diff --git "a/AdultNoteBook/Kernels/AdaBoost/.ipynb_checkpoints/4-deep-analysis-and-90-accuracy-checkpoint.ipynb" "b/AdultNoteBook/Kernels/AdaBoost/.ipynb_checkpoints/4-deep-analysis-and-90-accuracy-checkpoint.ipynb"
new file mode 100644--- /dev/null
+++ "b/AdultNoteBook/Kernels/AdaBoost/.ipynb_checkpoints/4-deep-analysis-and-90-accuracy-checkpoint.ipynb"
@@ -0,0 +1,6727 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:24:44.478199Z",
+     "iopub.status.busy": "2021-07-05T16:24:44.477948Z",
+     "iopub.status.idle": "2021-07-05T16:24:44.482786Z",
+     "shell.execute_reply": "2021-07-05T16:24:44.481957Z",
+     "shell.execute_reply.started": "2021-07-05T16:24:44.478171Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import plotly.express as px \n",
+    "import seaborn as sns\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from aif360.datasets import StandardDataset\n",
+    "from aif360.metrics import BinaryLabelDatasetMetric, ClassificationMetric\n",
+    "import matplotlib.patches as patches\n",
+    "from aif360.algorithms.preprocessing import Reweighing\n",
+    "#from packages import *\n",
+    "#from ml_fairness import *\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "\n",
+    "\n",
+    "\n",
+    "from IPython.display import Markdown, display"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:25:00.744888Z",
+     "iopub.status.busy": "2021-07-05T16:25:00.744557Z",
+     "iopub.status.idle": "2021-07-05T16:25:00.854534Z",
+     "shell.execute_reply": "2021-07-05T16:25:00.853632Z",
+     "shell.execute_reply.started": "2021-07-05T16:25:00.744839Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df=pd.read_csv('../../Data/adult.csv')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# EDA"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:26:57.863973Z",
+     "iopub.status.busy": "2021-07-05T16:26:57.863640Z",
+     "iopub.status.idle": "2021-07-05T16:26:57.894742Z",
+     "shell.execute_reply": "2021-07-05T16:26:57.893763Z",
+     "shell.execute_reply.started": "2021-07-05T16:26:57.863943Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>age</th>\n",
+       "      <th>workclass</th>\n",
+       "      <th>fnlwgt</th>\n",
+       "      <th>education</th>\n",
+       "      <th>education.num</th>\n",
+       "      <th>marital.status</th>\n",
+       "      <th>occupation</th>\n",
+       "      <th>relationship</th>\n",
+       "      <th>race</th>\n",
+       "      <th>sex</th>\n",
+       "      <th>capital.gain</th>\n",
+       "      <th>capital.loss</th>\n",
+       "      <th>hours.per.week</th>\n",
+       "      <th>native.country</th>\n",
+       "      <th>income</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>90</td>\n",
+       "      <td>?</td>\n",
+       "      <td>77053</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Widowed</td>\n",
+       "      <td>?</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4356</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>82</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>132870</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Widowed</td>\n",
+       "      <td>Exec-managerial</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4356</td>\n",
+       "      <td>18</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>66</td>\n",
+       "      <td>?</td>\n",
+       "      <td>186061</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Widowed</td>\n",
+       "      <td>?</td>\n",
+       "      <td>Unmarried</td>\n",
+       "      <td>Black</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4356</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>54</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>140359</td>\n",
+       "      <td>7th-8th</td>\n",
+       "      <td>4</td>\n",
+       "      <td>Divorced</td>\n",
+       "      <td>Machine-op-inspct</td>\n",
+       "      <td>Unmarried</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3900</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>41</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>264663</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Separated</td>\n",
+       "      <td>Prof-specialty</td>\n",
+       "      <td>Own-child</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3900</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   age workclass  fnlwgt     education  education.num marital.status  \\\n",
+       "0   90         ?   77053       HS-grad              9        Widowed   \n",
+       "1   82   Private  132870       HS-grad              9        Widowed   \n",
+       "2   66         ?  186061  Some-college             10        Widowed   \n",
+       "3   54   Private  140359       7th-8th              4       Divorced   \n",
+       "4   41   Private  264663  Some-college             10      Separated   \n",
+       "\n",
+       "          occupation   relationship   race     sex  capital.gain  \\\n",
+       "0                  ?  Not-in-family  White  Female             0   \n",
+       "1    Exec-managerial  Not-in-family  White  Female             0   \n",
+       "2                  ?      Unmarried  Black  Female             0   \n",
+       "3  Machine-op-inspct      Unmarried  White  Female             0   \n",
+       "4     Prof-specialty      Own-child  White  Female             0   \n",
+       "\n",
+       "   capital.loss  hours.per.week native.country income  \n",
+       "0          4356              40  United-States  <=50K  \n",
+       "1          4356              18  United-States  <=50K  \n",
+       "2          4356              40  United-States  <=50K  \n",
+       "3          3900              40  United-States  <=50K  \n",
+       "4          3900              40  United-States  <=50K  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:27:00.834338Z",
+     "iopub.status.busy": "2021-07-05T16:27:00.834016Z",
+     "iopub.status.idle": "2021-07-05T16:27:00.839732Z",
+     "shell.execute_reply": "2021-07-05T16:27:00.838718Z",
+     "shell.execute_reply.started": "2021-07-05T16:27:00.834310Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(32561, 15)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Dataset has 32561 rows and 15 columns."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:27:03.814230Z",
+     "iopub.status.busy": "2021-07-05T16:27:03.813921Z",
+     "iopub.status.idle": "2021-07-05T16:27:03.864502Z",
+     "shell.execute_reply": "2021-07-05T16:27:03.863793Z",
+     "shell.execute_reply.started": "2021-07-05T16:27:03.814204Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "age                  73\n",
+       "workclass             9\n",
+       "fnlwgt            21648\n",
+       "education            16\n",
+       "education.num        16\n",
+       "marital.status        7\n",
+       "occupation           15\n",
+       "relationship          6\n",
+       "race                  5\n",
+       "sex                   2\n",
+       "capital.gain        119\n",
+       "capital.loss         92\n",
+       "hours.per.week       94\n",
+       "native.country       42\n",
+       "income                2\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.nunique()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Label column has only two categories, hence it is a problem of classification. There are no constant columns nor there are any identifier column."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:02.068700Z",
+     "iopub.status.busy": "2021-07-05T16:35:02.068292Z",
+     "iopub.status.idle": "2021-07-05T16:35:02.095924Z",
+     "shell.execute_reply": "2021-07-05T16:35:02.094689Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:02.068667Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "age               0\n",
+       "workclass         0\n",
+       "fnlwgt            0\n",
+       "education         0\n",
+       "education.num     0\n",
+       "marital.status    0\n",
+       "occupation        0\n",
+       "relationship      0\n",
+       "race              0\n",
+       "sex               0\n",
+       "capital.gain      0\n",
+       "capital.loss      0\n",
+       "hours.per.week    0\n",
+       "native.country    0\n",
+       "income            0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are no null values in the dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:03.739240Z",
+     "iopub.status.busy": "2021-07-05T16:35:03.738768Z",
+     "iopub.status.idle": "2021-07-05T16:35:03.745896Z",
+     "shell.execute_reply": "2021-07-05T16:35:03.745052Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:03.739209Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "age                int64\n",
+       "workclass         object\n",
+       "fnlwgt             int64\n",
+       "education         object\n",
+       "education.num      int64\n",
+       "marital.status    object\n",
+       "occupation        object\n",
+       "relationship      object\n",
+       "race              object\n",
+       "sex               object\n",
+       "capital.gain       int64\n",
+       "capital.loss       int64\n",
+       "hours.per.week     int64\n",
+       "native.country    object\n",
+       "income            object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are 8 object type feautures rest of the features are of integer type."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:04.708192Z",
+     "iopub.status.busy": "2021-07-05T16:35:04.707812Z",
+     "iopub.status.idle": "2021-07-05T16:35:04.742550Z",
+     "shell.execute_reply": "2021-07-05T16:35:04.741480Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:04.708160Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "age                0.558743\n",
+       "fnlwgt             1.446980\n",
+       "education.num     -0.311676\n",
+       "capital.gain      11.953848\n",
+       "capital.loss       4.594629\n",
+       "hours.per.week     0.227643\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.skew()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There is skewness present in the data which needs to be removed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:05.649537Z",
+     "iopub.status.busy": "2021-07-05T16:35:05.648913Z",
+     "iopub.status.idle": "2021-07-05T16:35:05.661964Z",
+     "shell.execute_reply": "2021-07-05T16:35:05.661026Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:05.649498Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<=50K    24720\n",
+       ">50K      7841\n",
+       "Name: income, dtype: int64"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df['income'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Dataset is imbalanced."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:07.168945Z",
+     "iopub.status.busy": "2021-07-05T16:35:07.168374Z",
+     "iopub.status.idle": "2021-07-05T16:35:07.205495Z",
+     "shell.execute_reply": "2021-07-05T16:35:07.204571Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:07.168908Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>age</th>\n",
+       "      <th>fnlwgt</th>\n",
+       "      <th>education.num</th>\n",
+       "      <th>capital.gain</th>\n",
+       "      <th>capital.loss</th>\n",
+       "      <th>hours.per.week</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>32561.000000</td>\n",
+       "      <td>3.256100e+04</td>\n",
+       "      <td>32561.000000</td>\n",
+       "      <td>32561.000000</td>\n",
+       "      <td>32561.000000</td>\n",
+       "      <td>32561.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>38.581647</td>\n",
+       "      <td>1.897784e+05</td>\n",
+       "      <td>10.080679</td>\n",
+       "      <td>1077.648844</td>\n",
+       "      <td>87.303830</td>\n",
+       "      <td>40.437456</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>13.640433</td>\n",
+       "      <td>1.055500e+05</td>\n",
+       "      <td>2.572720</td>\n",
+       "      <td>7385.292085</td>\n",
+       "      <td>402.960219</td>\n",
+       "      <td>12.347429</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>17.000000</td>\n",
+       "      <td>1.228500e+04</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>28.000000</td>\n",
+       "      <td>1.178270e+05</td>\n",
+       "      <td>9.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>40.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>37.000000</td>\n",
+       "      <td>1.783560e+05</td>\n",
+       "      <td>10.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>40.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>48.000000</td>\n",
+       "      <td>2.370510e+05</td>\n",
+       "      <td>12.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>45.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>90.000000</td>\n",
+       "      <td>1.484705e+06</td>\n",
+       "      <td>16.000000</td>\n",
+       "      <td>99999.000000</td>\n",
+       "      <td>4356.000000</td>\n",
+       "      <td>99.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                age        fnlwgt  education.num  capital.gain  capital.loss  \\\n",
+       "count  32561.000000  3.256100e+04   32561.000000  32561.000000  32561.000000   \n",
+       "mean      38.581647  1.897784e+05      10.080679   1077.648844     87.303830   \n",
+       "std       13.640433  1.055500e+05       2.572720   7385.292085    402.960219   \n",
+       "min       17.000000  1.228500e+04       1.000000      0.000000      0.000000   \n",
+       "25%       28.000000  1.178270e+05       9.000000      0.000000      0.000000   \n",
+       "50%       37.000000  1.783560e+05      10.000000      0.000000      0.000000   \n",
+       "75%       48.000000  2.370510e+05      12.000000      0.000000      0.000000   \n",
+       "max       90.000000  1.484705e+06      16.000000  99999.000000   4356.000000   \n",
+       "\n",
+       "       hours.per.week  \n",
+       "count    32561.000000  \n",
+       "mean        40.437456  \n",
+       "std         12.347429  \n",
+       "min          1.000000  \n",
+       "25%         40.000000  \n",
+       "50%         40.000000  \n",
+       "75%         45.000000  \n",
+       "max         99.000000  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.describe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "All the columns are not present as they are of object type. Count of each column is 32561 showing there are no null values. Mean is very much greater than the median in capital gain and capital loss stating that there is high skewness present and data is skewed to the right side. Also there is high variance in Capital gain and Capital loss column. Min, Max, and interquartile ranges have variable difference, that means there are outliers present in the data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Univariate Analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:08.839479Z",
+     "iopub.status.busy": "2021-07-05T16:35:08.837615Z",
+     "iopub.status.idle": "2021-07-05T16:35:09.131486Z",
+     "shell.execute_reply": "2021-07-05T16:35:09.130826Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:08.839436Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<=50K    24720\n",
+       ">50K      7841\n",
+       "Name: income, dtype: int64"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,8))\n",
+    "plt.subplot(1,2,1)\n",
+    "df['income'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.subplot(1,2,2)\n",
+    "sns.countplot(x='income',data=df)\n",
+    "plt.ylabel('No. of People')\n",
+    "df['income'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Dataset if highly imbalanced. There is less than 25% of >50K income category while more than 75% of <=50K income."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:10.728010Z",
+     "iopub.status.busy": "2021-07-05T16:35:10.727634Z",
+     "iopub.status.idle": "2021-07-05T16:35:10.804001Z",
+     "shell.execute_reply": "2021-07-05T16:35:10.803077Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:10.727975Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Separating categorical and continuous variables\n",
+    "cat=[feature for feature in df.columns if df[feature].nunique()<45]\n",
+    "cont=[feature for feature in df.columns if df[feature].nunique()>45]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:11.248240Z",
+     "iopub.status.busy": "2021-07-05T16:35:11.247852Z",
+     "iopub.status.idle": "2021-07-05T16:35:11.596616Z",
+     "shell.execute_reply": "2021-07-05T16:35:11.595911Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:11.248209Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Private             22696\n",
+       "Self-emp-not-inc     2541\n",
+       "Local-gov            2093\n",
+       "?                    1836\n",
+       "State-gov            1298\n",
+       "Self-emp-inc         1116\n",
+       "Federal-gov           960\n",
+       "Without-pay            14\n",
+       "Never-worked            7\n",
+       "Name: workclass, dtype: int64"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,15))\n",
+    "plt.subplot(2,1,1)\n",
+    "df['workclass'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.ylabel('')\n",
+    "plt.subplot(2,1,2)\n",
+    "sns.countplot(x='workclass',data=df)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['workclass'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are 9 workclass in total including Never worked and one unknown category(?).Most individuals work in private sector and there are very few who have never worked or work without pay. There are 3 categories of govt job provided state, federal and local among which no. of people working in the local govt is highest."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:11.598122Z",
+     "iopub.status.busy": "2021-07-05T16:35:11.597716Z",
+     "iopub.status.idle": "2021-07-05T16:35:12.108023Z",
+     "shell.execute_reply": "2021-07-05T16:35:12.106821Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:11.598081Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "HS-grad         10501\n",
+       "Some-college     7291\n",
+       "Bachelors        5355\n",
+       "Masters          1723\n",
+       "Assoc-voc        1382\n",
+       "11th             1175\n",
+       "Assoc-acdm       1067\n",
+       "10th              933\n",
+       "7th-8th           646\n",
+       "Prof-school       576\n",
+       "9th               514\n",
+       "12th              433\n",
+       "Doctorate         413\n",
+       "5th-6th           333\n",
+       "1st-4th           168\n",
+       "Preschool          51\n",
+       "Name: education, dtype: int64"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,15))\n",
+    "plt.subplot(2,1,1)\n",
+    "df['education'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.ylabel('')\n",
+    "plt.subplot(2,1,2)\n",
+    "sns.countplot(x='education',data=df)\n",
+    "plt.xticks(rotation=45)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['education'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Most of the people are high school graduate. There are few who have done masters and doctorate. The no. of people who went through just the preschool or 1st to 4th is the least."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:12.109985Z",
+     "iopub.status.busy": "2021-07-05T16:35:12.109649Z",
+     "iopub.status.idle": "2021-07-05T16:35:12.558681Z",
+     "shell.execute_reply": "2021-07-05T16:35:12.557565Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:12.109951Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9     10501\n",
+       "10     7291\n",
+       "13     5355\n",
+       "14     1723\n",
+       "11     1382\n",
+       "7      1175\n",
+       "12     1067\n",
+       "6       933\n",
+       "4       646\n",
+       "15      576\n",
+       "5       514\n",
+       "8       433\n",
+       "16      413\n",
+       "3       333\n",
+       "2       168\n",
+       "1        51\n",
+       "Name: education.num, dtype: int64"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,15))\n",
+    "plt.subplot(2,1,1)\n",
+    "df['education.num'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.ylabel('')\n",
+    "plt.subplot(2,1,2)\n",
+    "sns.countplot(x='education.num',data=df)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['education.num'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Majority of individuals lie in the 9th 10th category of education no. which is a liitle higher than the median education number. People with least and highest educations are very few."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:12.560435Z",
+     "iopub.status.busy": "2021-07-05T16:35:12.560166Z",
+     "iopub.status.idle": "2021-07-05T16:35:12.869875Z",
+     "shell.execute_reply": "2021-07-05T16:35:12.868971Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:12.560409Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Married-civ-spouse       14976\n",
+       "Never-married            10683\n",
+       "Divorced                  4443\n",
+       "Separated                 1025\n",
+       "Widowed                    993\n",
+       "Married-spouse-absent      418\n",
+       "Married-AF-spouse           23\n",
+       "Name: marital.status, dtype: int64"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,15))\n",
+    "plt.subplot(2,1,1)\n",
+    "df['marital.status'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.ylabel('')\n",
+    "plt.subplot(2,1,2)\n",
+    "sns.countplot(x='marital.status',data=df)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['marital.status'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Majority of people are married to a civialian spouse or Never married. Least people are married to armed forces. From the above maritial status data we can see that there are less young people in the workforce as compared to young ones."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:12.871334Z",
+     "iopub.status.busy": "2021-07-05T16:35:12.871082Z",
+     "iopub.status.idle": "2021-07-05T16:35:13.433357Z",
+     "shell.execute_reply": "2021-07-05T16:35:13.432594Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:12.871308Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Prof-specialty       4140\n",
+       "Craft-repair         4099\n",
+       "Exec-managerial      4066\n",
+       "Adm-clerical         3770\n",
+       "Sales                3650\n",
+       "Other-service        3295\n",
+       "Machine-op-inspct    2002\n",
+       "?                    1843\n",
+       "Transport-moving     1597\n",
+       "Handlers-cleaners    1370\n",
+       "Farming-fishing       994\n",
+       "Tech-support          928\n",
+       "Protective-serv       649\n",
+       "Priv-house-serv       149\n",
+       "Armed-Forces            9\n",
+       "Name: occupation, dtype: int64"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(20,15))\n",
+    "plt.subplot(2,1,1)\n",
+    "df['occupation'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.ylabel('')\n",
+    "plt.subplot(2,1,2)\n",
+    "sns.countplot(x='occupation',data=df)\n",
+    "plt.xticks(rotation=45)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['occupation'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can observe over here that prof-speciality has the highest number for people than any other occupation. followed by craft repair persons. Minimum occupation category is the armed forces with only 9 people in it. There is an unknown category of occupation too."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:13.434688Z",
+     "iopub.status.busy": "2021-07-05T16:35:13.434305Z",
+     "iopub.status.idle": "2021-07-05T16:35:13.709834Z",
+     "shell.execute_reply": "2021-07-05T16:35:13.709127Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:13.434658Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Husband           13193\n",
+       "Not-in-family      8305\n",
+       "Own-child          5068\n",
+       "Unmarried          3446\n",
+       "Wife               1568\n",
+       "Other-relative      981\n",
+       "Name: relationship, dtype: int64"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(20,8))\n",
+    "plt.subplot(1,2,1)\n",
+    "df['relationship'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.ylabel('')\n",
+    "plt.subplot(1,2,2)\n",
+    "sns.countplot(x='relationship',data=df)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['relationship'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are much more husband working than their wives. There are 25% individuals working who fall in not in family category."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:14.808243Z",
+     "iopub.status.busy": "2021-07-05T16:35:14.807932Z",
+     "iopub.status.idle": "2021-07-05T16:35:15.255826Z",
+     "shell.execute_reply": "2021-07-05T16:35:15.255091Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:14.808215Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "White                 27816\n",
+       "Black                  3124\n",
+       "Asian-Pac-Islander     1039\n",
+       "Amer-Indian-Eskimo      311\n",
+       "Other                   271\n",
+       "Name: race, dtype: int64"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(20,8))\n",
+    "plt.subplot(1,2,1)\n",
+    "df['race'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.subplot(1,2,2)\n",
+    "sns.countplot(x='race',data=df)\n",
+    "plt.xticks(rotation=45)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['race'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "SInce this is from european countries, most of the individuals working here are white. There is also an other category where minory races are present."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:15.348302Z",
+     "iopub.status.busy": "2021-07-05T16:35:15.347799Z",
+     "iopub.status.idle": "2021-07-05T16:35:15.540302Z",
+     "shell.execute_reply": "2021-07-05T16:35:15.539609Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:15.348270Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Male      21790\n",
+       "Female    10771\n",
+       "Name: sex, dtype: int64"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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vaWZdcjwLHnsAgPXfdjirbLots6/9NU9dVyWii1VfNI119jz4ea+dPf0Cnr7xUkiwxg5vYa1X7gPAE1ecydx7r2XSBluy/r98HoCnb/kDA3Nm//M5UgYvAr4NHJY7iCRJan2WsDFSKlcPAN6RO0crefx3pzD5hTsz9V3/RVq8kLRwPvPuv4m5d13NJh86gejpZfEzTz7vdQtm1nj6xkvZ6MBjie5eHj3/K6z64lfSvdoUFjxyD5sc/P1GuZtZo2ftjXnm5svZ4N1HNP8LSs91aKlc/Xmtv+8PuYNIkqTW5nTEMVAqV6cCx+fO0UoG5j/DvL/fwhrb7wVAdPfSNXkNnrr+Ytba7d1ETy8A3auv/bzXLpz1IJM23oau3slEVzerbL4dc+68EgjSwCJSSgwsnE90dTP7r79gzZ3eTnT79wRlF8DJpXJ1Uu4gkiSptVnCxsZxwPq5Q7SSRU/+g+7V1mLWxd/l4TM/zaxLjmdgwTwWPvEQ8/9+CzPO+RyP/KTM/Bl3Pu+1k9Z/AfMfvIXFc2czsHAec++dzuLZj9G1ymqs+qJpzDjr03SvsQ6xyuosmHEnq229e4ZvKA1pa+BzuUNIkqTW5vDBKJXK1dcA78+do9WkgcUseOQe1n3Tx1llk214/Lc/ZPbVP4OBxQzMe4qN/u0YFsy4k5kXfJtNP3YaEfHP1/auvzlr7bofj57330TvZCZt8EKIxt8Lpuy6H1N23Q+AWZccz5TXvJ+nbryUefddT+8GJdZ+1XuzfF9pkC+XytUf1fr7HswdRJIktSZHwkahVK52Ad/LnaMV9ay5Pt1rrs8qm2wDwGrbvJoF/7iH7jXXZ7WtX0VEsMom2xARDMyd/bzXr7nDXmz8we+x0fu/TdfkNehdd9PnPL7gH/eQUqJ33c2Yc/v/MfWdZRY98QgLH3+oKd9PWo7VcZVUSZK0HJaw0fkQsFPuEK2oe4116FlrfRbOagwGzLv/RnrX34LVttqNeQ/cBMDCxx8iLV5E16prPe/1SxbsWDT7UebceRWrv/T1z3n8yT/9iLVf+wEYWARpoHEwgrRo/vh9KWn49i+Vq69f8dMkSVIncjriCJXK1bWAb+TO0crWfdPHeeyio0mLF9Gz9kas97bP0NW7CrMu/h4Pn34o0d3Len2fJSJY9NQsZv3meDZ899cAmPmrbzIw9yno6mbdN3+crslr/PN959x5FZM2ejE9a64HwKQNXsjDp3+S3g1KjamLUms4tlSuvrLW3zeQO4gkSWotkVLKnaEtlcrVbwJfzJ1DUkv7UK2/76zcIdRapk2blqZPn547htS2Hjji5bkjaALb4is3j9l7RcS1KaVpQz3mdMQRKJWrmwGfyZ1DUsv7ZqlcXT13CEmS1FosYSNzJLBq7hCSWt7GwH/kDiFJklqLJWwllcrV7YEDc+eQ1DY+UypX184dQpIktQ5L2Mr7Ov5zkzR8U3D6siRJGsQysRJK5eoOwNtz55DUdg4vlatTcoeQJEmtwRK2cv4rdwBJbWlt4NO5Q0iSpNZgCRumUrm6NbBf7hyS2tZnS+XqmrlDSJKk/Cxhw1fGf16SRm4d4FO5Q0iSpPwsFcNQKle3AD6QO4ektve5Urm6Ru4QkiQpL0vY8Pwn0Js7hKS2tx5wWO4QkiQpL0vYCpTK1Y2AD+fOIWnC+HypXHWzd0mSOpglbMU+B0zOHULShLE+cEDuEJ0gIs6IiEcj4m+DjlUi4qGIuKG4vG3QY1+MiLsj4o6IeMug43sXx+6OiPKg41tGxF+K4+dFxKTmfTtJUjuzhC1Hce7Gx3PnkDThHJo7QIc4C9h7iOPHpZR2LC4XA0TES4H3Ai8rXnNiRHRHRDfwA+CtwEuBA4rnAny7eK8XA0/grAlJ0jBZwpbvfYBLSksaazuXytVdc4eY6FJK/ws8Psyn7wOcm1Kan1K6D7gb2KW43J1SujeltAA4F9gnIgJ4A/A/xevPBt45lvklSROXJWz5PpY7gKQJy9GwfA6LiJuK6YrrFMc2Bf4+6DkPFseWdXw94MmU0qKljg8pIg6JiOkRMX3mzJlj9T0kSW3KErYMpXJ1Z2Cn3DkkTVj7l8rV9XKH6EAnAS8CdgRmAMc040NTSqeklKallKZNnTq1GR8pSWphlrBlcxRM0niajOcQNV1K6R8ppcUppQHgVBrTDQEeAjYf9NTNimPLOj4LWDsiepY6LknSClnChlAqV9fE1cskjb+Pl8pVfw43UURsPOjuu4AlKydeCLw3IlaJiC2BrYC/AtcAWxUrIU6isXjHhSmlBPwB2K94/UHABc34DpKk9tez4qd0pPcDa+QOIWnC25LGqnvV3EEmooj4KbAHsH5EPAh8FdgjInYEElCjmPWQUrolIs4HbgUWAZ9MKS0u3ucw4FKgGzgjpXRL8RFfAM6NiK8D1wOnN+ebSZLanSVsaIfkDiCpYxyKJWxcpJSGmtGwzKKUUvoG8I0hjl8MXDzE8Xt5djqjJEnD5jSYpZTK1VcCr8idQ1LHeEupXHWlBkmSOogl7Pk+kjuApI7SzbPnFUmSpA5gCRukVK72APvmziGp47wndwBJktQ8lrDnej2NDTglqZleWypXN17x0yRJ0kRgCXsupwRJyqELeHfuEJIkqTksYYVir5535c4hqWM5JVGSpA5hCXvWa4ENc4eQ1LF2L5Wrm+cOIUmSxp8l7FlORZSUUwD75w4hSZLGnyUMKJWrAfxr7hySOp5TEiVJ6gCWsIZXAZvkDiGp473SKYmSJE18lrAG9waT1CrelDuAJEkaX5awhrflDiBJhTfnDiBJksZXx5ewUrm6CbBN7hySVHhTcZ6qhhAR60TE9rlzSJI0Gh1fwoA9cweQpEGmAjvkDtFKIuKKiFgrItYFrgNOjYhjc+eSJGmkLGHwhtwBJGkpTkl8rikppdk0VrE9J6W0K547J0lqY5YwR8IktR4LxnP1RMTGNPZRuyh3GEmSRqujS1ipXC0BW+bOIUlLeW2pXF0ld4gWcgRwKXB3SumaiHghcFfmTJIkjVhP7gCZOQomqRWtCrwG+F3uIK0gpfQz4GeD7t+LW4tIktpYp5cwzweT1KreTIeXsIg4AUjLejyl9OkmxpEkacx0eglzJExSq9o9d4AWMD13AEmSxkPHlrBSufpiYNPcOSRpGV5RKlej1t+3zJGgiS6ldHbuDJIkjYeOLWHAtNwBJGk51qSxkfztuYPkFhFTgS8ALwUmLzmeUnJKuSSpLXXy6og75g4gSSuwc+4ALeLHwG00VrP9GlADrskZSJKk0bCESVLrsoQ1rJdSOh1YmFL6Y0rpYFxYSZLUxjp5OuKOuQNI0gpYwhoWFtczIqIPeBhYN2MeSZJGpSNHwkrl6kbAhrlzSNIKvKJUrkbuEC3g6xExBfg88O/AacBn80aSJGnkOnUkbMfcASRpGFycA0gpXVTcrOPWIpKkCcASJkmtbWc6vIRFxJkMsWlzcW6YJEltp1NL2CtyB5CkYdqJxuqAneyiQbcnA++icV6YJEltqVNL2I65A0jSMG2VO0BuKaWfD74fET8F/i9THEmSRq3jFuYolauTgRfnziFJw/TC3AFa0FbABrlDSJI0Up04ErYFHVg+JbWtLXMHyC0inqJxTlgU148AX8gaSpKkUejEMrJF7gCStBJWK7bV6FgppTVTSmsNut566SmKkiS1k04cCXtB7gCStJJeSGP0p6NExE7LezyldF2zskiSNJYsYZLU+l4IXJk7RAbHFNeTgWnAjTSmJG4PTAd2z5RLkqRR6cTpiJYwSe2mIxfnSCntmVLaE5gB7JRSmpZS2pnGNiMP5U0nSdLIdWIJ85wwSe2mI0vYINuklG5eciel9Ddg24x5JEkaFacjSlLr6/QSdlNEnAb8qLj/fuCmjHkkSRqVjiphpXK1C9gsdw5JWkml3AEy+xDwCeDw4v7/AifliyNJ0uh0VAkDNgF6c4eQpJW0Xu4AOaWU5gHHFRdJktpep50TtknuAJI0AquVytVJuUM0W0ScX1zfHBE3LX3JnU+SpJHqtJGwtXMHkKQRWht4NHeIJlsy/fBfsqaQJGmMdVoJWyt3AEkaoXXosBKWUppR3NwXODel9HDOPJIkjZVOm464Zu4AkjRC6+QOkNGawOUR8aeIOCwiNswdSJKk0ei0EuZImKR21bElLKX0tZTSy4BPAhsDf4yI32aOJUnSiFnCJKk9dGwJG+RR4BFgFrBB5iySJI2YJUyS2kPHlrCIODQirgB+R2O5/o+mlLbPm0qSpJFzYQ5Jag8dW8KAzYHPpJRuyB1EkqSxMKyRsIj48FL3uyPiq+MTaVxZwiS1qym5AzRbRCz5mX0U8EBErDv4kjObJEmjMdyRsDdGxL7Ah4F1gbOAP45XqHFkCZPUrnpzB8jgJzT2CLsWSEAMeiwBL8wRSpKk0RpWCUspvS8i3gPcDDwDvC+l9OdxTTY+VssdQJJGqDt3gGZLKf1Lcb1l7iySJI2lYZWwiNgKOBz4ObAt8G8RcX1Kac54hhsHseKnSFJL6rSFlIiInZb3eErpumZlkSRpLA13OuKvgcNSSr+NiAA+B1wDvGzcko2PlDuAJI1Qx42EAccU15OBacCNNP6Ytj0wHdg9Uy5JkkZluCVsl5TSbICUUgKOiYhfj18sqf18oPvyq18e983PnUMT05Os8Sj05Y7RVCmlPQEi4hfATimlm4v72wGVjNEkSRqV4ZawVSPiOGDTlNLeEfFSGn+BvHP8oknt44Xx8P1H9py5UwSTcmfRhHV77gAZbbOkgAGklP4WEdvmDCRJ0mgM9xyDs4BLgY2L+3cCnxmHPONtIHcATUxn9B41wwKmcdbJP79uiojTImKP4nIqcFPuUJIkjdRwS9j6KaXzKX4JSCktAhaPW6rxszB3AE08r+m6+eZS1z92y51DE147/swdKx8CbqGxQNThwK3FMUmS2tJwpyM+ExHrUSxsERG7AfVxSzV+FuQOoInnxN7v5Y6gztCxJSylNA84rrhIktT2hlvCPgdcCLwoIv4MTAX2G7dU48cSpjH1we7fXLVWzHGFNjXDotwBcomIV9NYiOMFDPr/VkrJzZolSW1puCXsRcBbgc2BfYFdV+K1rcQSpjHTy6IFX+r58aa5c6hjtOPsg7FyOvBZ4Fo6eERQkjRxDPecsP8ulqhfB9gTOBE4adxSjZ+5uQNo4qj0nHVVbyzeIncOdYwncgfIqJ5SuiSl9GhKadaSS+5QkiSN1HBL2JK/PPYBp6aUqtCWK8E9njuAJoa1eeqJA7p/v0PuHOoonVzC/hARR0XE7hGx05JL7lCSJI3UcKcUPhQRPwTeDHw7IlZh+AWulTyWO4AmhhN7v3dTV/D63DnUUTq5hO1aXE8bdCwBb8iQRZKkURtuCdsf2Bs4OqX0ZERsDPzH+MUaN5YwjdqL4qH7d++69VW5c6jjPJk7QC4ppT1zZ5AkaSwNq4SllOYAvxh0fwYwY7xCjSNLmEat2Jj5BblzqON03EhYRHxueY+nlI5tVhZJksZSO65wOBqWMI3K67puvOkFXY+6MbNy6LgSBqyZO0Cr2/k/zskdQRPYtUcdmDuCNGFZwqSV8IPe47tzZ1DHejJ3gGZLKX0tdwZJksZDOy6uMRqWMI3Ywd2XXLlmzH1Z7hzqSPOo1OflDiFJksZGp5WwJ3CjT43AJBbO/2LPT9wTTLn4ByRJkiaQjiphtf6+ATrzvAqN0td6zrq6NxZvljuHOlYtd4AcIuLw4vrVubNIkjSWOqqEFR7JHUDtZR1mP/7e7j/smDuHOtq9uQNk8qHi+oSsKSRJGmOdtjAHwN3AdrlDqH2cNOl7f4vgdblzqKPdlztAJrdFxF3AJhFx06DjAaSU0vaZckmSNCqdWMLuyh1A7WOreLC2a9y2e+4c6ngdWcJSSgdExEbApcA7cueRJGmsdOJ0REuYhu303qP+EUFv7hzqeJ06HZGU0iMppR2AGTT2DVsTeDildH/eZJIkjZwlTFqGPbuuv3GLrpm75s4h0aEjYUtExOtp/Oz+AXAicGdErHCKcEScERGPRsTfBh1bNyIuj4i7iut1iuMREcdHxN0RcVNE7DToNQcVz78rIg4adHzniLi5eM3xERFj+b0lSROXJUwaUkrH936/E6frqvXMBx7KHSKzY4G9UkqvTym9DngLcNwwXncWsPdSx8rA71JKWwG/K+4DvBXYqrgcApwEjdIGfBXYFdgF+OqS4lY856ODXrf0Z0mSNKROLGEPA3Nyh1Br+0j3xVe5MbNaxP1U6il3iMx6U0p3LLmTUroTVjxNOKX0v8DjSx3eBzi7uH028M5Bx89JDVcDa0fExjQK3+UppcdTSk8AlwN7F4+tlVK6OqWUgHMGvZckScvVcSWs1t+XaKyQKA1pEgvnf6HnXDdmVqvo2PPBBpkeEadFxB7F5VRg+gjfa8OU0ozi9iPAhsXtTYG/D3reg8Wx5R1/cIjjQ4qIQyJiekRMnzlz5gijS5Imio4rYQWnJGqZjuw5042Z1UruWPFTJrxPALcCny4utxbHRqUYwWrKKGNK6ZSU0rSU0rSpU6c24yMlSS2sU895sYRpSOtSn7V/9xU75s4hDXJt7gC5pZTm0zgv7NgxeLt/RMTGKaUZxZTCR4vjDwGbD3reZsWxh4A9ljp+RXF8syGeL0nSCnXqSNituQOoNZ086bu3RDAldw5pkOtyB5hgLgSWrHB4EHDBoOMHFqsk7gbUi2mLlwJ7RcQ6xYIcewGXFo/NjojdilURDxz0XpIkLVenjoRdkzuAWs/W8ff7Xhl3uDGzWskc4PbcIdpVRPyUxijW+hHxII1VDvuB8yPiw8D9wP7F0y8G3kbjnOE5wIcAUkqPR8SRPPv/jSNSSksW+ziUxgqMqwKXFBdJklaoU0vYHUAdHPHQs07vPerRCLbMnUMa5AYq9cW5Q7SrlNIBy3jojUM8NwGfXMb7nAGcMcTx6cB2o8koSepMHTkdsVgh0dEw/dMbuq67cfOux9yYWa3GqYjLEBGH5M4gSdJIdWQJK/w1dwC1ipSO7/3+CvcckjLo+EU5liNyB5AkaaQsYep4H+u+6Ko1Yt5Lc+eQhuBI2DKklH6YO4MkSSPVySXsL7kDKL9VWDDvP3rOc2NmtaJ5uJIrABGxWUT8MiJmRsSjEfHziHAvP0lS2+rYElbr73sE+HvuHMrryJ4zru6JAX+ZUyu6kUp9Ue4QLeJMGkvIbwxsAvy6OCZJUlvq2BJWcEpiB1uX+qx3d//vTrlzSMvwp9wBWsjUlNKZKaVFxeUsYGruUJIkjVSnlzCnJHawH0467pYI1sqdQ1qG3+YO0EJmRcQHIqK7uHwAmJU7lCRJI9XpJeyPuQMoj23igfumxZ2vyp1DWob5OBI22ME0NlV+BJgB7EexmbIkSe2oUzdrXmI68Biwfu4gaq7TJx09042Z1cKuolKfkztEq0gp3Q+8I3cOSZLGSkeXsFp/30CpXL0cOCB3FjXPG7uuvWGzeGyX3Dmk5XAqIhARX1nOwymldGTTwkiSNIY6fToiwG9yB1AzpXR87w9WyZ1CWgFLWMMzQ1wAPgx8IVcoSZJGq6NHwgqXAgmI3EE0/j7e/esrV495r86dQ1qOJ2lMle54KaVjltyOiDWBw2mcC3YucMyyXidJUqvr+JGwWn/fP4Drc+fQ+FuFBfP+ved8zwNTq7uCSn1x7hCtIiLWjYivAzfR+MPhTimlL6SUHs0cTZKkEev4ElZwSmIH+Gbv6X/piYFNcueQVsCpiIWIOAq4BngKeHlKqZJSeiJzLEmSRs0S1mAJm+DWo/7Yv3b96RW5c0jD4M+jZ30e2AT4MvBwRMwuLk9FxOzM2SRJGjHPCWu4CqgDU3IH0fg4ZdKxt0bwutw5pBW4nkr9ntwhWkVKyT8USpImJP8HB9T6+xYBl+fOofHxknjg3p3iLjdmVjs4P3cASZI0/ixhzzovdwCNjzMmHTUrwlFftQVLmCRJHcAS9qyLAM8xmGD26rrm+k1i1itz55CG4Voq9Xtzh5AkSePPElao9ffNA36RO4fGUkrH9Z44OXcKaZgcBZMkqUNYwp7rx7kDaOx8svuCK1eP+dvmziENkyVMkqQOYQl7rt8DM3KH0OhNZv7cz/b8zwtz55CG6Roq9VruEJIkqTksYYPU+vsGcIGOCeFbvaf9tScGNs6dQxomf+5IktRBLGHP55TENrc+T858Z9efd8qdQxqmBPwsdwhJktQ8lrCl1Pr7pgN35s6hkTtl0rG3RbBm7hzSMF1Gpf5A7hCSJKl5LGFD+0nuABqZbeP+e14Rd786dw5pJZyUO4AkSWouS9jQzgQW5w6hlXfGpKMej6A7dw5pmP5OY49CSZLUQSxhQ6j19z0AXJA7h1bO3l1/uW7jeNyNmdVOTqVS9w8+kiR1GEvYsh2fO4CGLxgYOLb35NVz55BWwiLgtNwhJElS81nClqHW3/dH4MbcOTQ8n+y+4MrVYv42uXNIK+FXVOruSyhJUgeyhC3fCbkDaMUaGzP//EW5c0gryQU5JEnqUJaw5fsxMCt3CC1ff++pf+12Y2a1lzuo1H+fO4QkScrDErYctf6+ecCpuXNo2TbgiZn7dF25c+4c0ko6OXcASZKUjyVsxU6kcQK9WtApk469PYI1cueQVsLjuCCHJEkdzRK2ArX+vr8Dv8qdQ8/3srjv7h3inlflziGtpO9SqT+dO4QkScrHEjY8R+UOoOc7fdLRT7oxs9pMHbe/kCSp41nChqHW3/dXoJo7h571tq6/XLdRPDEtdw5pJZ1ApV7PHUKSJOVlCRu+r+QOoIZgYODo3pPcmFnt5mnguNwhJElSfpawYar1912H54a1hE91//LK1WKBGzOr3fyASv3x3CEkSVJ+lrCV8xUg5Q7RyVZl/pzDe37x4tw5pJU0BzgmdwhJktQaLGErodbfdzPwP7lzdLJv955yTXekjXLnkFbSD6nUZ+YOIUmSWoMlbOVVgIHcITrRhjz+6Nu7rnJjZrWbebjCqiRJGsQStpJq/X23AufmztGJTpl07B1uzKw29F0q9Rm5Q0iSpNZhCRuZrwGLc4foJC+Pe+/aPu51Y2a1m5nAt3KHkCRJrcUSNgK1/r47gdNy5+gkp006uu7GzGpDFSr12blDSJKk1mIJG7kvA0/mDtEJ/qXrqms3jCfdmHkF5i1K7HLq0+xw8tO87MSn+eof5gHw4QvmssPJT7P9SU+z3/lzeHrB8xf4nDVngD3PfoY1vjmbwy6e+8/j8xcl9v7RM2x34tOceM2Cfx4/5NdzuW6Gg8ErcDtwSu4QkiSp9VjCRqjW3/cYjUU6NI6CgYGjen+4Zu4c7WCVbvj9Qatz48fX4IaPrc5v7lnE1Q8u4ri9J3Pjx9fgpk+swRZTuvj+Xxc877WTe4Ij91yFo/ea/Jzjl96ziNds0cNNn1id/3fTQgBufGQxiwdgp40dmFyBz1OpL8odQpIktR5L2Oj8ALgtd4iJ7PCeX/x51Viwde4c7SAiWGNSALBwABYuhgDWWqVxLKXE3IWJGOK1q08KXrNFD5N7nnu8twvmLEwsXAypGED77z/M58g3rDJ+X2RiqFKpX5w7hCRJak2WsFGo9fctAg7PnWOiWo15z3yq+5db5c7RThYPJHY8+Wk2OOop3vzCHnbdrNGqPnTBXDY65mlunzXAp3adNOz3e/OLeqg9OcBupz/Dp3edxIV3LGSnjbvYZE1/dCzHAuAzuUNIkqTW5W9So1Tr77scOD93jonoO70/dGPmldTdFdzw8TV48HNr8teHF/O3RxvnbZ25z6o8/Lk12Hb9Ls7728Jhv19PV/CTfVfj+o+twbtf2sN3r17A53dfhc9dOo/9zp/DhXcM/706yHFU6nfnDiFJklqXJWxsfBZ4KneIiWQjHv9HX9dfXpk7R7tae3KwZ6mH39z97ClJ3V3Be7fr5ee3jew0pROvWcCBO/Ry9YOLmbJKcN5+q3LMVc8/v6zDPQB8PXcISZLU2ixhY6DW3/cw8JXcOSaSUycdc1cEq+fO0U5mPjPAk/MaJ27NXZi4/N5FbLNeF3c/PgA0zgm78I5FvGT9lf/P/om5iYvuWsSBO/QyZ2GiKyCi8Tl6jo9SqT+dO4QkSWptPSt+iobpBOAgYMfMOdre9nHPXdvFfW7MvJJmPJ046FdzWDwAAwn2f1kvfVv38Noz5zB7fiIl2GGjLk7qWxWAC+9YyPSHF3PEno0VEUvffYrZ8xMLFsOvbl/EZf+2Gi+d2lgB8Yg/zudLr12Frgje8uIefnDNHF5+0kI+vvPwzy/rAKdTqV+WO4QkSWp9lrAxUuvvW1wqVw8CrgH8zXQUTpt09OwIR2lX1vYbdnP9x9Z43vE/Hzz0gOI7tunlHdv0/vN+7TPL3gnguL2fXbp+ck9w2b85SLmUB4HP5Q4hSZLag7/ojqFaf99NOC1xVN7edeX0DaK+c+4c0ko6hEp9du4QkiSpPVjCxt5RwJ9zh2hHXQwsPqr3h1Ny55BW0llU6pfkDiFJktqHJWyM1fr7BoADAU/OX0mf6fmfqybHQvcFUzt5mMbqqJIkScNmCRsHtf6+e4HP587RTlZj3jOf7L7AAqZ28zEq9Sdzh5AkSe3FEjZOav19pwDV3DnaxdG9J0/vjrRh7hzSSjiHSv2i3CEkSVL7sYSNr48Aj+UO0eo2ZtYjb+36qxszq53cDnwydwhJktSeLGHjqNbf9wjw8dw5Wt1pk46+O4LVcueQhmkOsJ+bMkuSpJGyhI2zWn/fz4GTcudoVTvE3Xe+NO53Y2a1k09Qqd+SO4QkSWpflrDmOBy4KneIVnTapGOecmNmtZHTqdTPyR1CkiS1N3/5bYJaf99CYD/gkdxZWsk7u/5v+lQ3Zlb7uBE4LHcISZLU/ixhTVLr73sYeDewMHeWVtDFwOL+3lPXzp1DGqbZwLup1OflDiJJktqfJayJav19/4f7hwHw+Z6fXTk5Fr44dw5pmD5CpX5X7hCSJGlisIQ1Wa2/7wTg/+XOkdPqzH36490XbpM7hzRM36VS/1nuEJIkaeKwhOXxMeD63CFyOaaxMfMGuXNIw3Ahjl5LkqQxZgnLoNbfNxf4V2BW7izNtgmPzXhL1zW75M4hDcN04AAq9YHcQSRJ0sRiCcuk1t9XA95OY+PXjnHapKPvcWNmtYH7gbdTqXfUf5+SJKk5LGEZ1fr7rgLeAyzKnaUZXhF33bFtPODGzGp1deBtVOpuKSFJksaFJSyzWn/fRcAhuXM0w6mTjnnGjZnV4hYC/0qlfmvuIJIkaeLyF+IWUOvvOxP4r9w5xtO7uv50zfoxe6fcOaQV+CiV+u9zh5AkSRObJaxF1Pr7vgWckDvHeOhiYPG3ek9bN3cOaQWOoFI/O3cISZI08VnCWstngPNyhxhr/9Fz3p8nx8IX5c4hLcfxVOpfzR1CkiR1BktYC6n19w0ABwK/y51lrKzO3KcO6b5o29w5pOX4AZX64blDqLkiohYRN0fEDRExvTi2bkRcHhF3FdfrFMcjIo6PiLsj4qaI2GnQ+xxUPP+uiDgo1/eRJLUXS1iLqfX3LQDeBfw5d5axcGzvidd1R5qaO4e0DCcDn8odQtnsmVLaMaU0rbhfBn6XUtqKxh/DysXxtwJbFZdDgJOgUdqArwK7ArsAX11S3CRJWh5LWAuq9fc9BewNXJE5yqhsyswZe3Vd68bMalWnAodSqafcQdQy9gGWnBd4NvDOQcfPSQ1XA2tHxMbAW4DLU0qPp5SeAC6n8bNbkqTlsoS1qFp/39PA24DLcmcZqdMmHX1vBKvmziEN4XTgYxawjpaAyyLi2ohYsk3IhimlGcXtR4ANi9ubAn8f9NoHi2PLOv48EXFIREyPiOkzZ84cq+8gSWpTlrAWVuvvmwu8A6jmzrKydoo7b39J/N2NmdWKzgIOsYB1vNeklHaiMdXwkxHxusEPppQSjaI2JlJKp6SUpqWUpk2d6gxtSep0lrAWV+vvmw/8K/DL3FlWxqmTjpkbQeTOIS3lHODDVOoDuYMor5TSQ8X1ozR+vu4C/KOYZkhx/Wjx9IeAzQe9fLPi2LKOS5K0XJawNlAs1rE/bbJ8/X7df7xmvXjqFblzSEs5AfiQBUwRsXpErLnkNrAX8DfgQmDJCocHARcUty8EDixWSdwNqBfTFi8F9oqIdYoFOfYqjkmStFw9uQNoeGr9fYtK5er7gQXAv+XOsyzdLF70jZ4z3JhZrSQBZSr17+QOopaxIfDLiIDG/wd/klL6TURcA5wfER8G7qfxxy+Ai2mco3s3MAf4EEBK6fGIOBK4pnjeESmlx5v3NSRJ7coS1kZq/X2LS+XqB4HHgM9mjjOk/+w576pVYuFrc+eQCgtojH79JHcQtY6U0r3ADkMcnwW8cYjjCfjkMt7rDOCMsc4oSZrYnI7YZmr9fQO1/r7PAYcCi3LnGWx15j710e7qS3LnkAqzgbdawCRJUquxhLWpWn/fSUAfUM+dZYnv9f7gui43ZlZreBh4LZX673MHkSRJWpolrI3V+vsuA14F1DJHYbOY+fAbu65zY2a1gluB3anUb8odRJIkaSiWsDZX6++7FdgVuCpnjtN7j7rPjZnVAv4AvIZK/YHcQSRJkpbFEjYB1Pr7HgXeAJyb4/OnxR23bR0PujGzcvsO8GYq9SdyB5EkSVoeS9gEUevvmwe8DziCxpLcTXPKpGPnuzGzMpoN7Eul/gUq9cW5w0iSJK2IJWwCqfX3pVp/31eBtwIzm/GZ+3f/4a/rxlM7NuOzpCHcArySSv0XuYNIkiQNlyVsAqr1911KYw+cK8bzc7pZvOjInjPXH8/PkJbjp8CuVOp35g4iSZK0MixhE1Stv28GjU1HvwYMjMdnfKHnp1euEoteOB7vLS3HQuBwKvX3Uak/kzuMJEnSyrKETWDFxs4V4E3AjLF87zWYM/sj3Ze8dCzfUxqGB4A9qdSPzx1EkiRppCxhHaDW3/cHYEfg8rF6z2JjZqciqpnOBF5Opf7n3EEkSZJGwxLWIYpl7N8CfBFYMJr32jwefegNXdfvNibBpBV7BHg7lfrBVOqzc4eRJEkaLUtYBylWT+wHXsEoNnc+vfeo+yOYPHbJpGU6D3gZlfpFuYNIkiSNFUtYB6r1990KvAY4HFiphQ12idtu3Soe2n1cgknPmgW8h0r9vVTqj+cOI0mSNJYsYR2qWLTjeOBlwKXDfd0PJx23wI2ZNc5+TWP06/zcQSRJksZDT+4AyqvW33c/sHepXD0QOA5Yd1nPfW/37/+yTjy9a9PCqdPMAD5Ppf7T3EEkSZLGkyNhAqDW33cOsC0w5OhDN4sXHdFz1gbNTaUOsYjGHwC2sYBJkqROYAnTP9X6+x6t9fe9h8YqircMfuyLPT+5clIs2jJPMk1g/wvsRKX+OSr1p3KHkSRJagZLmJ6n1t93GbADcBgwa02eqR/c/ZuXZY6liaUG7E+l/noq9Ztzh5EkSWomS5iGVOvvW1zr7/sB8OL/7vnRt7sirZk7kyaEp4EvAdtSqf8sdxhJkqQcXJhDy1Xr73sS+r5FZcpPga8D7wNXR9RKmwecCnyLSn1G7jCSJEk5ORKm4anUa1TqHwB2Ai7LHUdtYz7wfeBFVOqftoBJkiQ5EqaVVanfALyFypTdgC8Cb8eRMT3fAuA0GiNfD+YOI0mS1EosYRqZSv1qYB8qU7YDysB7ge68odQCFgBnAN+kUv977jCSJEmtyOmIGp1K/W/FNMWtgJNonPujzjMHOBnYikr9ExYwSZKkZXMkTGOjUr8POJTKlCOAzwKfAFxRceK7DzgROJ1K/YncYSRJktqBJUxjq1J/BPgClSnfBA4EPgq8PG8ojbEE/BY4AahSqQ9kziNJktRWLGEaH5V6ncYv6ScUi3gcArwHWC1rLo3GU8DZwA+o1G9v1odGxGJg8IbO70wp1cbps2rAtJTSY+Px/pIkSWAJUzM0FvG4msqUzwDvpzE69oqsmbQyrqFRvs6hUn8qw+fPTSntmOFzJUmSxoUlTM1Tqc+msXjHSVSmTKNRxvYH1s4ZS0O6Dfgp8FMq9btzh1laROwMHAusATwGfDClNCMirgCuB14LrE5jSuwXaUyJPS+l9OXi9b8CNgcmA99LKZ0yxGd8APg0MAn4C3BoSmnx+H4zSZLUCSxhyqNSnw5MpzLlMOANwL7APsAGWXN1tr8D5wI/KfaDaxWrRsQNxe37aBT3E4B9UkozI+I9wDeAg4vnLEgpTYuIw4ELgJ2Bx4F7IuK4lNIs4OCU0uMRsSpwTUT8vDgOQERsS2P67KtTSgsj4kQao7jnjP/XlSRJE50lTHlV6guBS4FLqUz5BPAaGoXsX4FNc0brEDNoFJWfAP9HpZ4y5xnKc6YjRsR2wHbA5REBjf3pZgx6/oXF9c3ALSmlGcXr7qUx+jUL+HREvKt43uY0tliYNeg93kijvF1TfMaqwKNj+q0kSVLHsoSpdVTqi4E/An+kMuVwYFcaZWwfYOuc0SaQBcCf+Gfxrd+UOc9IBI1ytfsyHp9fXA8Mur3kfk9E7AG8Cdg9pTSnmMI4eYjPODul9MWxCi1JkrSEJUytqTEic3Vx+U8qUzYF9gT2KK5fmC9c27kL+A2N4nUFlfozmfOM1h3A1IjYPaV0VUT0AlunlG4Z5uunAE8UBewlwG5DPOd3wAXF9MVHI2JdYM2U0v1j8xUkSVIns4SpPVTqDwE/Ki5QmbIFjTK2pJi9IFe0FjNAY1GNv9IosJcXG2lPGCmlBRGxH3B8REyh8XPsu8BwS9hvgI9HxG00Ct3VQ3zGrRHxZeCyiOgCFgKfBCxhkiRp1Cxhak+V+gM0lk0/u3F/ypbALsCOwA7FZZNM6ZrpARqFa8nlWir1p/NGGlsppTWGOHYD8Lohju8x6PYVwBVDPQa8dRmfVRp0+zzgvJXNK0mStCKWME0MjdGe+xj8S3NlylSeLWQ7Ftfb0p7/3s+kMa1wyeVG4K9U6i4WIUmS1Gba8ZdRaXgq9ZnAb4tLcWxKL7AZjemLWxSXFwy63hxYrdlRgTk09rt6iEbJuptnC9fdVOr1DJkkSZI0Dixh6iyNJfGXjJot4zlT1qdR1NYadFlzGbeHKmwDNFYhXHJZCDxDYwn0x4rL4NuPUanPG/V3kyRJUluwhElLq9SXlCNJkiRpzHXlDiBJkiRJncQSJkmSJElNZAmTJEmSpCayhEmSJElSE1nCJEmSJKmJLGGSJEmS1ESWMEmSJElqIkuYJEmSJDWRJUySJEmSmsgSJkmSJElNZAmTJEmSpCayhEmSJElSE1nCJEmSJKmJLGGSJEmS1ESWMEmSJElqIkuYJEmSJDWRJUySJEmSmsgSJkmSJElNZAmTJEmSpCayhEmSJElSE1nCJEmSJKmJLGGSJEmS1ESWMEmSJElqIkuYJEmSJDWRJUySJEmSmsgSJkmSJElNZAmTJEmSpCayhEmSJElSE1nCJEmSJKmJLGGSJEmS1ESWMEmSJElqIkuYJEmSJDWRJUySJEmSmsgSJkmSJElNZAmTJGkUImLviLgjIu6OiHLuPJKk1mcJkyRphCKiG/gB8FbgpcABEfHSvKkkSa3OEiZJ0sjtAtydUro3pbQAOBfYJ3MmSVKL68kdQJKkNrYp8PdB9x8Edl36SRFxCHBIcffpiLijCdn0fOsDj+UO0S7i6INyR9DY8N/7lfHVGMt3e8GyHrCESZI0zlJKpwCn5M7R6SJiekppWu4cUjP5731rcjqiJEkj9xCw+aD7mxXHJElaJkuYJEkjdw2wVURsGRGTgPcCF2bOJElqcU5HlCRphFJKiyLiMOBSoBs4I6V0S+ZYWjanhKoT+e99C4qUUu4MkiRJktQxnI4oSZIkSU1kCZMkSZKkJrKESZKklhcRiyPihkGX0jh+Vi0i1h+v95dGKyJSRPxo0P2eiJgZERet4HV7rOg5ag4X5pAkSe1gbkppx9whpBbxDLBdRKyaUpoLvBm3x2grjoRJkqS2FBE7R8QfI+LaiLg0IjYujl8REcdFxPSIuC0iXhkRv4iIuyLi64Ne/6vitbdExCHL+IwPRMRfi9G3H0ZEd7O+n7QCFwN9xe0DgJ8ueSAidomIqyLi+oi4MiK2WfrFEbF6RJxR/Pt9fUTs06TcwhImSZLaw6qDpiL+MiJ6gROA/VJKOwNnAN8Y9PwFKaVpwMnABcAnge2AD0bEesVzDi5eOw349KDjAETEtsB7gFcXo3CLgfeP31eUVsq5wHsjYjKwPfCXQY/dDrw2pfQK4CvAN4d4/ZeA36eUdgH2BI6KiNXHObMKTkeUJEnt4DnTESNiOxql6vKIgMY+bTMGPX/Jptk3A7eklGYUr7sX2ByYRaN4vat43ubAVsXxJd4I7AxcU3zGqsCjY/qtpBFKKd1UnBt5AI1RscGmAGdHxFZAAnqHeIu9gHdExL8X9ycDWwC3jU9iDWYJkyRJ7SholKvdl/H4/OJ6YNDtJfd7ImIP4E3A7imlORFxBY1fQpf+jLNTSl8cq9DSGLsQOBrYAxg8knsk8IeU0ruKonbFEK8NYN+U0h3jnFFDcDqiJElqR3cAUyNid4CI6I2Il63E66cATxQF7CXAbkM853fAfhGxQfEZ60bEC0YbXBpDZwBfSyndvNTxKTy7UMcHl/HaS4FPRTHMGxGvGJeEGpIlTJIktZ2U0gJgP+DbEXEjcAPwqpV4i9/QGBG7DegHrh7iM24FvgxcFhE3AZcDG48yujRmUkoPppSOH+Kh7wDfiojrWfbMtyNpTFO8KSJuKe6rSSKllDuDJEmSJHUMR8IkSZIkqYksYZIkSZLURJYwSZIkSWoiS5gkSZIkNZElTJIkSZKayBImSZIkSU1kCZMkSZKkJrKESZIkaVQiYvWIqEbEjRHxt4h4T0TsHBF/jIhrI+LSiNg4IqZExB0RsU3xup9GxEdz55eabVk7aEuSJEnDtTfwcEqpDyAipgCXAPuklGZGxHuAb6SUDo6Iw4CzIuJ7wDoppVPzxZbyiJRS7gySJElqYxGxNXAZcB5wEfAEcCVwb/GUbmBGSmmv4vmnAPsCO6SUHmx+YikvR8IkSZI0KimlOyNiJ+BtwNeB3wO3pJR2X/q5EdEFbAvMAdYBLGHqOJ4TJkmSpFGJiE2AOSmlHwFHAbsCUyNi9+Lx3oh4WfH0zwK3Ae8DzoyI3hyZpZwcCZMkSdJovRw4KiIGgIXAJ4BFwPHF+WE9wHcjYhHwEWCXlNJTEfG/wJeBr2bKLWXhOWGSJEmS1EROR5QkSZKkJrKESZIkSVITWcIkSZIkqYksYZIkSZLURJYwSZIkSWoiS5gkSZIkNZElTJIkSZKa6P8DBukjtBw95VgAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 1080x504 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,7))\n",
+    "plt.subplot(1,2,1)\n",
+    "df['sex'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.subplot(1,2,2)\n",
+    "sns.countplot(x='sex',data=df)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['sex'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There is more than double the number of men working than the no. of women."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:15.542072Z",
+     "iopub.status.busy": "2021-07-05T16:35:15.541542Z",
+     "iopub.status.idle": "2021-07-05T16:35:16.018810Z",
+     "shell.execute_reply": "2021-07-05T16:35:16.017828Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:15.542025Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "United-States                 29170\n",
+       "Mexico                          643\n",
+       "?                               583\n",
+       "Philippines                     198\n",
+       "Germany                         137\n",
+       "Canada                          121\n",
+       "Puerto-Rico                     114\n",
+       "El-Salvador                     106\n",
+       "India                           100\n",
+       "Cuba                             95\n",
+       "England                          90\n",
+       "Jamaica                          81\n",
+       "South                            80\n",
+       "China                            75\n",
+       "Italy                            73\n",
+       "Dominican-Republic               70\n",
+       "Vietnam                          67\n",
+       "Guatemala                        64\n",
+       "Japan                            62\n",
+       "Poland                           60\n",
+       "Columbia                         59\n",
+       "Taiwan                           51\n",
+       "Haiti                            44\n",
+       "Iran                             43\n",
+       "Portugal                         37\n",
+       "Nicaragua                        34\n",
+       "Peru                             31\n",
+       "Greece                           29\n",
+       "France                           29\n",
+       "Ecuador                          28\n",
+       "Ireland                          24\n",
+       "Hong                             20\n",
+       "Cambodia                         19\n",
+       "Trinadad&Tobago                  19\n",
+       "Laos                             18\n",
+       "Thailand                         18\n",
+       "Yugoslavia                       16\n",
+       "Outlying-US(Guam-USVI-etc)       14\n",
+       "Honduras                         13\n",
+       "Hungary                          13\n",
+       "Scotland                         12\n",
+       "Holand-Netherlands                1\n",
+       "Name: native.country, dtype: int64"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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GbKojSZIkSVoJWwwOkzw+yeeAY4CrAY82U6kkSZIkrS9bXOcQ2AU4pKpOmXFdJEmSJEkrZLF1DrevqvOBl3bbO4w/XlU/m3HdJEmSJEnLZLGew3fR1jg8ESggY48VcL0Z1kuSJEmStIwWW+fw3t3P3ZavOpIkSZKklbDYsNK9FnthVZ00fHUkSZIkSSthsWGlL+t+bgfsA3yVNrR0T2ADcJvZVk2SJEmStFw2u5RFVe1XVfsBPwL2qqp9qmpv4BbAD5argpIkSZKk2dviOofAjarqtNFGVX0N+NPZVUmSJEmStNyWEhyemuSNSe7U3d4AnLqlFyU5LMk5Sb42tu/QJD9Ickp3u9fYY/+Q5KwkZya5+9j+e3T7zkryrLH9uyX5Srf/PUm2XfrbliRJkiSNW0pweCBwOnBwd/t6t29L3gLcY4H9r6iqm3e3IwGS7AH8NfBn3Wv+K8nWSbYGXgPcE9gDeGj3XIB/68q6AfBz4KAl1EmSJEmStIDFEtIAUFW/A17R3Zasqo5LsusSn74/cHhVXQh8J8lZwK26x86qqm8DJDkc2D/JN4A7A3/TPeetwKHAayepoyRJkiSp2WLPYZLbJTk6yf8m+fboNsXvfGKSU7thp1ft9l0b+P7Yc87u9m1u/9WAX1TVRfP2b+49PCbJhiQbzj333CmqLkmSJEnr01KGlb4JeDlwe+CWY7c+XgtcH7g5LQvqyxZ99kCq6vVdttV9dtxxx+X4lZIkSZK0pmxxWCnwy6r6xBC/rKp+MrrfJbb5WLf5A2CXsafuzMblMhbafx5wlSTbdL2H48+XJEmSJE1oKT2Hn03y0iS3SbLX6NbnlyW55tjm/YFRJtMjgL9OctkkuwG7A8cDJwC7d5lJt6UlrTmiqgr4LPCg7vUHAB/pUydJkiRJ0tJ6Dm/d/dxnbF/REsJsVpJ3A3cCrp7kbOB5wJ2S3Lx7/XeBxwJU1elJ3kvLhHoR8ISqurgr54nAUcDWwGFVdXr3K54JHJ7kRcDJtOGvkiRJkqQelpKtdL8+BVfVQxfYvdkArqr+GfjnBfYfCRy5wP5vszGjqSRJkiRpCpsNDpM8dbEXVtXLh6+OJEmSJGklLNZzeKVlq4UkSZIkaUVtNjisqucvZ0UkSZIkSStnKdlKJUmSJEnrnMGhJEmSJGnzwWGSg7uft1u+6kiSJEmSVsJiPYcHdj9fvRwVkSRJkiStnMWylX4jyTeBayU5dWx/gKqqPWdbNUmSJEnSclksW+lDk/wJcBRw3+WrkiRJkiRpuS3Wc0hV/Ri4WZJtgRt2u8+sqj/MvGaSJEmSpGWzaHAIkOSOwNuA79KGlO6S5ICqOm7GdZMkSZIkLZMtBofAy4G7VdWZAEluCLwb2HuWFZMkSZIkLZ+lrHN4mVFgCFBV/wtcZnZVkiRJkiQtt6X0HG5I8kbgHd32w4ANs6uSJEmSJGm5LSU4/HvgCcCTu+3PA/81sxpJkiRJkpbdFoPDqrqQNu/w5bOvjiRJkiRpJSxlzqEkSZIkaZ0zOJQkSZIkGRxKkiRJknoGh0keM3RFJEmSJEkrp2/PYQathSRJkiRpRfUKDqvqv4euiCRJkiRp5WwxOEyyc5IPJTk3yTlJPpBk5+WonCRJkiRpeSyl5/DNwBHANYFrAR/t9kmSJEmS1omlBIc7VtWbq+qi7vYWYMcZ10uSJEmStIyWEhyel+ThSbbubg8Hzpt1xSRJkiRJy2cpweGjgAcDPwZ+BDwIOHCWlZIkSZIkLa9ttvSEqvoecN9lqIskSZIkaYVsNjhM8txFXldV9cIZ1EeSJEmStAIW6zn89QL7rgAcBFwNMDiUJEmSpHVis8FhVb1sdD/JlYCDaXMNDwdetrnXSZIkSZLWnkXnHCbZAXgq8DDgrcBeVfXz5aiYJEmSJGn5LDbn8KXAA4DXAzetql8tW60kSZIkSctqsaUsngZcC/hH4IdJzu9uFyQ5f3mqJ0mSJElaDovNOVzKGoiSJEmSpHXAAFCSJEmSZHAoSZIkSTI4lCRJkiRhcChJkiRJwuBQkiRJkoTBoSRJkiQJg0NJkiRJEgaHkiRJkiQMDiVJkiRJGBxKkiRJkjA4lCRJkiRhcChJkiRJwuBQkiRJkoTBoSRJkiQJg0NJkiRJEgaHkiRJkiQMDiVJkiRJGBxKkiRJkjA4lCRJkiRhcChJkiRJwuBQkiRJkoTBoSRJkiQJg0NJkiRJEgaHkiRJkiQMDiVJkiRJGBxKkiRJkjA4lCRJkiQxw+AwyWFJzknytbF9OyQ5Osk3u59X7fYnyX8kOSvJqUn2GnvNAd3zv5nkgLH9eyc5rXvNfyTJrN6LJEmSJK13s+w5fAtwj3n7ngUcU1W7A8d02wD3BHbvbo8BXgstmASeB9wauBXwvFFA2T3n0WOvm/+7JEmSJElLNLPgsKqOA342b/f+wFu7+28F7je2/23VfBm4SpJrAncHjq6qn1XVz4GjgXt0j21fVV+uqgLeNlaWJEmSJGlCyz3ncKeq+lF3/8fATt39awPfH3ve2d2+xfafvcD+BSV5TJINSTace+65070DSZIkSVqHViwhTdfjV8v0u15fVftU1T477rjjcvxKSZIkSVpTljs4/Ek3JJTu5znd/h8Au4w9b+du32L7d15gvyRJkiSph+UODo8ARhlHDwA+Mrb/kV3W0n2BX3bDT48C7pbkql0imrsBR3WPnZ9k3y5L6SPHypIkSZIkTWibWRWc5N3AnYCrJzmblnX0X4H3JjkI+B7w4O7pRwL3As4CfgMcCFBVP0vyQuCE7nkvqKpRkpvH0zKiXg74RHeTJEmSJPUws+Cwqh66mYfussBzC3jCZso5DDhsgf0bgJtMU0dJkiRJUrNiCWkkSZIkSauHwaEkSZIkyeBQkiRJkmRwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJIkVCg6TfDfJaUlOSbKh27dDkqOTfLP7edVuf5L8R5KzkpyaZK+xcg7onv/NJAesxHuRJEmSpPVgJXsO96uqm1fVPt32s4Bjqmp34JhuG+CewO7d7THAa6EFk8DzgFsDtwKeNwooJUmSJEmTWU3DSvcH3trdfytwv7H9b6vmy8BVklwTuDtwdFX9rKp+DhwN3GOZ6yxJkiRJ68JKBYcFfCrJiUke0+3bqap+1N3/MbBTd//awPfHXnt2t29z+zeR5DFJNiTZcO655w71HiRJkiRp3dhmhX7v7avqB0muARyd5IzxB6uqktRQv6yqXg+8HmCfffYZrFxJkiRJWi9WpOewqn7Q/TwH+BBtzuBPuuGidD/P6Z7+A2CXsZfv3O3b3H5JkiRJ0oSWPThMcoUkVxrdB+4GfA04AhhlHD0A+Eh3/wjgkV3W0n2BX3bDT48C7pbkql0imrt1+yRJkiRJE1qJYaU7AR9KMvr976qqTyY5AXhvkoOA7wEP7p5/JHAv4CzgN8CBAFX1syQvBE7onveCqvrZ8r0NSZIkSVo/lj04rKpvAzdbYP95wF0W2F/AEzZT1mHAYUPXUZIkSZIubVbTUhaSJEmSpBVicChJkiRJMjiUJEmSJBkcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCdhmpSughf3ktS/u/dqd/v7ZA9ZEkiRJ0qWBweFAzn3d66Z6/Y6Pe9xANZEkSZKkyTmsVJIkSZJkcChJkiRJMjiUJEmSJGFwKEmSJEliHQSHSe6R5MwkZyV51krXR5IkSZLWojWdrTTJ1sBrgLsCZwMnJDmiqr6+sjWTNu/Dh91zqtff71GfGKgm0nTu9aH+S+4AHHl/l92RJGk1WdPBIXAr4Kyq+jZAksOB/QGDwxn65n/uP9Xrd3/iR+Zsn/S6+0xV3l6P++hUr9+So950r6lef/eDjhyoJsvjTW+721SvP+iRn5qz/Z/vvPtU5T3xYUdN9fot+Yf33WOq1//LX31yoJosj3t9uP8AiyPv968D1mRTf/nBV071+o8/4JBB6rFW3fv975vq9R970F8NVBMBPPgDZ0z1+vc+8MYD1WRh//6hH0/1+v93/z8ZqCZrz5ffcs5Ur9/3b68xUE2k4aWqVroOvSV5EHCPqvq7bvsRwK2r6onznvcY4DHd5o2AM5dQ/NWBnw5Y3dVc3mqum+VZnuWt3fJWc90sz/Isb+2Wt5rrZnmWt1bKu25V7Th/51rvOVySqno98PpJXpNkQ1XtM1QdVnN5q7lulmd5lrd2y1vNdbM8y7O8tVveaq6b5VneWi9vrSek+QGwy9j2zt0+SZIkSdIE1npweAKwe5LdkmwL/DVwxArXSZIkSZLWnDU9rLSqLkryROAoYGvgsKo6faDiJxqGusbLW811szzLs7y1W95qrpvlWZ7lrd3yVnPdLM/y1nR5azohjSRJkiRpGGt9WKkkSZIkaQAGh5IkSZIkg0NJkiRJ0hpPSLMaJdkBeBzwO+CNVXX+CldJQJKtgZ0Y+8xX1f+tXI1mq8vee8Nu88yq+sNK1keSpPUsyU2APYDtRvuq6m0rVyOtNkn2WuzxqjppueqyGBPSjElyO+CUqvp1kocDewGvqqrvTVDGZ4H/AS4L3AO4T1V9e8A67gTcsts8vqrOGars9SrJk4DnAT8B/tjtrqrac+VqNdcQn72xsu4EvBX4LhDaWqAHVNVxU9bxGsw96a2a4DrJ9YGzq+rC7v3vCbytqn7Rs7wrA4cCd+h2HQu8oKp+OWE5T13s8ap6eZ/6rWbd9+0dVfXzgcq7aVWdNlBZt6P9X69LaygK7VhwvSnKfMACu38JnNbn+DzksWAtGPqCOskjF9o/ZZlXBXZnbh17HU+TXAH4bVX9sdveCtiuqn4zYTl3rqrPbObzR1V9sEfdtgaeXFWvmPS1i5R5H+Djo/c7UJmDnouGKC/J84A70T7LRwL3BL5QVQ/qWaetaeewh/V5/WbKvDzwNOA6VfXoJLsDN6qqj/Uoa3fgX9j0uzvxsXTo8+Sszrvj390kNwRuDHxiksb3LkaA9jfbB/gq7Ty0J7Chqm7Ts2770K5XrgX8FvgacHTf87A9h3O9FrhZkpvRvkBvBN4G3HGCMq5WVc8GSPIp4Ngkv+jK+7uqenDfyiV5MPBS4HO0D9Orkzy9qt7fo6wb0t7vTlV1kyR7Avetqhf1KGsf4DlsesHVO/hKsiPwTDY98Ny5R3EH0w6A5/Wtz3wD1w+G+eyNvAy4W1Wd2dX1hsC7gb37VCzJfbsyrwWcQ/s/fwP4sz7ldWU+APg34Bq0z8voM7N9zyI/AOyT5Aa0FM4fAd4F3KtneYfRDq6j7+sjgDcDC16ILeJK3c8b0Rp1Ruuw3gc4vmfdRp+/RwO7Mrc3/FETlnMasNkWwp7f4Z2AE5KcRPs7HlXTtUL+V5LLAm8B3jlpgD7Pm4CnACcCF09RzriDgNsAo5P+nbryd0vygqp6+4TlDXksGOxYleSjLP5ZuW+Pui14QU17v33dcuz+dsBdgJP6lpnk72jnkJ2BU4B9aQ3AfY/1xwB/Afyq27488CngthOWc0fgM7RjyXwFTBwcVtXFSR4KDBYcAg8BXpnkA7Tlxs7oW9DQ56KBy3sQcDPg5Ko6sGvIf0efesEl/4vrJtm2qn7ft5x53kw7No0CkB8A7wMmDg67sp5H+6zsBxxI/6lqQ58nr7Tlp/RyHHCHrrHoU7S11h8CLDmAr6r9AJJ8ENhr1PDZNZIdOmmFkhwIPAn4Du1/eybtuHd74JlJvgb808QNHlXlrbsBJ3U/nwscNL5vgjK+COw6th3g2rQTwDWnrN9XgWuMbe8IfLVnWccCt6IdyEb7vtazrDOB+wK70Q6u1wWuO+V7/RTtousbtJPgYcC/9Szrs8A2A39WBqvfUJ+9sbJOXcq+CT93Vxt9VmgngjdN+fc7C/jTAf8fo7/f04EndfdPnqK8U5ayb4LyjgOuNLZ9JeC4Kcr7Ei24fjDwwNGtRzmj7+tLuttNu9u/Av86Rf0C3B04vPtfvxi4/hTljVqpz6IF/XftWc5XhvrMjZV5FK2RbbS9U7dvhz7H1CGPBd1rBzlWda+9I/Aq4D20C7f7dP+PV/Ss22m0C8qvjv3tjh74/3MV4JNTvP402sXWKd32jYEPTlHeKUvZN0F5uy1l3wTlvQL4T1ovxF6j25T/g+2BxwJfpgXWjxk/Hk5QzqDnoiHLo43kgnaBvn13DDxjyr/b22gByD8BTx3dpihvQ/fz5PG/Qc+yTux+njZ/3xT1G/Q8OfRt7Nj8JOAZ3f1TepZ1+lL2LaGcJwCXW+TxmwN3mbRcew7nuiDJP9B6Ce7QDfe4zIRlPArYdrRR7b/zg25zomEjC9iq5g5TOo/+LTWXr6rjk4zvu6hnWedW1RFbftpErlZVb0pycFUdS+uBPaFnWd8GPpfk48CFo5013ZC+IesHw3z2RjYkeSMbWy0fBmyYom5/qKrzkmyVZKuq+mySV05RHsBPquobU5Yx7g9di/cBbGxJ7/v3A/htkttX1RfgkqF+v52ivJ2A8dbf33f7+rp8VT1zitcDUN1QxSR3rapbjD30rK7n71k9y60kPwZ+TDuuXBV4f5Kjq+oZPcr7ZpJ/pH2O/wO4RdrB69k12fC5zyZ5Ka1XZfxYMM08j12q6idj2+d0+36WpM9c39Gx4OHAn095LICBjlXda0nysqraZ+yhjybpe3wZDdG6KMn2dH+7nmVtzq9pDZd9/a6qfpeEJJetqjOS3Gia+iTZa/SZS7I30x1bPkAL4Ma9n54jRWgXkwAvGNtX9O8pparOT/J+4HLAIcD9gacn+Y+qevUERQ19LhqyvA1JrgK8gRYg/ooWCE/jW91tK4bpDft9ksvRjQDopmNcuPhLNuvC7tj0zSRPpF3nXnHK+g16nkyyHa1h7M+YO2piohE2c4vMbWjXVAd1+7buWdapC1ynnTppIVX1mi08fsrkVXNY6XwPAf4GeFRV/TjJdWjDOJesuqF8M/LJJEfRhghCq+8nepb10+7AMDpIPAj4Uc+yntd9yI9h7gXXxMNaxowuqn6U5C+BH9Ja4vv4v+62LWOB+5SGrB8M8Nkb8/e01qQnd9ufB/5rirr9IskVaa1670xyDu2Ca2Jj82M2JHkP8GGG+cwcSEsE9c9V9Z0kuwGTDucb9/fAW9PmHgL8HPjbKcp7G3B8kg912/ejzQvt62NJ7lVVR05RxrgkuV1VfbHbuC09G56SHAw8EvgpbUjk06vqD6MLCWCi4LAb8n4g8JfA0bR53CcluRbt4muSz8ytu5/jwc1UF760hqeP0YZnQevF/Vza/JRf9ChvdCw4aIBjAQx/rLpCkutVN5e++65doWdZg19Qzxv+uhVtyOp7pyjy7K6OHwaOTvJzYJr5n4cA70vyQ1rv0p/Q/ucTSXJj2kXvlTN33uH2jF0IT6q6YW9DSbI/7dh5A9px8FZVdU7a/LevA5MEh4Odi4Yur6oe3919XZJPAttX1cQX+/PKfD5AV0eq6leLv2KLngd8EtglyTuB29H/vHYwbUTck4EX0o6hB0xZv6HPk28HzqCNYnkBLQCbplH6EOAfgA9V1elJrsfG6QSTOpB2nXFwt30cbUpBL0neChxcXZ6Fbujry/oGwiakmSfJdYHdq+rT3cFr66q6YKXrNdKdBG7fbX6+qj602PMXKed6tLlZt6Vd+H4HeHhVfbdHWe+gDbU5nbkJX/q2zpDk3rSgZhfayWN74Pkz6KHsZRb1W62fve4i93e0C5mHAVemzf2aeA5nkjcv8vBUn5lZ6HozqAGyDnc9BKPv7nFVdfIUZV1AuyC/kHbxP9Wcza5uh9H+t6EdEx7Vp0ctyfNpc4s2uYBO8qeT9hgnOZY2V/B9VfXbeY89oiaf0zeorgfzgbQLLWhTCz5Qq+TkOvSxKsk9aOeOb9M+K9cFHltVR01Zz10Z4II6yR3HNi8CvldVZ09T5ryyr0wbptp7HliSy9DmV0HPbNJd0HU/2pSO8f/lBcDhVfWlnnW7Mi2I+PNuV69kXGPlvYV2PNgkgU+Su1TVMROUNdi5aOjyktwf+Mzo79Q1KNypqj7cp25dGTehBTijxpyfAo+sqtOnKPNqtHmzAb5cVT/tW9YsDHyePLmqbpHk1Kras/vefb6q9p2yjkMF64MZvdct7Vtyeavk/LUqJHk0bSz8DlV1/bRsTK+rqruscNWAS1pof1RVv+u2L0eb6/LdKcq8Am24au8gJMmZVTXNMJuZSkvI8Aw2HVowTW/BoIb87GXhJCO/pA3Je1HfE+mQxnupFtu3hHJmkVCFJC8GXjKvFe5pVfWPfcrrylj1y6mMekr7XgiOlbNq32vXezb/WPCCzb9ieSXZlxbE/SltpMPWwK+q6sqLvnAZpSUIunG3eUZVTTQ0LcmNu+GZC6Z17zvMt/vcfXrI3q+u53YTk36eM4Psol25t6mqaYcvjpf3AVoyrlGPzSOAm1XVpMm4ZvL/WK2SnFJVN5+3r/fFeff6LwHPqarPdtt3Al5cVZMmLxqVN3UAm+SVVXVINpOgqnokpppX/mDnjiTHV9WtkhwHPJ42zeH46pmdOslNab2bO9CC63PpGaxn08zZQL9sr115X6X9L3/ebe8AHFtVN+1TnsNK53oCLUnLV+CSeS7XWNkqzfE+5mY0u7jbd8uFn755A1/8finJHlX19R6v3Vz9BsnG2HknLYHCvWlDDw+gfan71OsZVfWSJK9m4QPjkxd42VIM+dn7BO2z8a5u+69pwz9+TMv4uFB2u010vVOLBV59M4tCu/idf2G40L4tuXf38wndz1Ev0sNZpO5LcM/qsg4DVNXPk9wL6BUcZu5yKhfT9fTR0lf3kmHT61+W1vu1K7BNurnIfYKmtPknhzJv6RgmfK+LBP69syEneR3tu7Afbcjrg5gia2xX5tCZd/+T9p19H2346yPZuGZpn/pdj5ZE5ja0/8f/AE+p6ZZY2puNx+abJaEmWyriabTj+8sWeKz3MN9qGR7/mOTK0zZwjPl4V6fQvmu70ZKwTZrR8o4MmF10dC4C/iZtvvXcAvufi65fVQ8c235+klP6FDTU/yPJF6rq9mPnpIz/nPS7tsi5bZrv7kLD8Ke9xr7CKDAEqKrRcPW+nldjo82q6hdpGYM/PEEZo3Psv09RjwXN4Dz5+u48+U+03vUr0hJ99fXftIRA48H6G5g80zAMnzn7ZcD/JBlNb/grWiK4XgwO57qwqn4/ujBKsg3TXWAObZvxoSxdXfvOoRvy4ndf4JQk36ENc5t6KQvaUgSfBz7N9F+cIZPHjIbETZPgZSFDfvb+oqrGg6zTkpxUVXulrZu2JFV1pa4uL6TNR307G4ffXLNPxdImc98W2DFz1yLanh4Tu2vzCVWemSkSqgBbpyWfuLAr/3K0tUv7OpgBl1PJ8On1P0LrXT6R/gkKRg5hmPd67y0/ZWK37YYXnVpVz0/yMvrP2x55CW0e5GAJlqrqrCRbV9XFwJuTnEyb69LHu4DX0JKAQAs8383G+ZcTSfJ24Pq0z93o2FxMsFREVT26+zmLHqVf0Y55RzM2f6xvsDS/5b3r7Xz8Zp6+WDnP634e2KceC5jVuWjoZFxT/z+q6vbdz0GWKBiqnHk2JHk57bsGrcHyxCnL/HaSf2Juo+c0jTpTB7BVNXpPV6OtXznt+WLcoOfJqnpjd/dYoPdatmOGDNZ/WVXTnnsuUVVvS0sMNroGeMA0HTYGh3Mdm+TZwOWS3JV2AvjoCtdp3LlJ7lvdXJG0OQd9x4sPefF7j56vW8wg2Rg7gyVkqKqPdj+nmSS9kCE/e1snuVVVHQ+Q5JZsDLz6ZKS9b1XdbGz7td0Qhj4tcNvSWu+2YW72tfNpvTh9JQMlVOm8EzgmG+dIHsh0E+O/Twu+hnIwbcTAl6tqv7TkFL1bCYGdq2qo7/Eg77Vms+j76CL3N2kJbc6jZ0PHmKEz7/6ma/Q7JclLaA0z03yWL19z52W+I8nTpyhvH2CPqv5zUjY3tHKk7xDLzgfpscbfUlVLhjRxYJ2BF+ae4bloPBlXgJ8xXTKuQf8fXXB+e1qDxBdqijlpY2Veg7kjMPoMY3wSrYfqPd320Wwc0dLXo4Dns/Hv9/luX19DBrD3AV7RDdl8D20ebt+M9yODnic38537JW3JjVN6FDlksD5o5uwkb6+qR9CSPM3fN3l5Uxzf1520bHoHAXejHRSPqqo3rGytNkrLLvpO2oKtoX2RHllVZ/Uo65m0L/f4xe8R3TCVvvUb4gA7KutFwJdqgGyMGTAhw+bG2Y/0HW+/0GcPeGOfC7AuGDyMFoSFFnj9HS1h0F9W1USZ+9LmPbyGtmZdAQ8FnlA95z10ZV53yIv/DJhQZazMe9IW0Ia29lrvhBtJ3kRLQDHIcipJTqiqW3bDvW5dVRcmOb2q+i4G/Xrg1dUtyDuNGbzXhebg/brP0K/uxP5q2v/1NbTP8xuqqvdQoySvomWc/DADZN5NS0z1E9p7fQrtM/1fkx7n0+acADyT9n0YfX8fAly1qnr1RHbDlp5cVX2zWzPW6HIN2kiCz3Tb+9GO+1P1GneNndepAbKHz7vA3Io29P1qVXX3Cct53mKPV5eZclJpUzCeScvKOtic+gyYjGsoSZ5LGy43+m7dj5ao6kU9y7svbTjetWjLqFwX+Ebf4+hq1/Vy/RPwF92uo2l5CPpmH78McE/aMeX2tPPk301Rv6HPHe+iNWaNGtrvTVsuYlfa52ai691uiOrzGUsKCRxa3Ty/CctaKMtp9f3ejkaHjW1vTVuDco9e5RkcbtQNO3zVlvattAyUKSkt69wlB4m+F7+zOMBmwGyMSbarLonPtLIxE94DaBeEozVqHkrrQXjKEL9nCBkuuciutDlLt6NdXH4ROKSmS4T0WRaeszntBc0g73lom7swnOKC8EO0Bp1DaMNIfg5cpqru1bO8r9NSzU89NHwG73UDC8zB6xvcjJV7WWC7Ab4fC2XgreoxP7o7ob+tqh42TZ26sr7DxnlZC9Wvb+KDz9LWwjueuRdwEzeMJfkUcMAo0ExyTeAtkwZe88q8D20+1LZVtVuSm9OybfZtuBv/PF8EfJeWjXaQc8q0ur/he4D/x9ic+klH3gzdszlW7u7Av7Bp8Drx5y/JmbTkOONJ+U6pngnxuhEwd6YlzblFkv1oWdsP2sJLx8sYPEHLrBqhZ6ELEO9BOx/9eVVdfYqyhj53HAfca3St3F07f5xW3xP7Bk6rSdqauM+mrSH6GzYe738PvL53I6DB4UbzI+9u38k1RbapISR5eFW9Y3MH7ykO2oMsnTDEAXaWkpxFa4n/fHf7wgAXhBtq7kLQC+6boLz5matGF+d9L+BWe0bG8QWat6MlQ7moeiyQ3pU3J6HKaP+k7zmbJj645CGmSzIyMxkgvX53LNjEkL27fY2+V+nSkXf7eh2X0xZFfjxjw9KA166WC31on0Hgzn3/l7OWuUtFXKLafO5Jy/pGVf3p2PZWwOnj+3qUeSLtfPS50Wckydeq6iZ9yxxSNiYI2pf2GZwqQVCSE6tq73nfjxOqaqJEdWMX5jeiDVkfjay5Dy3D45Lnq88r9wu0JCOv6Mo6kJYhfeLe+q5h4v61MZHeVYAPTtHbMjq2fBW4RVX9MclXa+40ii2VsXdVnTjw92ImjdBJbkhrRNiVuefJif9+3ciahwB3Aj5HW0v0UzX90NLBJDkDuGl1S8V01wlfraob9zmHZODM90NepyX5l2kbTMc55xBIy/T1N8BuScaHGl6JNt5+pY0mvA42iTpjSyfQkgtcG3gdG4fRTeIPVXVekq2SbFVVn03yyp71GjzFeVXdIC0d+R1oC2m/Jskval7a6QkNuRA0DJi5KgNnZOwuqA9i04NY77kPtXFS+8gXk0yTNXKQhCo1cOKDkSFPKl3v0ulVdeOujIkvPuarjYl95gwN72PoEyjDzsF7G20duNHC239Dmz/yVz3LI8nOXXmjdQ4/T1uMuO/aet+mfR+OYG4Cj76NgI9caH9Nll10/HVTf97GHJPkKFqCHGgXm5+essw/VNUvkzkdpn/c3JO3ZDO9OKOlgf67R8PCoAmCGGhOfW1ccP04YK9RQ3GSQ2m9LX1drqqOSZLuOHNoF8AvOTjMxuzgvwROT0tuU8BdmS7b8C+63qTjgHcmOYex79xSjM5lQ34vRmUledm8BuePdiMp+nof7TrvjUyf6O+RtB7rx9ZASWlmcO54J/CVJB/ptu8DvCtteG2fZC1DZr4fOnP2c9ISDu5WVS9MsgtwzepyT0zK4LD5Eu2C4+rMTa19AW188oqqqv/ufm7StZ7+2UqHXDph6gPsmKfSgtbBUpx3F2+3owWHN6PNvftCz/qNPAX4XJI5C0FPUd6QmauGzsj4duAM4O7AC2jZSqdKwJGN86GgXejvTev96mvIhCqb6Fqon1BV/9yziMFOKtXSw5+Z5Do10NqB2czQcCZP1w8DvtfOI2ifkSfSvne70FrU+7jJvKFEn00bUjuNN9Mu+EcB5sO7fXftWd63uttWDNMgON6DtB2tAfAkJsguOi4DzgGtqiemrb02WnD99TWWar+n05P8DS0x1+7Ak2nn+L6+DezI3AD2AtryIm+gfT4nMXSCoBelDad/Ghvn1E8zvWEn2pC0kd93+/q6sOsR/mbaMjc/oM2Hn8QoIDoRGP98fG6KegHsD/yO9vd6GO0c1LfnZrDhs2OGboS+qKpeO8XrL1FVmyyfMoBBzx1dkPQJNjbcPa6qRp+lPkP3h8x8P/R12mtojWB3Bl5IyxL8GnosdQdAVXlbIzfagXDXse1b0rrI+5T1le7nyd3PbYBTe5Z1BdoFwja0L/OTaV+iFf+bdfX7Iy0I3n/gci9LCzZvBlx2yrL+FXgpbS2yvUa3Kf+3X6Zd7F8WOGuKuo0+I6d2Py9Dy5I5zfv9Du2i6zvAN4FPAbeforzX04aPTPs/3aUr62O0JD5XoAVN5wKvmqLcE8f/ht39E6Yo7zjaBeoxtOFfR9ASSvUt76u01OSj//V+wJtWyXs9eCn7lljWO4B9x7ZvTZvjN81n5pSl7FstN+AqtCHIfV+/gTY/9eTuuH8g8C9TlLcTrUX/3sA1Bnh/lwf+GTihu72INre0b3mbfHZH+2g9+EstZ4fu9m+0JXZ2pTXCPGOav98MPh/P6Y4Hh3a3U4BnT1HeLWnB4M60RpMPjn8HV8ONFlCP/j879CzjC7SGl1O7/+uhtLmu09TrHsD/0a79jqXNd737FOUdShtWf80B3u++3ffrV7QGhIuB86d8v0OfO66z0G2K8r7c/TyKNgrtFsC3epY19HXaSd3Pk8f29YoPqsqew3FDtojOyL8An0zyH7RhoPeknZj7ODYDLZ1QczNdDZZWO205gl2ZOza+T2v3LWhzjP4mybNowcixVfWmKas47ULQ40ZDisaHkPTqKQU+1vV0vZTWQ1C0Fu6+RsOWfpHkJsCPaVkGe6uq3aZ5/QJuD/xtpl9r8220k/AHaCfmDbSLo5tW1Y+nqN9gy6l0/mmK1y5ksKHhDP9eD6DN0Rr3twvsW4q9gS8lGfW4Xgc4M8lp9F+b9bxuOM+oZ+mhtCUyesmMkjWN+TVTrvlVA63DmOTBtOPU52jf2VcneXpVvb9HWdvRehtuAJwG3KaGmf90xfFe+m6Kwqjna5J5oScyN0HQ+EiTYsK/39hQywVV/3Ud/znJJ9mYkfHAmmK5iKoa9az8iv7XKwCkZR5/IZvOze91jZbksbTsk7+jNSKPFl3v8/2YevjsfFX1ya5H8sbdrjNquiGcB3Q/x3uq+77f/2SBRGFT1A2GP3d8nI3fkcsBuwFn0m9EDCzcS39Iz7IWuk5746KvWNwfuiknBZcM0e0/nL6LLsXssuINKcmdaOmHf0qbQN3rgjXDLp3wAFpr6DW6sqZO3pHNLLTc94TXDXu9PW1o6cO7whZMwrES9ZuVDJCRMW3B9Q8Ae9Jafq8IPLeqXjdFmZehrac1Gk72Odr8nT9s9kWLlzdIQpXMS0aQ5GxaS2Pvg2xXzmDLqcxCkk/T0sL/C214/TnALavHciVDvddsnAt++668kSsBf6yqiedHb+5zMjLp52WszFfTev2LNoTxydVzyG+GT9Y0PmduK9qwt/dW1bN6lnccLcv1G2kNRT8C/rYmSOIxVtZXgbtW1Tnd9o60xGZ9ynoP7eLy87SG0+9W1SGTlrNAufeizdP6Fu3cthutMfVzwKOr6pXT/o6e9TpgbPP5tKQvl6gp1z/MQEtTDTlnMy253ANoKfqnvnhN8k1aI0Lf9aLHy/oS7Vj1ftrSLD8A/rV6ZlIdK/cmbDpUtW8j9GAyYKKwsTJnep5My2Xx+JpiuY0Fyjxk2mPAQNdpD6MNed+L1knzIOAfq+p9vcozONxoFh/2IaWt0fVg2py8PWnj5J9WVb0mi2egtaC6A/Z9asCFoJN8gykXWh4rawOty/5LdBlL+1wEzqJ+mUEm2qyNjIxvpA1PHV3APAK4eNqD9rQXNN3F6p3Y2Lr/2fHtqlrRBFXZNIvqJQ8xXQv6FWit52Hj3Jt3VlXvHrBpdUHXbrSAdTyQuYA27Kh3r9BQF77LJcnxVXWrCV9zA9qQzfERQhfR/sc/qqpv9azLdWmNB5dhinUYu7JOq6qbjm1vRRsKddNFXrbFspJsQ8uwuWBisx5lX5aNvTdnTnMszcAJgroyB7tOyabzj69D67Hqu4bqq9h0zub5tOPY9jXBIt1dr/pdpm2sGyvvk8ADquo3A5R1S9o87avQejevDLykqr48RZnPo51/9gCOpDV6fKGqHjRFmYMEm0M2Ei2n+cecAcr7v6q6zgTPX3S+fPVcH7cr+8a0oc0BjpnmmtxhpXMNmRVvFq4G3Kqqfgv8T3dgeyM9Mol1J4CX0obP7pbp1oL6yZCBYedrtBTOvRdaHnPPqpomIcZChqrf4JloGTgjYwZaJmKeW847iXymC8x6WeCCpm9ClSvThn+NpzocZcidePjN0EO/auAsqmPlDjY0PC1pwpPY9PMy0bGla8D5Hq1HbhADfk5mNqwvwyVreiXwD1V12rzyb9o9dp8+9RtrWPstrcdqGp/MptlKj+xZ1iWjDqrqoszNVjqt3WlLPGzH9FMIBk0Q1Bmylf+FtPlkc5ammqK829bcZTU+mm6pjSSnT1jWM4AjkxzLAIuk04byfinJV+aVN/F3d8jhs2MeRMtpcHJVHZhkJzYuazGxzQWb9PvsPYI29Wo8UdgDe9ZrVsfS8Ub3rWi9aj/sU9Ziv2bC5y923C3anNxequoM4Iwkj5n2mtzgcK4hs+INrtpCq5dLcqOqOrM7SffNiPc8WrbSz3Vln9Jd1PWxoRvS82HmHmAn/pCPDUG5EvD1tOUNei20POqVAx6x0IXCFCcUaEPvpqpf9/zNZqKdwtAZGQdZJmKei5Ncf9R7kbb21zSptQe5oKmqXaeow0KmSTs+czPqifwwbWmWjzLdEgKzqNuQF77j/9tNhvVNYXxu2kW0pE191ozdaX5gCFBVpyXZddLC0s3L3Nzj1WO+ZlU9vWtJH81vmyZb6c2SnN/dD20+/flM36s+5AU1VfWkeeVfBTi8T1kzMuT8Yxhuzia0REO/ogXVfTO1j/tv2hDQ05jiWAWQZB9aMp/RfEig3/dizG+rrb14UZLtaQ1au0xR3mDB5sCNRLM6T443pl5E60j5wMC/Y6KGmaoaquFgMY+jJdbrzeBwrvtV1atow6tGa/4cTL/EB4NLch/g3xmmt2+htaD6tj5uD/yGNn9xvKw+LSBH0IZCfX7e/jsweS/dLHrlRg4dsrAMuzDySUn2HQ1nSXJrpjv4zmKZiKfTgtbR+9uV6Vpbh76guUSSQ6vq0D6vrXnzftLmvlJVvxqgalObUU/k76rqP6YtZEZ1G+xzMv6/7eadDJKMq4ZL1nSVRR67XI/y7t2zHlvyJVrD0B9p2Q97qaqtB6vRXIP23izg17Th0xOZ13hy+XmBce9gmGGXpoKWvOMLSebM2eyGsk/6nblWVd1kirrMd5mqWnBKRw/vpJ3Xpg40x2zoGg/eQGs0+hXt2qCvqYPNGTUSvbUr+69q3hy5JL3XoAW+vpnyJpqHt4WGyomOpZnBVKLN1GsqBodzDZkVbxYOZdPevr5Z54ZcC+qNVfXF8R1Jbre5J2/B/iw8FOpnwItpPRJLMqNeuVHZgy1425l6YeSxg/Zl2DQj4xlT1O1LSW66UC/EpLp5Gd+vltVtd1rGvvvRlrLoPayU4S9oxt2XKRsDunkeb6dlXkuSc4FHVtWkw6pmYt5QxpELql+CoFd1vS2fYm6v+kmbf8myGX1OPs+wn5Mh5kYPPRdlQ5JHV9WcTMVpCaZOnLR+Yz0Fo3mHu1fVp9Pmrve6lujq8lxa780oW+kLquqwPuXNyKC9N5mboGVrWnb0905azqyGmNPOwb9lgLX/AKrqyMzNuDk+Z/OVExZ3ZJK7VdWn+tZnnk8keQxtlMP4sarP3PJza+AEY1X1+O7u69KmEW1fVdOsvT1EsDmrRiJow3znB24L7VvW8gb+rs2y02Kk15SBcSakgcWy4m1PS5IxcVa8WUjy5araN2OTzzOWPGfCsi5PGwIx6u07CnhR9Zhon+Skmjfxf6F9SyzrhHnzE8Yf6zWROC1By0G0eUXjk7Af1aOsWSUE2eT/mHmZM5dQxuCZGLtyv05LDz/tMhEkOQn4i6r6WZI/pw2nehJwc+BPq+dE+8wwoUoGSPaQlsnuOVX12W77TsCLq0c20FlI8l3aBe/PaX/Dq9CSDPyElpFxycFEkn+hDdH/Fhtb0KuGW4qht+64N/qcPJx2jH9nz4vB8XJ7He/mlfHm7u41gNvSAiaA/YAvVdVEF2VdD9eHaEP3Rv+/fWgjT+5f/TNdP5qWFG2Hqrp+d+H/uj7nySRn0uaknddtX432XqfK8DikJP8FPJvWYPc02gX1KX2HhyW549jmRcD3qursqSs6kK5H4z1V9YMByxxkWaru/HsF2nnoD0x/3v3OArureixcn+QutGVsjmHK6TVjZf75Qvur6rgeZYU2Cuj73fauTBFsdufcUcPJDWnB/yf6NCgmuSdwL1rCxfeMPbQ9LfHfpMm4Bi1vNdtcD+RI355Iew6bL9GGLF6dlqxg5ALagqarxSC9fWlroXy8qvajBYi9JLkN7SJmx3kf0O1pLaJ9XGWRx/oMhYLWY3MGcHdaC+jDaEkoJjbD1tpPpK3BeDgt+HwIrZV0h+73bvHidV7L/s1oQ3GhZWedplfunlO8dr6tx97LQ2hzjD4AfCDJKX0LrRmttdkZIuPhFUaBIUBVfa47ua4WRwPvr6qjAJLcjZZc4M3AfzFBDzYt8dH1qmrS+UQzs5lGndHQm+d2Q96eU1XH9Cxz6mF9o2AjyadoFzA/6ravCbxlkrK68n4C3DZtXuVoKN7Hq+ozi7xsKZ5AG8Hyle73fDMt+2sf59HOsyMXMMUakUPrLqj/pap+wUC9N1V1bJI/of0Ni9aIsppcCfhUN1rnPcD7us9SL9nMsk/0mLM59Pl3wCHc0KZF3Jg2cueSRjGmSDDC3PUIt6N9Zk6kx/rHVVVJjgRu2m1/d4p6QRulc4ckV6WNEjmBdk5/WI+yfkib+nJf5o5quIDWg73S5Q1uwE6LmVyTGhyyaVa8rvXyz4Ff1TCL6A7lSbRg7kLakMOjaAkWJlJVFyf5Y5Ir1xTrqtBaoK9I+xyNf0DPp83T6GOwoVBJtun+fzeoqr9Ksn9VvTXJu9h0TuNKe3D387Hz9v81E2bJTJsn+2g2npTekeT1VfXqRV62WaOgM/PS//e09dj/5S60HoiRiY9HYxfoYe7F/7QtylemDSW9Q7d9LG1+b9/vy7fTlqJ5e7f9cKDPfNJZ2beqHj3aqKpPJfn3qnpsWrbaSXyN1shzzpAVnMZiF5VdY9lNaHOGljyfaYYNRbuMAsPOT2hDw3vpGiU+u8UnLt2FVfX7dPPV05aNmGgI0lhj4lnAV5J8pCtjf1ZRg+wMLqhX/VDaatMwnp9kT9rF/rFJzq6qv+hZ5D4MtyzVYD1pXXmXB55KW9LrMV2j+42q6mM9irvl0D3eVTVneGCSXZh8KO64k5LcsjZmVp1Gquo3SQ6iLWXzkr4NvF3j9Ve7a7MAN+weOrNPT2RVfTXJ14C710BzwWdgqE6LIwf6f85hcAgk+RjwrKr6WtdKexKt1eH63UX1K1e0gp1qa/E8hyl6+8b8CjgtydGMzbmpCVIGV5t3d2ySt1TV95JcvqZfL+gQ4ENpC3puMhRqwrKOp/X6jA4uv0ib+/Vj2tCtVWPgFsyDgFuPetOS/BttXkGv4DADpv+nNWocm+SntHktn+9+xw1oGVEnMsML9MNoQc4oaH8ErRetb/biR9GSXH2QdhH8+W7favGjJM9kY9bEhwA/6QKnSZMrXIWWTvsEpsjku1yq6mLahUmv78cMHJNNl3f49ArWZ75jkzyblg30rrQ1VT86YRmj7+23mNtz9pEB6je0IS+oofUG3WL+UFraMWc1OYd2rjyP6c6XQy5LNVhPWufN3etHw/t/QJuP1ic4/FKSPapqmszgW3I2bY5qX7cGHt5NI/g1U0wRoXWs34YW1IyyKU+bFOq2tB7l73Z12yXJAX2C/64TZJck266mUSxjhuq0eH3aPPrDgXcP9fkzOGx2q6qvdfcPBI6uqkcmuRLwRaZrqZlakkUnOfe86PogG3uWRi16fTMcXSvJJ2i9iNfphjQ+tjZOpl6yGQ2Fen039OEfadlQrwj80xTlDS6bLlz/edo8nj6LLYe5y0JczHTZqwZL/19V/5zkGOCawKfGWpO3ovWMT6wLYE6vqhtv8clLd/2qGl+z6fl9WkW7/+vjaHM2TwOe1qcldBn8DW0phg9321/s9m3NxgB5qYZa0mFZVZfAaqVV1RPTktOMhoVPs7zDLDwT+Dva5/mxtOUd3jhJATWDJGEzdGvgYUm+x/QX1LD6h9I+nvad35EWKD16ygvOQZZ96l4zdE/a9avqIWl5J+h6wvqeK/elrZE99dz8kcxd/28r2tz8iRN7ZeNSInfvW5cFHEJL7vKhqjo9LTnitCMUXg7crarOBEiby/hu2lqvfXwH+GJ3DT3eCTJERtBpDdJp0V2T3Yg2yuz9Sf5A+5sdPs1IB4PDZvxi7S60TE5U1QVJhkpJPI3bAN+n/cO/whQX+kn2p01Kfk23fTztJFC0k34fr6QddI6AS7r0Fxz+sVQDDYW6xtjwpVHygNd0P1fTfC8YYOH6rgf3b2mtoV9JMrqgvB8TZHldwKDLRFS3xMa8ff87RXkXJzlz7AQ4hN8muX1VfQEuyb772x7lvJV2fPk8be7mn9JOqqtKVf2UzQfnZy21nC5Q/++BA/VLnWpJLKaZqzQT8xpi3rCl5y+hvFmsDTe0IS+oYTNDaUfnqlVw4boLcEhVnTJQeYcOVM5Cpu1J+31att0CSHJ9+q/lO/RyTzB3CaqLaD1DX9zckxfxYWCvboTXB+Y1fPYyNnLsikmuWG3ZrV6L1Y+5zCgw7H7H/ya5zBTljUYmbMVss4P2Meq0+Cc2dlo8t09B3d9sNBz8ZrRA8ZgkP66qXisHGBw230/yJNqBZi/gkwDdQWOaD+ZQ/oS22P0oq+rHaQeJPmnwn0H74IxsS2uVuSItqOiVMriqvj+vwW2aBc2HsjXtfS0UTK+2NL1DLFy/J7SLiySfY+PC0gdW1clT1G2Wy0QM5aq0hE3HM7eFsO9QxscBb0ubewgti+cBPcrZo7oMu0neRBvqvOp0LbT/j00zCk40XGtGgfqlStdr+G+0VuQw5fzZIc3g/zuLteEGVcPOuYbND6Vd0YvXbFzO5qXztoHeyzsMuuzTUD1pYw6lXe/tkuSdwO3oud7uDD4nAO+nrRt7cVf21j2n74xfA/Vd/mxugclNaY3aQy7PtCHJG9m4jujDmGKN5tEIhayy9YUBqmo02uJYhvufbEU7b+xE6wDpPe/f4LA5iDYh9C+Ah1TLTAZtmMCbN/ei5dIdGD4JfDItOcRDgc8leX5V/eeExW1bXSrjzhe6g/7P0j974vfTUlVX18pzMD2zgQ7sR1XVe32mZTbEwvWXT3ILNp4IvtD9TJK9asJ15rp5gDux6bpX16XnENAZGnqY8PlVdbO0dc2oqvOT9JkXesmohKq6qP+IpZl7H/A62vDAaRt2hg7UL21eAtynqlbDMXQhQ/5/B18bbmgZds71+AXrEHP0h3Qim59iMlFStHGZm9V3W1qD+697NnYM1ZMGXJJ460TatV6Ag7tRFBMb+nPSOYZ2XToKai5Hyww66RJItZn70/hv4Kk1d3mmNzB53cb9PS0b8qgH8vO0bNm9ZO76wqTlOlgV6wt31/IPZNMG2YmvWZPcgRYX3I/W0HY48JSaIuGk6xxuRpI/qZ7rQM1C90H6S9oHYFdaN/RhNeFaREnOqqobbOaxb1XV9XvU7erAq2gHsdAOXgfXAGvMTSMDrE+3XJJ8A7gRML5w/Zm0E+CS5i10J+ET2ExP6aS9QGmJmv6hqk6bt/+mtDX6pl5odUiZuzD35WnLZlywpddtpqyF1u48saommvuQ5GI2XkCHdnL/DauoNwj6vbdFyrrjQvuH7EFYz5J8se9QoOUw5P83M1gbbmhJvkpLeDJnznVVHbSFl26uvNvQhvlfsaqmmqO/1nTz+fanZUd+1iqozzE1b33OhfYtsaxBPyddmadU1c23tG8J5YzOQ+PnIJjiPJQF1mFeaN+EZV6BeT2lwGX7NqJkFa8vnLYszi9pjTKXNMhW1cs2+6KFy/k+bbWFw4H3VtUgWcLtOdy8IxlmfbOpJXkbLTnLkcDza2PynD6+koWXingsPYe8dS1tfda2mbWJD/AraIj5CmdNGgBuwU7zA0OAqjotbQHdVSNjC3PT1tS6Nq0nbKLPQJIb01p6r9wN7xvZnh5Dhapq2uxty+WjaYkoPsTci/SJh5JVW8dtk0B9uKquexuSvIc2T2jVBUwDB/mzWBtuaIPOuWYGc/SH1s2F2p2566/1Wi5iXLXeiA8neR6w5OAwyWks3OPVK+lLWqKwywNX797rqEF1e9q5o4+hPycAvx4f9ZNkb3rMfZ/ReWgWyzMN1VM6sprXF965qoa47rt9ja1xDZd8f39RU/T+GRxu3moa//VwWqvPwcCTx4am9Wn1eQrt4Pw3bByrvzdwWVqX9JIleUa1tW3G5wFcoiZYFmMW+s6RWE5Jtq+q85mbve4SK/werrLIY5dbrkos0VALc98IuDftvY/3jF5AWztyvRrNpxxPFd9rKNlQgfql2Pa0lv27je1b8YBp3vDAOQ/Rvxd88LXhZmDwOde1OufoA4zWYTwY2Jm2cP2+tKWQejU8zmtk24q2NNWkWbjv3ed3L+KxtMRg16L13Iz+GecDk07VGRl9Tj7PcHPzDwHel+SHXR3/hLk5I1bS+PJMMMzyTNuNzwusql91jYt9reb1hb+U5KYLNcBP6IAk762qM7oRhp8EbgZclORvqqrXMkgGh5s3dSa2oVTVVgOWdQ5tqYg7s3EsfN+lIh7Xddv3njAs3kU78Y3me4xfMUx6cb7ZbLNJrtZjmO+GzfQy/x0b16BcLaZemBugqj7SDad9ZlW9eOA6rlo17DqbQwXql0pV1SshxqzVbNYUXY614aY1f871lWk5CvparXP0Rw4Gbgl8uar260ZTTHMsHG9ku4i2ht3+kxQw3jOSZKeufgDH9xlGV1WvAl6V5ElVNdT6pvelBb0H04KQ7WnBU29VdUL39x81oPRaFH4WqurnTJ+ddL75PaX70C9L+MiqW184yddooyS2AQ5M8m2mW/rkIbTlxmBjI++OwA1p2dJ7BYfOOWTTrFzzrYUeqJWQ5BDaB/OawHtpk8OnyYqpASX5Fi2z7TuAt9TcbKhLef1OtGGGv2djMLgPLanA/VfZnNyXAL8AHklLlvN44OtV9Zye5R1fVbcaroar06j3v7v/V1X1vrHHXlxVz+5R5leq6tajOb9doH5Sj5PepVKSnWlL2ozmHX6eNof77JWr1Wx0c62vT1uPbJC14YaWlojqR9WtOZuWxXyn6rmGWBaeo//k1XKdkeSEqrpl2rqut66qC5OcXlXTJFYZqm4PpmVT/Rztb3cH4OlV9f4pyrwJsAdzh9C+bYLXL9SjPmrk/R0tM+1zquqYCcoc/Lg8tCQfZdP3/UtaZ8F/V481mpPckjZ37ofdrmvSkkRO1BidTdcXPmy1BNVJfk7Lsrug+UNEl1DeydXl1kjyAdr60f/dbW+SO2HJ5RocQtqipaNem+vQ0taHNrTs/wZuVV93uvlFf93dLkfrDXt3VX1zRSu2BiRZ9ItbE2YYXaD8pwD/TlvOYsknvHll7Eeb8wptjbM+vcwzlZbC+SDaULwARwFv7DvmPskraPOg3sPcjIxT/T9Wm/GTx/wTSd8Ty9CB+qVNkqNpx9DxoVAPq6q7rlytZqM7d2xi0gukWUqyAbhtVf2+294W+GJV3XLxVy65/KsCj6+qfx6ivGmlrY97IG1I451p10OXqap7TVjOgtNNRvpMO0lL+nLXUW9hkh1pCWB6JUHp5j7eiRYcHklbi/YLVfWgPuUtUP7WtHPnO6vqJlt6/tjrBj8uDy3Jq2g9VO/udj2ENiy3gO2r6hETlHVL4PtV9eOuN/2xwAOArwPPnbThpJuzPb6+8Her6pBJypiVof9/Sb4M/B3wE1oSw72r6jvdY2dUzzWHDQ7HJHkD8KGqOrLbvidwv6p67MrWbO1IW0rhMGDPGU2CXleSfHaRh6smSDCT5FPAo2vjekv70oYVvBS4W1U9eKrKXops5v8y0f9jLZjX6njJ/YW2JyhzPFAHOKo2rumkLchAGQrXksxbG65W0RqZm/l/TJyVMckutCV3rkUbkXE4bcjbI2mNqQcPU+PhpGWmvTLwyVFwPMFrx9eFfT7wvPHHq+qtPepzWnXrxnbbWwFfHd83aXm0+VknV1u6aCfgHUM3xCR57Kg3Z4nPH/y4PLRRD/NC+ybtaU5yEvAXVfWztORMh9MaFm8O/Omkwfr456QbuXL8agioAZKcDbx8c49X1WYf20x5+wJvoQXqr6yqF3b77wU8oqoe2qeezjmca9+quiTpRFV9omsF1yK6L989aT2Hd6EN+Th0Bau0ZlTVfgMWd42xwPAvaUHhfarqf9Oy0a5bSW5H+8xdl3ZcGw1P67U218D/l9VssfWvJmo5TLI/LQPba4A3pCWm2RHYO8kvphn6dSlzXpKHs7FF/qHAii4LNCuZzdpwQzs3yX2rW4+x+5z3WQvvbbQFrz9Ay069gZbwZc/VMEQ/LfHHH0bD75LciJax/XuTBoYwN/hLckifYHABn0xyFHN7q46corzfVtUfk1yUtqbtOcAu01ZyvkkCw9FLNnN/oe2VcsUk1xk15CS5DnDF7rFJPy9bj/UOPgR4fVV9APhAN7x5Uqt5feGtaX+nQSpVbW3sTXoHu06u3t8Ng8O5fpjkH2lztKBNPv/hIs+/VEtyV9qFy71oy2AcDjymqqbN0HWpkeTOVfWZzM3odomaLH39hV1r7S60VrdbVNUPu5PeaknfPCtvoiWMmLNmUF9dC/KLgWtV1T2T7AHcpqreNG3Zq8zNkpxPO1FdrrtPtz3p0h3PYG4mvW1pmZCvCLwZMDhcmkfR5hy+gnYh+CXaML/16IW0bJhz1oZb4TrN9zha9sn/pH0vvk/r7ZvUDlV1aHf/qCR/RRsu/MdFXrOcPknr8f9mkhvQMpS+E7h3klvVdOsSThXQdPXZqaqe3p0rb989NKpjXxuSXIWWgPBE2hIK/zNNXQcy5HF5Vp4GfCEtt0GA3YDHpy0VMWlDwNZJtqmqi2gdDI8Ze6xPnHKzeX+zy439PatWdn3hH1WPhe43J8lT5+0qWuPVF0bDS/swOJzrobShDx+i/YGP6/ZpYf9AmxvztGqZqzS5OwKfYW5Gt5FJ09c/jLZ21O+BlwCHpWWT3Z9VlH13Rn5ZVZ8YsLy30AKa0Ty5/6XNP1xXweHAQ7+3rarvj21/oWsN/llWz9pSq17X+3/fla7HMpnF2nCDqqpvAfumLVNAjaXan1Tmrql3Hm091XTlrnRCmqvWxjwBB9CGuj6pm2N5IhOsSzgDr6Rdb4waTD8IkOSm3WMLnT+3qKoe3919Xdqi5NtX1anTVnZaa2FKTlUdmWR3NvZanVkbk9C8csLi3g0cm+SntOykn4dLGgV+2aNuq/nvN3Q35kJZpHcFnpPk0Ko6vE+hzjlcQJIr2PultS4t2c1daPMpeqUzXu2yMaHPg2nDNT7I3IXDeyWQGZs7MT73Y13P+5pWkrOq6gabeexbVXX95a7TWjKLBB6rXZJP09bX/Rfg6rRhfbesqr6LXg8mycOr6h0LtMwDveYGfZeWwn6hi8PeQ+CHkuTU6rLEJvki8NKq+nC33WeO5XgWz8vT1u6EHr03C81vG3tszjzECev45wvtr6rj+pR3aZJkwd7z6p/4bl9adtJPja6/k9wQuGLf8/hqlGSH5WgISluF4dN951raczgmbe2hN9KGQV0nyc2Ax461LkkzkbZ46QNpLT6XfC+nGX7QHVDXzUF1M142b3ufsftFz4WbaestXa0rY3TimrgF81LmK1l4XczH0oada3Hj68VuksBjPRkNE2TTNQSvSxsSvxqMersHWd+xqnYdopwZOjXJvwM/oC0B8CmAbtjlxGrYdTEXq8Plpij36WP3t6Otz3oi/c8blybjwfp2tIbok2hzayfWzZ2bv+9/+1Vt9VquEQJdcp/evZT2HI5J8hXgQcARY70FX6sJUhBLfXRDWn7JvDlzVTU/+FmsjIXWW7rECo+zn6kk16uqb29p3wTl7UWb93UT4Gu0xCoPWg1DjlartIyTH6b13I4aJfYGLkvL+vyTFaramrNaMhLOSpKPAf9QVafN239T4MVV1WuY4FrTDfs6dKXrAZC2fuPBtN6bw6rqq93+2wLXr6q3L/b6Gdft3cBnFmh4+jva0hYPGej37ELL+PjAIcq7NOkaEQ6vqnusdF3EaAmyf6qeGdYNDsdk3uLN3b6Jh1NIkxqyESLJC4Ef0dZJC61F/ppV9dwhyl+NssDaQUlOrKq9pyhzG+BGtL/hmbVKFtFd7ZLcmY3ZJlflupir3UKf5/VkVsMEh5RkseNlVZcyfsrfsar/z0n2Wg1D+roEYR+izacfLYi+Dy3p1f1roGyvXU/L6VW1xxDlXZqkrU/4taq60UrX5dIkbTmW+YHcDrRkmo+sqjP6lOuw0rm+37WSVfdBP5iWVluatS8luen8lvSe7juvQeO1aYsHr7vgMMmNaYHIledlfN2eKbK6LTCfYq8kvedTXJp0waABoRZzlUUem2aY4JAWyjtwBVpGz6vRMq1Oa1Xl2F/AG2nLWayobtTBbbvekFEj6senbXiaN893K+AWrP+pGFNJciTwBOA/2Pi32xr4U+B9K1WvS7F7z9su4Lxp86YYHM71OOBVwLVp4+4/BTjfUDMz1uqzDXBgkm/ThuWNJu3v2aPYXyd5GG1pkaJl3F2vCZZuRDs4XoW5GesuAB690AuWaND5FNKWzE/gMS8V+0qnXx/ahs3MT/07NvYMrajxIf1JrkRrLD6Qdlxd8nD/Leg9smGZrKrgtao+C3x2wCJH83wLuAh4V1V9acDy16M3A0fRlqs4ntabexFtPcyzV7Jil0Zddus5kjwGeP005TqsdEyS21XVF7e0TxpKkusu9vhCX/wllLkrrZHjdrST3heBQ6rquz2quCYkuU1VzWx9KudTSMNZrmGC0+oy/j2VNjT/rcCrasplm5LsSGu42pW5ycceNU25s5DkfqOMpetJkv2BnavqNd328bR55QU8o6pck3UR3bIu/wTcgzZ95ZK1OifN4qvhDTFc3Z7DuV7NpkMoFtonDeUntB7rGwCnAW+qthBsb10QuP/0VVtTzktyDG2h5Jsk2ZM2vPZFA5X/a9oiv5KmNKthgkNK8lLgAbQW+JvWFOsbzvMR2jpun2Ys+dhKG1sWaNz/jfavhrmHA3oG8Ndj29vSenGvSOsZMzhc3O9p58TL0rL5/nHxp2uZTd3jb88hrdcBuC1wCPCKsYe2p7VimpBGM5HkPcAfaBcL96QNzTh4yjK3o82L+TPG5t2txpbpoSQ5lpaW/L+HyDSc5KPMnYuyB/DeqlrJhaAlLZMkf6QN8b+IuQkfphrmu1rXS02y2HDN6pv1cDWanxApyX9W1RO7+1+uqn1XrnarW5J7AC8HjgBeUFW/2cJLtMyS7DztEF97DpttaS1G2zB3TaPzaUtbSLOyxygzX5I3Mcx6cG8HzgDuDryANiRqvSdWunxVHT9vWZ9pemD/fV45zqeQLkWqaqsZFf2xJPeqqiNnVH4vVbXfStdhGV11fGMUGHZ2XOa6rDXPAf6qqk5f6Ypoo27qyyPphquProWq6sl9yjM4BKrqWODYJG/pM8dLmsIlyyNU1UVTrFk67gZV9VdJ9q+qtyZ5F61ncj37aZLrs3HR+gfRlvOYSNfrOugwX0kaczDw7CQX0o7/qyLhUJJnVNVLuvt/VVXvG3vsxVX17JWr3eC+spmESI9lmAbadauq7rDSddCCjgS+TLtumXqYr8NKgSSvrKpD5g0lu0RV3XcFqqVLgSQXszGTaGhp3H/DFBcMSY6vqlslOY6WbffHwPFVdb2Bqr3qJLkebW7QbYGfA98BHj5pEp5ZDPOVpNVuPInF/IQWq309xkkluQbwYdqw4dFcyr1pc+ju182JldaMob+j9hw2b+9+/vuiz5IGVlVbz6DY1ye5Ki2b2BG0IdPrbo3DcVX1beAvklwB2KqqLuhZ1CyG+UrSJbrj8+7MnRN+3MrVCJibxGL+EJZVtaTFtKrqHFpCpDvT5ubDKkuIJE3o7UkeDXyM1ugBQFX9rE9hBodAVZ3Y/Tx2pesiTauq3tjdPRZYt72FsOBi9aP9AH0WrZ/FMF9JAi5Zy/FgYGfgFGBf4H+AlU74Upu5v9D2utAFgwaEWg9+D7yUNid09H0tel4DOqx0TJLbAYcC16UFzqOhfev6AlvrQ5KnLvb4elx/KMmrN/PQfYFrV9VEDWCzGOYrSSNJTgNuCXy5qm6e5MbAi6vqAStcr9Gxb/y4R7e9XVVdZqXqJmlxSb4N3KqqfjpEefYczvUm4Cm0RXlXzfpD0hKNMu3eiHbxcUS3fR/W6fDIqnrS6H5aN9/DgGfSJmb/c4/yZjHMV5JGfldVv0tCkstW1RlJbrTSlfLYJ61pZ7GxQWdqBodz/bKqPrHSlZD6qKrnA3SJaPYazbtLcijw8RWs2kwl2Qb4W+D/0YLCB1XVmStaKUla2Nld2vkPA0cn+TlglnRJ0/g1cEq3Xun4nMNeS1k4rHRMkn8FtgY+yNw/7kmbfZG0yiQ5E9izqi7sti8LnFpVK946PbQkT6DN3zkG+LdJs5NK0kpJckfgysAnq+r3K10fSWtTkgMW2l9Vb+1VnsHhRl3EDRsnc47mGa30RHFpyZI8B3gw8KFu1/2A91bVi1esUjOS5I/AOcC5zE2aMPru7rkiFZOkBSTZFzh9bGTH9sCfVtVXVrZmktQYHDInkccoNWHRLja/UFXfWZlaSf0l2Ru4fbd5XFWdvJL1mZUk113s8apyuJakVSPJybRh/9VtbwVsWE/rCEpaXkl2B/4F2IO5S+T0SqjpnMPmSgvsuy7wnCSHVtXhy10haRpVdWKS79MdJJJcp6r+b4WrNbiFgr8k966qj61EfSRpC1JjrfJV9cdu3rQk9fVm4HnAK4D9gAOBrfoWZs/hIpLsAHzaFj2tJUnuC7wMuBZtyOV1gDOq6s8WfeE6keQkv7OSVqMkHwQ+B7y22/V4YL+qut9K1UnS2pbkxKraO8lpVXXT8X19yusdVV4aVNXP2DjUVForXkhbWPl/q2o34C9oWTwvLfzOSlqtHgfcFvgBcDZwa+AxK1ojSWvdhd0Q9W8meWKS+wNX7FuYQxkWkWQ/4OcrXQ9pQn+oqvOSbJVkq6r6bJJXrnSlltFjV7oCkrSQqjoH+OuVroekdeVg4PLAk2kdBHcGFsxguhQGh0CS05ib6RBgB+CHwCOXv0bSVH6R5IrAccA7k5xDWwNn3UnygM3s3xmgqj64vDWSpE0leUZVvSTJq9n0eqP3emSSVFUndHd/RZtvOBWDw+be87YLOK+q1uUFtda9/YHfAU8BHkZbR+sFK1qj2blP9/MatKFan+m29wO+RFuzVJJW2je6nxtWtBaS1p1uKb6FGp16LcVnQhpJa16STwEHVNWPuu1rAm+pqruvbM0kSZJmp1u+bGQ74IHARVX1jD7l2XMorTPdUMt/o/WmhY0Lwm+/ohWbrV1GgWHnJ7QsrZK0aiS5IfD/gF0Zuwbr28IvSVV14rxdX0xyfN/yDA6l9eclwH2q6htbfOb6cUySo4B3d9sPAT69gvWRpIW8D3gd8Ebg4hWui6R1oFt6b2QrYG/alKJ+5TmsVFpfknyxqm630vVYbl2P6R26zeOq6kMrWR9Jmm+atcckaSFJvkObcxjgIuA7wAuq6gu9yjM4lNaXJK8C/gT4MHDhaL+ZOyVpZSU5FDgH+BBzj88/W6k6SdI4g0NpnUny5gV2V1U9atkrs0wupfMsJa0xXQv/fFVV11v2ykha05JsD+xUVd/stv8KuFz38FFV9ZNe5RocSlrrkpzFpW+epSRJupRK8nrgS1X1lm77LOATtADxoqp6XJ9yTUgjrROX8kWWf2JgKGm1SnLnqvpMN8phEw77l9TDLYHHjm1fUFVPAkjSa74hGBxK68mleZHlDUneg/MsJa1OdwQ+A9xngccK8FglaVLb1NwhoI8Yu3+VvoU6rFRaR5JsDfxbVf2/la7Lcro0zrOUJEmXXkm+Cty9qn48b/+1gU9U1Z59yrXnUFonkmxTVRcludQtY1FVB650HSRpS5JcBXgksCtj12DrfNi/pNl4KfDRJE8DTu727QX8e/dYLwaH0vpxPO2gcEqSI2iLLf969OB6HmKZZDvgIODPgO1G++05lLTKHAl8GTgN+OMK10XSGlZV70jyU+BFtOufAk4HnltVn+hbrsGhtP5sB5wH3JmNi6Ku9zktbwfOAO4OvAB4GBvnYErSarFdVT11pSshaX2oqk8CnxyyTOccSutEkrOBl7MxGMzYw1VVL1+Rii2DJCdX1S2SnFpVeya5DPD5qtp3pesmSSNJngL8CvgYc5Nn/WzFKiVpTUryj8B/be74keTOwOWr6mOTlGvPobR+bA1ckblB4ch6bwX6Q/fzF0luAvwYuMYK1keSFvJ72lyg57DxuFzA9VasRpLWqtNocw5/B5wEnEsbPbY7cHPg08CLJy3UnkNpnUhyUlXttdL1WAlJ/g74ALAn8GZakPzcqnrdilZMksYk+TZwq6r66UrXRdL6kGR34HbANYHf0qbVHFdVv+1VnsGhtD6MhlaudD0kSQtL8ingflX1m5Wui6T1J8lVgV/UFAGew0ql9eMuK12B5ZZk0cQO63mepaQ16de0jNKfZe6cQ5eykDSRJM8F3ltVZyS5LPAJ2nDSi5L8TVV9uk+5BofSOnEpTWhwpZWugCRN4MPdTZKm9RDghd39A4CtgB2BGwJvpc05nJjBoaQ1q6qev9J1kKSlqqq3JtmWdvEGcGZV/WGx10jSZvx+bPjo3YF3V9XFwDeS9I7xthqkapK0gpLsnORDSc7pbh9IsvNK10uSxiW5E/BN4DXAfwH/m+TPV7JOktasC5PcJMmOwH7Ap8Yeu3zfQg0OJa0HbwaOAK7V3T7a7ZOk1eRlwN2q6o5V9ee01v5XrHCdJK1NhwDvB84AXlFV3wFIci/g5L6Fmq1U0pqX5JSquvmW9knSSkpyalXtuaV9krRSnHMoaT04L8nDgXd32w8FzlvB+kjSQjYkeSPwjm77YcCGFayPpDVqgYztBfwU+MKoF7FXufYcSlrrklwXeDVwG9rB8UvAk6vq/1a0YpI0pks3/wTg9t2uzwP/VVUXbv5VkrSpJM9bYPcOtOHqh1bV4b3KNTiUJElaHl3yCKrq3JWui6T1J8kOwKeraq8+r3dYqaQ1K8mraT2FC3JhaUmrQZIAzwOeSJcMMMnFwKur6gUrWTdJ60tV/aw75vRitlJJa9kG4MTudt+x+6ObJK0GTwFuB9yyqnaoqh2AWwO3S/KUla2apPUkyX7Az3u/3mGlktaDJCdX1S1Wuh6SNF+Sk4G7VtVP5+3fEfiUxy5Jk0pyGpuOntoB+CHwyKo6o0+5DiuVtF7Y0iVptbrM/MAQ2rzDJJdZiQpJWvPuPW+7gPOq6tfTFGpwKEmSNFu/7/mYJC2oqr43f1+SxwCvn6Zch5VKWrOSXMDGHsPLA78ZPQRUVW2/IhWTpDFd8pmFWvMDbFdV9h5KmlqSk/pmKR2x51DSmlVVV1rpOkjSllTV1itdB0mXCr2zlF5SgD2HkiRJkrS2Jdm5qs6eqgyDQ0mSJElae5I8dYHdvwROrKpTJi7P4FCSJEmS1p4k7wL2AT7a7bo3cCqwK/C+qnrJROUZHEqSJEnS2pPkOOBeVfWrbvuKwMeBe9B6D/eYpLythq+iJEmSJGkZXAO4cGz7D8BOVfXbefuXxGylkiRJkrQ2vRP4SpKPdNv3Ad6V5ArA1yctzGGlkiRJkrRGJbklcNtu84tVtaF3WQaHkiRJkrQ2Jdka2ImxUaFV9X99ynJYqSRJkiStQUmeBDwP+AlwMRCggD17lWfPoSRJkiStPUnOAm5dVecNUZ7ZSiVJkiRpbfo+bdH7QTisVJIkSZLWpm8Dn0vyccaWrqiql/cpzOBQkiRJktam/+tu23a3qTjnUJIkSZJkz6EkSZIkrSVJXllVhyT5KC076RxVdd8+5RocSpIkSdLa8vbu578PWajBoSRJkiStIVV1Ynd3e+DjVfXHIcp1KQtJkiRJWpseAnwzyUuS3HjawkxII0mSJElrVJLtgYcCB9LmH74ZeHdVXTBpWfYcSpIkSdIaVVXnA+8HDgeuCdwfOCnJkyYty55DSZIkSVqDktyX1mN4A+BtwFur6pwklwe+XlW7TlKeCWkkSZIkaW16IPCKqjpufGdV/SbJQZMWZs+hJEmSJMmeQ0mSJElaS5JcQEs+s8lDQFXV9r3KtedQkiRJkmS2UkmSJElag5K8fSn7lsrgUJIkSZLWpj8b30iyDbB338IMDiVJkiRpDUnyD928wz2TnN/dLgB+Anykd7nOOZQkSZKktSfJv1TVPwxWnsGhJEmSJK09Sf58of3z1z1ccnkGh5IkSZK09iT56NjmdsCtgBOr6s59ynOdQ0mSJElag6rqPuPbSXYBXtm3PBPSSJIkSdL6cDbwp31fbM+hJEmSJK1BSV4NjOYJbgXcAjipb3kGh5IkSZK0Nn0d2Lq7/wvg3VX1xb6FGRxKkiRJ0hrSLXb/YuBRwP91u68DHJbk+Kr6Q59ynXMoSZIkSWvLS4EdgN2qaq+q2gu4HnAV4N/7FupSFpIkSZK0hiT5JnDDmhfMJdkaOKOqdu9Trj2HkiRJkrS21PzAsNt5MRsT1EzM4FCSJEmS1pavJ3nk/J1JHg6c0bdQh5VKkiRJ0hqS5NrAB4HfAid2u/cBLgfcv6p+0Ktcg0NJkiRJWnuS3Bn4s27z61V1zFTlGRxKkiRJkpxzKEmSJEkyOJQkSZIkGRxKkrSJJPdLssfY9guS/MVK1mkpktw8yb1Wuh6SpLXJ4FCSpE3dD7gkOKyq51bVp1euOkt2c2DB4DDJNstbFUnSWmNwKEla95LsmuQbSd6Q5PQkn0pyuSSPTnJCkq8m+UCSyye5LXBf4KVJTkly/SRvSfKgJPdI8r6xcu+U5GPd/bsl+Z8kJyV5X5IrLlCPnZJ8qPt9X+1+F0memuRr3e2QsTp/bey1/y/Jod39zyX5tyTHJ/nfJHdIsi3wAuAhXb0fkuTQJG9P8kXg7UmOS3LzsTK/kORmw//FJUlrkcGhJOnSYnfgNVX1Z8AvgAcCH6yqW1bVzYBvAAdV1ZeAI4CnV9XNq+pbY2V8Grh1kit02w8BDk9ydeAfgb+oqr2ADcBTF6jDfwDHdr9vL+D0JHsDBwK3BvYFHp3kFkt4P9tU1a2AQ4DnVdXvgecC7+nq/Z7ueXt09Xoo8CbgbwGS3BDYrqq+uoTfJUm6FDA4lCRdWnynqk7p7p8I7ArcJMnnk5wGPIyNa0UtqKouAj4J3KcbpvmXwEdoQd0ewBeTnAIcAFx3gSLuDLy2K+viqvolcHvgQ1X166r6FW1R4zss4f18cN572Zwjquq33f33AfdOchngUcBblvB7JEmXEs4/kCRdWlw4dv9i4HK04Oh+VfXVJH8L3GkJ5RwOPBH4GbChqi5IEuDornduKBcxtxF3u3mPj97PxSx+Pv/16E5V/SbJ0cD+wIOBvQeopyRpnbDnUJJ0aXYl4EddT9rDxvZf0D22kGNpQ0IfTQsUAb4M3C7JDQCSXKEbtjnfMcDfd8/ZOsmVgc8D9+vmO14BuH+37yfANZJcLcllgXsv4f0sVu+RN9KGt55QVT9fQpmSpEsJg0NJ0qXZPwFfAb4InDG2/3Dg6UlOTnL98RdU1cXAx4B7dj+pqnNpc/neneRU4H+AG8Mly2Dct3v5wcB+3TDWE4E9quokWg/m8V1d3lhVJ1fVH2gJZo4Hjp5Xv835LLDHKCHNQk+oqhOB84E3L6E8SdKlSKpqpesgSZKWSZJrAZ8DblxVf1zh6kiSVhF7DiVJupRI8kha7+RzDAwlSfPZcyhJkiRJsudQkiRJkmRwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJOD/A9izANkmzHa5AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1080x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,8))\n",
+    "sns.countplot(x='native.country',data=df)\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['native.country'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Majority of the people working belong from U.S. whereas there are people who come to U.S. from their own countries but there no. is very low. Second highest no. of people belong from Mexico as it is a neighboring country."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:16.020665Z",
+     "iopub.status.busy": "2021-07-05T16:35:16.020406Z",
+     "iopub.status.idle": "2021-07-05T16:35:16.513800Z",
+     "shell.execute_reply": "2021-07-05T16:35:16.512712Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:16.020640Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Minimum 17\n",
+      "Maximum 90\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.histplot(df['age'],kde=True,color='r')\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "print('Minimum',df['age'].min())\n",
+    "print('Maximum',df['age'].max())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Minimum age of a working individual is 17 and highest is 90 which is way far retirement, but majority of the people working are in the age 25 to 45. Data is skewed to the right side."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:16.515521Z",
+     "iopub.status.busy": "2021-07-05T16:35:16.515168Z",
+     "iopub.status.idle": "2021-07-05T16:35:17.180910Z",
+     "shell.execute_reply": "2021-07-05T16:35:17.179988Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:16.515490Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Minimum 12285\n",
+      "Maximum 1484705\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.histplot(df['fnlwgt'],kde=True,color='k')\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "print('Minimum',df['fnlwgt'].min())\n",
+    "print('Maximum',df['fnlwgt'].max())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is assigned by combination of features and has the peak wt as 0.2*1e6. Data does not follow normal distribution and data is rigt skewed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:17.182335Z",
+     "iopub.status.busy": "2021-07-05T16:35:17.182055Z",
+     "iopub.status.idle": "2021-07-05T16:35:17.609944Z",
+     "shell.execute_reply": "2021-07-05T16:35:17.609082Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:17.182307Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Minimum 0\n",
+      "Maximum 99999\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x864 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,12))\n",
+    "sns.distplot(df['capital.gain'],color='m', kde_kws={\"color\": \"k\"})\n",
+    "print('Minimum',df['capital.gain'].min())\n",
+    "print('Maximum',df['capital.gain'].max())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Minimum capital gain is 0 while the range goes on to 99999 but most of the people are with the gain of 1000. Data is highly skewed with a very long tail due to presence of large outliers. Outliers here are very few people belonging to elite class who have very large capital gains."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:19.026256Z",
+     "iopub.status.busy": "2021-07-05T16:35:19.025814Z",
+     "iopub.status.idle": "2021-07-05T16:35:19.455618Z",
+     "shell.execute_reply": "2021-07-05T16:35:19.454778Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:19.026210Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Minimum 0\n",
+      "Maximum 4356\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x864 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,12))\n",
+    "sns.distplot(df['capital.loss'],color='g', kde_kws={\"color\": \"k\"})\n",
+    "print('Minimum',df['capital.loss'].min())\n",
+    "print('Maximum',df['capital.loss'].max())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Minimum capital loss is 0 while the range goes on above 4000 but most of the people are with the loss of 1000. There is also a slight peak seen near 2000. Data is highly skewed with a long tail to the right side."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:19.457101Z",
+     "iopub.status.busy": "2021-07-05T16:35:19.456823Z",
+     "iopub.status.idle": "2021-07-05T16:35:19.900891Z",
+     "shell.execute_reply": "2021-07-05T16:35:19.900079Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:19.457072Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Minimum 1\n",
+      "Maximum 99\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x864 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,12))\n",
+    "sns.distplot(df['hours.per.week'],color='b', kde_kws={\"color\": \"k\"})\n",
+    "print('Minimum',df['hours.per.week'].min())\n",
+    "print('Maximum',df['hours.per.week'].max())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Most of the people work 40 hours a day where there is a high chance that they belong to private sector. There are people working as low ass 1 hour a week and as high as 99 hours a week which undoubtfully might belong from the armed forces. Data shows less skewness compared to the other features in the dataframe."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:19.902487Z",
+     "iopub.status.busy": "2021-07-05T16:35:19.902231Z",
+     "iopub.status.idle": "2021-07-05T16:35:20.562454Z",
+     "shell.execute_reply": "2021-07-05T16:35:20.561464Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:19.902460Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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KurpGzfa5kj4taXXergeGqevN/P0tMZBBkxDIaIaDkj5su10q/reYilFt7bGE3XXrr3Lx/9zaVTzQ6Om65f+r4t9n1ZTr+tgotuefJf12Ppd8UW5Dejt8T7p43vXqoV4MVIVAxoRLKT0v6U5J/2j7WUnbJd0u6RHbh1X8+5+y51Q89vHfJN2R77AoOyRpYe2inor/Vfbntp9Rg9Gq7U7bu/LsF1U85esFSX8r6RsqHqv4AxWj4qMqHq9Y/4sAqBRPe8Oksn27pB+nlD7R5HbelVL6cR6Ff13S+1LxDGQgDM6FYbp43Pb5Ki4o3kEYIyJGyAAQBOeQASAIAhkAgiCQASAIAhkAgiCQASCI/wfXXq3svYhl7wAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 432x288 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for i in cont:\n",
+    "    sns.boxplot(df[i])\n",
+    "    plt.figure()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are outliers in all the features, while capital gain and capital loss have very vast no. of outliers."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Bivariate Analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:21.406007Z",
+     "iopub.status.busy": "2021-07-05T16:35:21.405672Z",
+     "iopub.status.idle": "2021-07-05T16:35:21.681042Z",
+     "shell.execute_reply": "2021-07-05T16:35:21.679969Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:21.405972Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='workclass'>"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.stripplot(x='income',y='workclass',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are individuals belonging from every workclass who earn >50k except for never worked and without pay, and even there no. is low in the <=50k category."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:21.683039Z",
+     "iopub.status.busy": "2021-07-05T16:35:21.682645Z",
+     "iopub.status.idle": "2021-07-05T16:35:21.997883Z",
+     "shell.execute_reply": "2021-07-05T16:35:21.996728Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:21.682998Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='education'>"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.stripplot(x='income',y='education',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There is no individual who has done preschool and earns >50k salary while there are few who earn 50k even after going through 1st-4th and 5th-6th in the education criteria. It is also to be noticed that there are doctorates and prof who earn <=50k even with such high education. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:22.868263Z",
+     "iopub.status.busy": "2021-07-05T16:35:22.867933Z",
+     "iopub.status.idle": "2021-07-05T16:35:23.135283Z",
+     "shell.execute_reply": "2021-07-05T16:35:23.134350Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:22.868234Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='education.num'>"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.stripplot(x='income',y='education.num',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is clearly seen that as the education no. increases chances of earning >50K salary also increases"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:23.458951Z",
+     "iopub.status.busy": "2021-07-05T16:35:23.458638Z",
+     "iopub.status.idle": "2021-07-05T16:35:23.729032Z",
+     "shell.execute_reply": "2021-07-05T16:35:23.728157Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:23.458923Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='marital.status'>"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.stripplot(x='income',y='marital.status',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are less no. of individual who are married armed forces spouse, thats why the no. is less in both the categories while people with married spouse absent are less in >50k category income comparatively."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:23.730509Z",
+     "iopub.status.busy": "2021-07-05T16:35:23.730264Z",
+     "iopub.status.idle": "2021-07-05T16:35:24.040631Z",
+     "shell.execute_reply": "2021-07-05T16:35:24.039822Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:23.730485Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='occupation'>"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.stripplot(x='income',y='occupation',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are very few people with income greater than armed forces and private house service while all the other categories of people are distributed evenly in both the income categories."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:24.498212Z",
+     "iopub.status.busy": "2021-07-05T16:35:24.497810Z",
+     "iopub.status.idle": "2021-07-05T16:35:24.936832Z",
+     "shell.execute_reply": "2021-07-05T16:35:24.936038Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:24.498182Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='native.country'>"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x1080 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,15))\n",
+    "sns.stripplot(x='income',y='native.country',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The grapghs shows people belonging to diff countries have less chances of earning >50k which is wrong, this is because no. of individuals belonging from other countries other than U.S are very low nut it is to be noticed that there are more people in the category <=50k than >50k."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:25.058221Z",
+     "iopub.status.busy": "2021-07-05T16:35:25.057755Z",
+     "iopub.status.idle": "2021-07-05T16:35:25.198488Z",
+     "shell.execute_reply": "2021-07-05T16:35:25.197591Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:25.058192Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='age'>"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(6,8))\n",
+    "sns.boxenplot(x='income',y='age',data=df,palette=\"Dark2\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "People with higher mean age earn >50k while there are individuals earning <=50k even wat very high age."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:25.200090Z",
+     "iopub.status.busy": "2021-07-05T16:35:25.199802Z",
+     "iopub.status.idle": "2021-07-05T16:35:25.345288Z",
+     "shell.execute_reply": "2021-07-05T16:35:25.344678Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:25.200063Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='fnlwgt'>"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(6,8))\n",
+    "sns.boxenplot(x='income',y='fnlwgt',data=df,palette=\"Dark2_r\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "People are equally divided with respect to fnlwgt in the income category while it is seen that as the fnlwt is high indiduals fall into <=50k income category."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:25.346871Z",
+     "iopub.status.busy": "2021-07-05T16:35:25.346494Z",
+     "iopub.status.idle": "2021-07-05T16:35:25.475057Z",
+     "shell.execute_reply": "2021-07-05T16:35:25.474403Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:25.346820Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='capital.gain'>"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(6,8))\n",
+    "sns.boxenplot(x='income',y='capital.gain',data=df,palette=\"crest\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As the capital gain increases more people fall into >50k salary while mean of both categories remain cloase to zero capital.gain"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:26.988346Z",
+     "iopub.status.busy": "2021-07-05T16:35:26.987809Z",
+     "iopub.status.idle": "2021-07-05T16:35:27.116512Z",
+     "shell.execute_reply": "2021-07-05T16:35:27.115855Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:26.988304Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='capital.loss'>"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(6,8))\n",
+    "sns.boxenplot(x='income',y='capital.loss',data=df,palette=\"ocean\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There is more density in the >50k income category with increase in capital loss while mean of both categories remain cloase to zero capital.gain"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:27.117918Z",
+     "iopub.status.busy": "2021-07-05T16:35:27.117540Z",
+     "iopub.status.idle": "2021-07-05T16:35:27.252839Z",
+     "shell.execute_reply": "2021-07-05T16:35:27.252061Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:27.117880Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='hours.per.week'>"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(6,8))\n",
+    "sns.boxenplot(x='income',y='hours.per.week',data=df,palette=\"rocket\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "People earning >50K income work mean hours per week greater than tose earning <50K while people from both the categories work from min to max hours per week."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:28.189107Z",
+     "iopub.status.busy": "2021-07-05T16:35:28.188736Z",
+     "iopub.status.idle": "2021-07-05T16:35:32.342940Z",
+     "shell.execute_reply": "2021-07-05T16:35:32.341965Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:28.189074Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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IgiAIiSVlZSDlDawMLE8tT04wgiAIQtKdM3P88tNtPPyx8/i/t4/h9ql8cHkZF0zNTXZYgiAIgpAw5tuuQn1vK0ZbJ/KUMpTlC5IdkiAIgpAk50ziB7B4YjZ/+Wj28AcKgiAIwjggZaRhvu7iZIchCIIgpIBzKvEbszQV1v8Sjr0NBXPgoq+AQySwgiAIgiCMXXu7mnj0xG6Cus5tJbNZllOS7JAEYVwTid9YsPo7sO4Xff+/6j1oOQB3P5fUkARBEARBEKLV6HPz4I6X8OsaABvba/jTkpuYni6m4QhCopwzxV3GtH3PDHx8/B3wtCclFEEQBEEQhFita63uT/oANMPg7ebKJEYkCOOfSPzGgqyygY/t2WBNT04sgiAIgiAIMSq0DT6PKQqxTRCE+BGJ31hw5XfAmd/3/012uPbHoJiTG5MgCIIgCEKUVuSUckXB5P7HS13FXF04JYkRCcL4J+b4jQUTFsIX9kLjXsipALsr2REJgiAIgiBETZYk/mf2pdw/aTFBQ2eSU5zbCEKiicQvlXRUQd0OwABbBky6GJSTfyKTFUoWJy82IWl8vUHqDnfgKnCSPcGZ7HAEQRij9NpGDJ8frBbw+ZEnFiNZxOgRYWgezc/WjsPkWjKZlVE2/BNGqMSRGfc2BUEITSR+qWLHw/D8g2Dop7cVzIV7XxHz+c5hjce7eP6XOwn6+ybAn3fDJJZeNynJUQmCMNYE//06+pHqgRvTHFg+eANSVkZyghJS3glPC5/Y+Svagz0A3FC4nK9PvzPJUQmCEC0xxy8VGAa88a2BSR9A0x7Y9XhyYhJSwuYXK/uTPoBtr1Tj9wSTGJEgCGONXtMwOOkDcHtQN+8Z/YCEMeOR2tX9SR/AC40bqfI0JTEiQRBiIRK/VKBr4OsKvc/bMbqxCCnF3zswydNUfUAiKAiCMBzD5w+/0+sbvUCEMac76Bm0rSvYm4RIBEGIB5H4pQLFBAvuGrzd7IA5t45+PELKmHn+hAGPy2Zlk+ayJSkaQRDGIrm8BNJDzw9W5k0f5WiEseSGwmVISP2PKxyFzM0oT15AgiDERMzxSxXX/QwK5sDxdyHQCzmTYel9ff8VzllzLizG5jRTtacVV6GDuReXJDskQRDGGMlswvKh96Ft34fe40GSJJAllNlTkCcWJzs8IYWtzJnFr+Z9ktebt5FryeSO4guRJXHPQBDGKskwjGTHMKwlS5YYW7duTXYYgiAIQoJJkrTNMIwlyY5jrBD9oyAIwrkj1j7ynLzj98yOWr770gE6PUFcDgvfuH4mNy5Ikauebcfg6fugcTdggMkGc26D6VfDuz+E3jZY+EG4+GsgScM2J4wdx3Y0s/mFStSAxuwLi1l05cRkhzQiVbu2895jf8fb3c3siy9n5e0f6LuzkCS6X6Xz+eN4D7SB0fd1sc3MIet9FcjWc/KnTzhHGV09qG+sQ29o6fsieP0ggTSpFPM1FyI5oh8+bug62rpn0fZvQHJmYrrwNuSyGXGM/jRPzXo6t/0OzddN+vQbyFxwb1J/Y84lJzzN/OTovzjqrmd59gy+OOUW0kz2mNs1DIO/Ve3g+fpDZJitfLxiCStz479kxFjUGdD45f5Odrb5mJ5p4XOzXBQ5Ur/v8vTo7F4fpKNFR5L76hfmFyvMXWHGYhXf12Q75+747a/v5tpfvTdgmwS88vlVzChMgZLWv1kBzfsHb5cUMM4o6vG+h2DR3aMXl5BQXS1eHvnWRgz99Pfxmo/PpWJhXhKjipynu4s/fvpe1MDpIhJXPPAg8y67KmkxdTxzhN5NjYO2O5cX4bppShIiEiIh7viNTCT9Y+Dh5zHqQldilKdPwnzT5VG/vrZjNerqR09vMFuxPPBjJJsj6jZDUT1t1D55M2iB/m25F/43aVOvi+vrCKF9cOsPOdbb0P84Xss6vNJwhO8ceKf/sVmS+dfKu8i1xvfzMxZ9a0cr7zR6+x/PzrLwmxUFSYwoMmue99HRMji3KJmisPgiSxIiGl9i7SPPuYHa64+1DtpmABuOtY1+MGfztIdO+mBg0gdw/J2EhyOMnvojHQOSPoCag+1Jimbk6g8fHJD0AZzYszM5wZzkP9o5ou2CMB4Zqho26QPQq+pial8/cWDghqAfo/F4TG2G4m/aNSDpA/DWiyGuo6E90DMg6QPY0nEoLm1v6xj4+QsaOrs6G8IcfW7Z3jawT93XGcCv6WGOTg2qaoRM+gBa6kVF8lRwziV+c4ozR7R9VNldkBHhkNOi+YmNRRhVeWXpEW1LVfkTJyGdNeE/f1JyCxOZi9NGtF0QxiPJZELKyQq/vzC2UQVS/lnD8mQFKTf+RagsOdMA6axtoiLpaMgyOym0ugZsm55eGpe2p6XnDngshdh2rpqaYR7weKLThFVJ7dN2k0kiLTP0cM6snNSO/Vxxzv0Vllfk8NlLp6DIfR9MkyzxhcunsrQ8O8mR0Tf34ra/guOsH73SFXD5/wNbVt+Qzzm3wbJPJCVEITFyS9JZecsUzDYFWZGYdcEEZqwoSnZYEcvIy+fy+z+FLS0dSZaZcf5FLLrmfUmNKeu6CiwTTw7fPvlLZynPIOu6SckLShCSwHT9xUjZJy9unnnimJ2F+arzY2pbWXIl8rTFff2XPQ3TlXcjpWXF1GYo5owSsld+GdmSDpKCc/LVZMy8Je6vIwwmSzLfnvEhim05AMzNKOeLk2+OS9s3F8/k6sIpKJJEusnCF6edT6kjBS7Ep4AvznYx7WTyV+o08V/zc5IcUWQWXWTBeTL5k0/+3GTlScxbYR7iWcJoOefm+J0SUHW8ARW7xYTFlGL5r2GArxPkk18S68k7FJraN9TFIsa+j1eapmNoBiaLkuxQoqJrGpoaxGxNnbUGdb8KZhmCuijqMgaIOX4jM5L+0fAHkKwWDH/fkEnJGr/5NkbQD4oJSU7sb5ehqxi6imxKnd+Yc4VhGHg0P84EvPc+TcUkyZjkFDsfSwG9QR2neWy9L4ZhoAbBZAY1CGaLKOoSL6Kq5wgYhsEb+5s42NjDhdPyWFCaleyQQpOkvmGf7ZWw/1lw5vUt5G629y32LoxbWlDnyJYm/F6VqUsKSM9OvZObnrZWtr30LNV7d5KVX8hFd99PVn7fhHNZUZCV1Epa+5M969jqOAUhHgxNRz90HP1oNXpnD5JJQZpUiml+fIdJSmZrXNsL+zqyCUlOTD+o6yqtNW/h620gp/hCnJkVCXmdsaYr2MtrzdswDIMr8xfjTMBr2MS5TVhjLekDkCQJ88nrSmZRzyWlnFN3/L713F7+vqEa6Mutfn7HAm5amCLLOJytYTf85SoIevoely6De18TSziMY5qm89T3t9JW6wbAYlO4/WtLySpInTu8nY0N/POrnyXgO11pTJJl7v+/v5KePTaGoQipTdzxG5nh+sfgv19HP1I9eIfTjuWeW5GcsZfkHy/2r/0KbXXvAiBJCrMv+iWugqVJjiq5uoMe7t72Yxr9HQDkWTL5x+L/wGURc6UFIRlEVc8I9fiCPLLpRP9jw4A/rIl/5bG42fLH00kfQM0mOLEhefEICVezv70/6QMI+DT2vhdbxb142736tQFJH/St47X+yYeTFJEgCOHo7Z2hkz6AXi/aviOjG1AK8/bU9Cd9AIahUX/osSRGlBrebNnRn/QBtAS6eK1ZVFMVhLHqnEn8JEkadLNszN08k86ZP5dw0pj5iI65L5MgnAuG+V6K7+3QRJ8b8hMkjZ2eSRCEs5wzv2ppVhMfWj6x/7EkwccvSm65+SGd93EwnzGSvmxF33BPYdwqm5VNbunp4TNWh4nZq1JrKPK8y67GYh849FSSZc6/40NJikgQhHDk7EzkaeWhdzodKLOnjGo8qcyeXkpOySX9jyXZRPG02BcoH+suz19Ike101fN8axZXFSxOYkSCIMTinJrjZxgGbx9q7ivuMjUvNdbuG0rnCdj/XF9xl1k3gTn1Cn0I8RUMaBzd2oTf01fcxZk1OgUTRsLd3sb2V1+gevdOXIVFXPihe8nIjW0tMEE4RczxG5nh+kdD19EPV6EfPYHe2Y1kUpAnlaDMm45kF33KmQxdpbXuXXzuenKKL8SRMXH4J50DuoMe3mjZjmEYXJG/iExzIsq7CIIQiVj7yHMm8XP7VSyKjEmW6PYFyXJYqOnw4DArZNjNmFNhUcygDwwNDB0UK5gsofdbxI/uucAwDPweFbNNQQvoWOypU/XM6+7B5kxDkiQCPi+yYsJkFmv0CLETid/IjLR/NPwBNJ8fCVAy0+MWhxHwYWgqktmKZIrvb4Gu+gCQTTb0oAc96EGx5yDFaaiqGuxFli3IivgNE1KHV9WRJQmrMvaH1gb8BmYzSPLY/7ckm1jOYRi+oMYXn9zJK3sbsZsVrCaZDk8QWQL9ZM5rNcl87+a53Lq4JHmBvvNDWPfzvuQOAyzpcPm34Lz7z9j/i751/BZ+GK77KSR4vSQheZqru3n9z/voavYiSX3FiMrn5XLFvbOw2JL3tW2vr+XFn/+AlhNVZBYUkj2hhKpd2zFZrKy49U6Wvu/WpMUmCEJ4hs9P4OnXoK6pf5tqtWD+6C3IWdEngIYaRH3lz+iHTyafigll1S2YFl8Za8gAdGz9Ld17H8cwdBRHLpq7AQDZlkXBVb/Amjsj6rY11cehTd+mrfYdTOY0yud9iqIpYlF4Ibk0w+AX+zp4qbYXsyxx16R0Pjo1xUeoheHtNdiyOkBHs47NAQtXWcgvEeeuyZQCt7kS6y/rKnl5TyOGAZ6ARocnCJxO+gD8qs5X/7WLlh5/coKs2QzvfA+CXuBkYIEeePk/oP34Gfs9oKuw7a+w5+nkxCqMitX/OEBXc1/1zFM35at2t7Lj9RNDPCvx3vrzb2g5UQVAV1MjlTu2Yug6QZ+XNY/8lZbqyqTGJwhCaNqGnQOSPgD8AdTn3oyt3Z1vn076ADQV7Z0n0dvqY2oXwFu/ha5df8fQ/KAH+5M+AN3XScs734yp/frDj9NW+zZgoAZ7OLr9x/h6G4Z9niAk0up6D8/X9KIZ4NMM/nq0m70dSTo/jdG+zUE6mnUAfB7Y/m4AXUv9kYbj2bhP/PbXd0d0nKrDkeaeBEcTRsOuMDsMaNwben/j7oSGJCSPrhu01fWG3Nd6xnIPydBcNXRi11yVwkukCMI5TG9qC7nd6IisjwzHaKkJs702pnYBAm2Hh9yvdp0glukq7s6zlrMwdHq7jkXdniDEw5Ge4OBt3YEkRBK7rnZ9wGO/D3wekfgl07hP/C6YkhvRcelWhfklWYkNJpxJF4UuG22y9VXzDLV/8iWDjxfGBVmWKJ6eFXJf6UzX6AZzlrK5C8LukxUTpbPnjl4wgiBETC6fEHK7NCE/tnbLZobYqCCXTIupXQDbhKUMtSSFtWBeTPP8ss5anF1WbGTkiN8wIbmW5Aws6iYDi3LGZiGmvAkDz12dmRL2NDHPL5nG/Ry/9y8tpanbz9Pba0i3mrGaZOo6PPhUnR6fChJMynXyo1vn4bQm6e3Imwa3/RXW/Bh66vtGe2ZPgku/AWl5ff+77a+w5iegemHZJ2DK5cmJVRgVl390Nu89eZj6I50AmMwyM1YUMfeiJM5DBS7/2KdQTCZq9u2moGIquaVlHNrwHha7g5W3f4CM3NhOIgVBSAzlvHkYPR70Hfv7x49LBTmYb4qtL1Fmr8Rwd6BtfR2CfkjPwXTpnUhpWTHHbM2ZRu7F36Zr1z9AVzFllOJr2IahB7HmziTvku/G1H5hxY0EfK00V76E2eqifN6nMFvH5lwqYfw4L8/O52dl8a9qN1ZZ4sOTM5iYNjYLD81aYsbQobFGJz1LYu5yc9yKMgnROWeqegqCIAipT1T1HBnRPwqCIJw7RFXPYbx7uIXfv3uUAw09GAZU5Du5Z+Ukbpg/Abc/yOcf38mBhh6Wlrv46e3zUZK5rEPzQXj6nr6CLshgdYLNBQ4X2F0gm8GRDUvvg6L5yYvzpG1N23jmyDNkWDP48MwPU5RWlOyQxqxDmxqp3NVKb5cPb3cQi10hzWUjLcvK3EtKcBWm/hIe7fV17Hj1BbRggPlXXEtBhVgcWhBSgXasBvWdTdDtBkkCk4I8cQKmy1fGvJaf7nGjvvpnjPpjYHWgLLkSZcHFSKGmL8TI0IJ0H3iaQMsBbEULSZt+Y9xeR1N91B95gt7Oo7gKl1Mw6bq4tDtaTnTtY1Pds1gUG+eX3kGuozQu7W7vPMqLjZto8nfi1QJgGCxxTeMDpReTZU6Lqe32gJcnavbQ4u/lyoIpLM+JT8zjTbNX5elqN10BjauLnSyM07BPTTd4c7/KjmoVTYfyXJnLZ5spyBj3s8AiYmgG2hY3eo0fucyKsjRtXCxHMa7v+L11oIn7/h76ed+5aQ5/XHOcE+2e/m2Lylz8+1Mro44zJpoK3ysEbfCk3kFMNvjEWsidmvi4wtjRvIN7Xr0HzdAAyHfk8+LNL2I32ZMW01i1880TrHv6aNj9VoeJD3x7OY4MS9hjks3T3cVfv/AJfO6+AkmK2cyHvv8LckvFAsjCyIg7fiMzXP+oV9YSfPKV0DtdGVgfeH9Mr+///ZfB3Tlgm3LetZhWxX9ZhNY138F95KX+x5nz7sa19FNxaXv/2q/SVvdO/+PyeZ+idOZH4tJ2otX3HOahzfeiGX3nD05zFv+x8kkc5tiGre7oPMand/0ancHnidPSivn7oi9HPWxPM3Tu3vwvKns7+7f9cO6VrMoTfcaZ/JrBh9c00OTrO9eSgZ+fl8eCOCR/T23xs716YPEVswJfutpGpn3sJzixCrzYjrb5dEE9ZXkalmuzkxhRn1j7yHGd1j+1NXxVsSc2nxiQ9AHsqOlIdEjh7XossqQPQPUlfTmH548935/0ATR7mllfvz6JEY1dB9YPXT7c71E5vrNllKKJztEtG/uTPgAtGOTguneTGJEgCADqniEqY3Z0o7e0R9223lI7KOkD0PaujbrNcAxdxX301QHbeg6/EJe2g4Fu2uoG/l41Vb4Yl7ZHw47G1/qTPoDeYCf7W2L/G7zctDlk0gdw2F3HIXf0lVv3d7cMSPoAXmo4FHV749X2Nl9/0gegA6+Eqfo9UjtP6IO2BTXYW6uFOPrco+3oHfLxWDWuE7/stPB3SHLTrINqhZmTOcwzq2xkxzsjq1aaKC7r4OqS2bbkXwkZi+zpw0/ajuSYZHJkDL6ybE8XRRIEIdkkx9B3BiSbdcj9Qz839BB0yRH9gvDhX0xBtmYM2KTY4lPlWFGsKGeNVjFbs+LS9mhwmrMGb7MM3jZSQw3llJDINEc/BSHTPPhzl2URI4bOlmUZfF6aZYnPAui2MKcVzuh/EsYVySGf9Xh8LDw/rhO/j19YQW6I5M9pkfnCFdO4bcnAComfvHjyaIU2WMVFkDcjsmML58L8OxMbzzA+MPMDlKSdfv+umHgFC/MXJjGiseu8GyowW8P/oBRPz6J8XnIT/eFULFpK2ZzT807zysqZc4moPCsIyWY6bx7YQl8ElefPQEqP/uRdSnchTztrxJEkoay6Neo2w76WJOFa+mmQTv5WKpa4DfOUFSsT536CU0tHyIrt5OOx4bziGylwTup/PC1nOdNzlsfc7h3FFzLBlhNy3/uLL6Qohou9ZY4sbi4+vRRIjsXOh8rmRd3eeDUzy8qlRY7+x4V2hdvKY5tbecr18weX+SjLlphTPD4SnFiZrsw6nSUpYL4yK4nRxM+4nuMH4AtqrD3SwtbqDnTDYEGpiwum5pJx8lLH1qp23jrQzE0LJzC9MGOY1kbBnqfh4EuQVgiOHEjPB2sWmO1gsgAGlK8COflfzKAWZFPjJjItmczNE2sfxcLXG6T+SCdmq0JzVTeZ+Q7MdgWzWaFoSuaYKH9sGAZ1h/ajBYKUzp6LrCT/MyqMPWKO38hE0j8aqoq2/xhGYws47aDpyFPLUYry4hKDVnMY/fBmpKwClJnLkByJ60tVdyP+1kPYCuag2EMnJdHyumvxdB0jI3fBmFvWQdNVjnVsw6LYKc+KXwIV0FW2dR5BN3Q8mp+grjEtrZgpaaHXhRypwz1ttPh7WeyagE0Z9/UGo3ag009XUGdRtg2LEr/zgS6PztaqvuIuk/NlKvKUMXG+MVqMbhW9LoBcbEHKSI3PZ0pX9ZQk6QvAx+hbmW4PcA9QBDwO5ADbgA8bhhFIVAw2s8KELAfXZtgIqDozijJwWhR213biclhwOSxIEgTUwWOdR11HFWRXwGXfguq1ULIEvJ2gWGHfM33DQRd8ICWSPgCzYuaC4guSHca4YHOaqViQh98TpKmqG8MwKJ6SRWutm5YTPRzf2ULJDBcl01N3OK0kSZTMmJ3sMIZlqDqBOjemHBvKEMPBBSGRRrV/VDUMSUL3BcBqRkaCXs/wz4uQUjoNOSsXw92JoZgx6o4g5UwIOxR0pPSgl+79T4MkYy9ahGPihQk5ObWnlWBPi+9aqarmo73zEJnp5VgtiUkmm3urCGoB7Kb0uAzxPJNFNrEie+bwB0ZpWnoO09L7EnhV1znY00KBLY08a/wrWXcG/NR4epmWnok1jhcmG7w+OgMq0zOcyAlKmqZnWjjUFaDNr1HkiN+pe6ZD5rJZoh8MR8owoaRIwhcvCbvjJ0lSMbAWmGUYhleSpCeBl4FrgX8bhvG4JEm/A3YZhvHbodqK9o6fN6Dxkb9uZnPl6cnrTotCTpp1UGEXgBUVOTz2QOzDI6Ly8ldg8x8gzETq0yS4+7m+oaHCuHJkaxOv/2nfkMe4Ch3c+c1lyOOgpHAyBOrdtP5lL7o7CIqE68YpOM8rTHZYwhnOhTt+o9k/agePoz73VuidmWlYP3FXlP+K09QNL6BteL5vYXhJ6vuvyYLp6ntRpsf2p/TUbqb5tc9xZt9oyppE0bW/QbHHZ45forS27+GdzV/CH+hCka0sX/B1ykuuilv7uqHxyJ5vsKd59YDtq8o+wA3TPhe31xkNdd5uPrfjZep9PSiSxP2TlnB3+YK4tf9KfQ0/OrCboKGTZbbwk4XLmJGRFXO7Dx2q4qnqRgygIs3OLxbPwmWN75z8Dr/GFza3UOkOIgG3lafxmZmp/dkXEifVq3qaALskSSbAATQAlwKnSlL+HbgpUS/+9LaaAUkfQG9AC5n0AWw43sb++u5EhRNe4x7Y/HuGT/roO+b5zyY6IiEJ3n10+IpmHY0eKlO8wmcq63q1qi/pA9AMOl86jh4QFcyEpEh4/2gYBuprQ1R37HKjHaqM5SUwuttPJ319L9r3XzWA+vZjGEZso2la3/02Z/eNamcl3fsej6nd0bB9/0P4A10AaLqfrXt/hq6rcWv/YOv6QUkfwHsnHqXJfTxurzMa/lq5g3pfX2VozTD4Y+VW2vzxuSsd0DV+eXgfwZOfxc5ggN8dPRBzu5VuD0+eTPoAjru9PHFi6Crd0XiyqofKk/2WATxV5aayJ8Iq8IJwloQlfoZh1AE/AU7Q16F10Td0pdMwjFO/fLVAcajnS5L0gCRJWyVJ2trSEt2Jbl2nb8TPOdGehHKtXSMsiexuTkwcQlIFfZElIN2t3gRHMn5pnf4Bjw2/huGL34mYIERi1PpHTQOfP/x+QG+M7UKS4e44neydrbcb1NhOUPVA6IuxqrsxpnZHQ6+3acBjf6ATTRv5eUk4nb7w70GnrynsvlTU5HcPeKwZBq2B+CR+vaqK+6zPYZMv9n60yTv4u9UcYlvsrzP43KBJ9FtClBKW+EmS5AJuBCYBEwAncHWkzzcM4w+GYSwxDGNJXl50E9Cvm1uEMoIhcSZZ4uLp+VG9VkzKV4FjBFUbZ70vcbEISVM4ObL5H5MXJeEzOk445g/8LbGUZ6BkiNrVwugarf5RMpmQJg09Z01ZPn/I/cORCsshK3QM8uT5SCHK9o+EveT8kNudFVfE1O5omDhhYGXjCfkrMQ+xRMJIzcxbhVkevFxHuiWHCtfYqrJ9WX7FgMcTHVlMTYtP8R6Xxcoi18C2Li8IeU1lRBZkZ5BtGTis87LC+FfgvuyMqp4A2VaZhdmi3xKik8gZi5cDlYZhtABIkvRv4HwgS5Ik08mrmiVAXaICmFuSyd/uWcpf11VR0+HBYVG4eFo+k/OcPLuzHrMisbu2i5YeP7lpFv549xJs5iQUTrGmwT2vwNqfQ1cN9Lb0/c+SBjYXdFaBv7uvjPXc2+F9vxr9GIWEe9/nF/DiQ7toONqJrMiUzHQR8Ki01bnxe1WsDjOX3zuTjFyx1lG00i8pRbIq+A61Y853kH7pCNfPFIT4GLX+0XzjZahvrkfffwz0M4ZdWi2Yrl6FbI3tBFKSFSy3fxl100voXW3IFhuG34NcMBFl+fUxRg/5l/4vzau/gbd2HRgGpoxiXIs/gaMs9QuLLZj5SayWLBpbNuPKnMacaffEtX2XrZCPL/4N7514lHZvPSBR4CznkvKPYlaGXr8x1dxUPBNFkljdXMkEezofmbggroVS/nfeEv5eeYTj7m6W5eRze1nF8E8ahk1ReGjpLB6urKcjEOTaCXmcnx//uXfnF9j59oIcXq3rJcsi86HJGViTue60MKYlsrjLMuAvwFLAC/wN2ApcCPzrjMnruw3D+M1QbcWynIMgCIIwdpwjxV1E/ygIgiCMWMou52AYxiZJkp4GtgMqsAP4A/AS8LgkSf97ctufExUDwM6aTn755mF21XTS4Qli0LdEqyTB9MJ0nnhgBRn2+FZgisnOx+ClL0GwF5BAMYPJBlOugOt+Ao7ULec/lrT/82G6nn8eU24ueZ99ENvMxJWrHk7N/na2vVaNtztAwK8S8Kg4XVZW3DyFSSm2cPvx7VvY+sK/MQyDxdffzJQly9DUIM/84H+oO3QAW1oaV33ic5TPX5S0GA3DwL2mDs/uFkxZVswT0vAdbEeym8i4vAxrWQqs1ymc00a7fzSCKoEXVsOR6tMbnXbkilJMFy1FcjrCP3nYtgMEn/kVRsMxsKdjuvoelLL4/Z66j75K57bfo/m7MbsqyF35FSw5U+PW/mjo7D7G25u+gMfbjKJYWTTrc0ybdEvcX2dD7b/ZWv8iTksWV1TcT2lG/P4Oe7ur+MWxZ6nqbSTD7OAjZVdwY9GKmNvd393Cnyu30R30c13RNG4qjm9f3B0M8PujB9nX1cECVw4PTJ6BwxT/U98Of5DfHTnBkZ5eFmdn8rEppTHdlWvza/zhUCdHu4MsybVx79RMrHFcv28sMzSD9g0qnmMa5hyZnAtNmDPEHdBIjesF3Ls8Qc7/4Wrc/vCTYGcWpfPK5y6MJbz4adoPvx3ih3TqVfDBJ0cvnnGq85lnafja1/ofK1lZTFn9FrIj+pOfqGNp8vDY/9uEroX+Ht7x9aXklaaPclShtZ6o4h9f/SzGyeFikiTzwe//nLWP/4Oqndv6j5NkhQf//iRmS3LmILjX19P5/LGQ+ySLQuFXl6I4U+hijzDAuXDHL54i6R8Dr6/F2BG6iqFUWoTlA9EPyQw88SOM2sOnN8gKls88hGSOfW0wb91mml4dWMVasmZQeufzyKaxMZRR0wI89eqVaNrAYiLXXvworozJcXudnY1v8Ojeb/Q/tpnS+NoFz2E3xT6nsCvYy00b/wevPnBJyR/MvpeLc6NfLL4n6OeW9Y/Rq50uvPK/cy7j0vzYh2Ge8pWdm1nferrQzVWFxfz3nPhfmPzclv1s7zhdiOjGkny+PCv6f8dnNjaxp+P0+33zxDQ+P0ss4QDQuiZI56bT5/XWfInSj4yN34N4SPXlHJJqw/G2IZM+gIMNPaMUTQT2/mvo/UdeB12Uno+Ve/XANa20zk48O3YkJZYT+9vCJn0A1XvaRjGaoR3fsbU/6QMwDJ3K7VuoOzhw7UFD1zi2dfNoh9fPuz/8e2YENPzHOkcvGEFIAcbB8Es2GDUNGP7o14g3Gs5aNkDX0E/EXiofwHNi8FIUhr8bf/OeuLQ/Gto69w9K+gCOVj8T19fZ3/regMc+1U1lR3z6tW2dRwYlfQDvte6Nqd3tnQ0Dkj6A91qqwxw9cpphsKF1YHXTtS3xr3bqUbUBSV/f63RE3V53QBuQ9AGsbxLVvE/pPTrwPNjfbBDsjm3ZmHPJuE78Juc5hz0mpYZ5Fg5z5Sx7EshJKD4zzljKJw3cIMtYJpYnJZasgqHvMg63fzS5JgyuguaaUIIzc/BVyIJJ8buSPVKmvKGL35jyUuc9FYRRkZMVfl+aEywx9IOOwUOnpbzYKyYCmDNDFV+SMKcPXak0laQ7Q8ea65oT19fJcwx+r3JDbItGmT10JemJjtgqTE90DK5kXRZiW7QUSaLYMfA8sMwZv6qqp9gUmXzrwDvcZY7oi7A5TDLZ1oGn56XORNZiHFssroFDXmUbKA4xDDZS4zrxm1qQzucum0q4YdGyBD+5PfphCnE38wYoWxl6nyUdbhDVPOMh52P3YV/UN9RDsljI/+IXsJTE50RlpEpnZjP7wmJCFS+bdl4BFQujW8okEaYsXsbsiy/vmyArScxcdQlTl63g2ge/jGI+feI4a9UluIomJC3OjEvLMBf3de6SWT6dCCoS6ZeWYika/oKQIIwn5ivPByXERUObFdPVq5BiqJ5ouuY+UE6flMpzVyFnxGductq0G7AVLz+9QZJxnfcZTOlFcWl/NNhtucyb/vEB27IzZ1BefFVcX2dV2Z1UuPr6NUUyc2XFA+Q7J8al7SlpE7i37EokTn9OFmdN4bbiVTG1W+50cd+kRZikvlPRxa4J3FEa34T4KzPm4bL0JWV5VhtfmB7f9gFkSeIrsyvIMPd9DwptFj47I/r33iRL/MecbNLNfe9LkV3hMzPFMM9Tci42Yz6Z/MlWyL/SgmwSiV+kxvUcv1M6PQF6fCpN3T56fEHSbSZa3QEun1mAKRVL4nZUQ82mvjt8ljRQ/ZA/C0yxz5kQTgvU1qJkZKBkJL/Yh6c7gK4ZyIpEb5cPR4YVZ2ZqrtPT29mBYRikuU4XGjIMgxN7d5FdXEp6dnzWXoqV2uZFdpqRbSbUDh+SRRFz+8YAMcdvZCLtHw1dR6ttRD9cjbRgOoosI2WkIcWh0IWh6+g1B5Fyi5Gd8btjc4rqbkL1tmHOKEWxpsac55EKBN00NG/ClTmVjLTELSPT7q3HZkrDYY5/v9YV7KXR10GG2UGRLX6F5rqDPnrVIEX2xPxtg7pOg9fDBLsDk5y4cz6/ptPk81PssKHEYSkKv2bQ7FMpdpjiurTFeGAYBsEOA1O6hGw+t96blK3qmUo6PEH+sb6Stw40k2E3c8vCCRRm2fnikzvRdINPXDSZuSVZyQ7zNNdE6GmAjb8HdDDbwWQHWwZMWAjTru6r9inExFKSGsOFNE2n8XgXakCjfF4ukiRTvaeNoimZZOU7qDnYjqcrwMS5OdjTkp/8O7NcqIEA+959kwPr1qCrGnMvvZIZK1chJbBTHSlTjh2t20/vnlZMOXasFfE/IRWEsUCrrkfdvBt6PWAxI+1VYOXCuCR9AJIso0yc1f9YbziO0VKLPHEmUmZsoxaCPfV4Klej+brQg16CnZVIJjMZs+/EUbJ8+AZShMWcxsTiyxL+Otn2+I228OtB1rbtQ9N12gLdrGvfR7rJzqrcubjMadiU2PqjgK6xtrWanqAf3TAodWSy2DUhpjvQoZhlGYfJxKsNtRQ7HCx0xb9atm4Y7Ozopt0fJNNsIjOW4dMnWRWJ0nFysdLdpdPWqJOZI5OVG/t5giRJWLLPrYQvXsb9Hb+X9zTwqUe2D3vcd26czYdXlEf1GnG35iew+jvh9xcvhnteFXcAxwFN03nmJ9tpquybGG51mPB7+goSSRLklqXTUt3Tv++WLy8me0JyhyoGfF7++Z+fp7Nh4NrSJTNn8/5v/zBJUQ3mr+6m9U97MIJ9k76dy4tw3TQlyVEJwxF3/EZmuP5RXb0RbUuIYihmE+YHP4Rsju+Jpbr+ObQNL/Q9kBVMN34apSK6KRWemvU0v/EfYIQuapY++w5yln8x2lCFIfSqPu7b8XOqPKGLoZTa8/jboi/hjLK6qlcL8sDW5znW2z5g+7WFU/nGrIujajOcvZ3tfH77Rnwni+PdVDyRL8+M7zSf/9p5iPea+wq6pJsUfrtsDhOd0c/zG0/qjqtsfScIJ9ON2eeZmDJ3fCS0ySCqeg7jl28eiei4n0d43KhY+7Oh99dtgyOvjU4sQkJV727rT/qA/qQPwDDoT/pO7dv51olRjS+UQ+vfG5T0AdQe2Ef94YNJiCi0nrdr+pM+gN5NDWjd/iRGJAijywiqaNvCVF4Mqmjrhr8oOrLX86NtefX0Bl07nQRGoWvnX8MmfQA9B/4dddvC0F5v3hY26QOo8bbwevO2sPuHs7q5clDSB/By4xFqPd0hnhG9f1Yd7U/6AJ6rq6bFF78qmYe6e/uTPoAeVePJ6oa4tT/WHdyu9id9AId2quh66t90Gq/GfeLXGwgOfxAQVFOoFKw29BIUAAQ8iY9DSLhgYGTLc6j+5C/nEfSHT56Cft8oRjI04+z31mBAIigI456uw1AnWP7I+seIadrg/isY/cUWXR3m5Fwsb5QwXm34JT4iOSYcnxb+s+fT4/u59GkDPycG4Nfj1xec3T6AVxN9zSln/yToKgMSQWF0jfvE7yMrJg1/EHD7ktSY7wXAnFuG3p9RDNOvGZ1YhISaNC+XNNfpIi7yWSVoHZmnh/NKssTsC5NTffRM01dcgNUxeLhpem4+pbPmJiGi0JwrBlb+s05zYcoRQ2+Ec4dktSBNCVNdUJJQzl8Y39ezOZBnDpx3pyy8NOr2MmbeNuR++xia4zfWXJG/iExT+GkFTsXGFfnRL4R+SX4FWebBw0TnZxYyJS2+BcJuLpnImT3redl5lITow6I1NyudqemnlwlSJIkbS2Jb6mI8mTRrYEXhidOVQec6wugZ93P8AF7b28BP3zhMVWsvJkVi2aQcCjJsbDzehgHcvWIi911QEb+A4+G9n8Gux0D1gWLrm89ny4Ky5XDeA5BekOwIhTjp7fKzf209akBn+vJCWk700FTVTfHULEpmZrN/bT29XX6mLS0gf2LyK5ACdLc2s/6px6jcsQUDmLL4PC784L3Y0uK/RlIs/Mc78e5rw5Rjx7m0AMks1sFMdWKO38gM1z8auo62YSfajv0QCPYt65DrwnzFSuT8+FfgNTQVfd96jNY6pPLZUc/vO8VTu4Geg8+hedvRgx40TwuSbMI55RpyzvtMnKIWQqn3tfFCwya8mp9KTyOH3XVYZRPLXTO5e+LlTLDF9vlp8rl5of4QDb4eZEliSloONxRNx2GK//yvnR1tvNvcQInDyfUTyrCGWt4kBu6gygt1zbT5g1xRlMP0jNTqC5OtoUqjpUEjK1emdLKCJIvEL1qx9pHnROInCIIgjA0i8RsZ0T8KgiCcO8RyDhH45CNbeWXPwEnKq6bksLe+G5Mi8+ClU7g7FSp67n8O3vgmdNVBuDHupcvhnpdBFncuxiM1qPHiQ7uoO9w5YLvJIrPqjqnMuiD5Qz1bqit5/Q8P0VJdSdncBciKwvGtmzAMg4KKKdzytf/BkZHcpRMM3aDrpeP0bm1CdprJvLocx7w8vHtb6XylEr0niGNxPlnXT0YSQ06Ecczw+lBffQ/96AmwmsF7xpw7kwnz/bcjx3B3Qm+qJvj0z8DXO3CH2Yr5zv9Ezi+Nuu0zta79Pu7DL4DRN3fKkjeb3FXfwOKKbDpHMrV27GPz7h/S1VNJccH5LJv/X1gt8Rm9sbryb6w58SiKZOKySfewsvT2uLR7imEY/F/lCzxbvx6fHkQ1NGRkbipawVemRf9aqq7zX3veYF1bX8Gymel5aIZOpaeT5dklfG3mhWSGGAp6rvCqOj/b18G7jV4mOBQ+N8vFwpyx8374fQY73wvQXKeT4ZJYcIGFzJyxObss8Ewb2s5eMEAqtWC9r2BM37Ecm3+FEdha1T4o6QN472gbHZ4gLT1+vvncPnbVdI5+cGfqaYSn74OOqvBJH0DNRnjvp6MWljC6trxUOSjpA1ADOm8/fIiulvhVIouGYRi8+Isf0nj0MFowSOX2LRzbspFTIweajh/ljd8/lNQYoa+Cp3tdPYZfQ2v30f7EIQL1btoeO4jW5sMIaPRuaMC9oT7ZoQpCQqlvb0I/XNVX6MV7VqEVVSX4+MsxtR/89y8GJ30AQX9fQhgHnpoNuA8915/0AQRa9tHyzjfj0n4i6YbGe1u/RkfXIXQ9QE3D2+w88Ou4tH2gdR2vHvstnmAXPYE2nj30E0507YtL26e83LSFh2tW49Z8qCcrrOro/LthHds6oq+G/njNbta2ncCgr87H/p4WDrnbCOgaa1qreejIxvj8A8aovx/t5vV6D37doNKt8s0dbfjHUMGYvRuDNJ7Q0TXobDXYsjrAWBhheDb1gAdtR29/MRqjJkDw5Y6hn5Tixn3i98TWmoiO21qd5D9k3bahE74zHX51+GOEMan24NCfw6bKrlGKJDRvTzft9bVDHlN3aP8oRROev+qscuCagXd3C2gDO55AdXzLhgtCqjFqG4c+oDP63xTDMMDTE/4A7xD7RsBT9U7I7cH2I+jB1K5w7fE04fEOvPjc0r47Lm1Xde4KsS0+bZ+yu7sy7L63Wwe/fqQ2tg3dj+zqCr+UxLlgb+fAizTdQZ1qdwQV31NEe9PAJLW32yCFin5HTDsw+PdFrxqD/5AzjPvE7/bFkVXrXFSWldhAhjNhEcgRjrydckViYxGSpmS6a8j9BZOSW9zFnp6Bq2jo4aZF02aMUjThWc8ugiNL2ObmwlnDOi1l6aMYlSCMPql4mEJgmdH/pkiSBPYhvkP2+BS4cExcFXK72TUZ2ewIuS9VOOz52G15A7bluuJT/Xhi5uDCOROz5sSl7VPmZpSH3XdRbvT/jvOyh+5H5mSc21UxZ2dZBzxOM0mUpY2d2Vmu/IHphTNdwjp2Rqr2U2YM/n2Ry8bgP+QM4z7xO29SDpfPHPwDsnySi3SbiWynhW9eP4uFZUOfcCdcRhHc8gfILAVpiPl7xUvgwv8YvbiEUbXkukkUTR48P04xy1x01zQy85J7kiNJEtd97ivkT5qMJMmUz1/EpEXngdSXUOVNrODKBx5MaowAzmVFOFcUIZlllEwr2XdMw1qcTvad01GyrGCScS4rJG3lhGSHKggJZbpkOfKUsr4HVstZOxXMd10bW/s3fxasIZZJMVkw3/qFmNo+xVF2Ac6p18EZRfnNOTPIu/j/xaX9RJJlE6uWfJ+s9ClIkkJJ4YUsnBWfaqSz8i7gior7sZnScJqzuGHa55mYGd8lda4tWMpdJRdjly0oJ08ZZSTeV7icpa7pUbf7gbL5rMgu7f+LTk/LYbIzG0WSOD+njM9OPbeX6vjIlAwuK3JgkqDMaeJ/FuZiU8bOKfvc5WYKSmQkCTKzJZZcaum7UDTGmGY5kOc5+n96pGIL5uuSnC/ESFT1FARBEFKGqOo5MqJ/FARBOHeIqp7DONTYzX8/u5ftJzrRdAOXw4zNrCBJoMgSLT1+ZEliyUQX37t1LsVZSbyjsu8ZWP3dvqqeJlvfXRRvB0gyKBbQVUgvgut/ClPFcM9Y+A4epPullzDl5pJ5660oSV5/rvZgO9V7+9aVNHSDgFel7lAHfp+Gq8BBbmkaxVNdTFmSnxJXzQxd5+D6NTQdP0rZnPlULFqa7JDCUlu9dL7aV8nTNj8XoyeA/3gX5uI0Mi4uQ8mwDN+IIIxh6tETaG9vhJ5e0DTQT17wLczF/OEbkeXo7yToNYcIrn4UutogbwJMWwLb3gSTGeWSD2KaNCsu/wZf0x46tv4Of9MeMFSU9CLyL/sB1pypMbVr6Br1x/5N64k3MNvzcGZORgv2kFN8IZl58V3gPtECmpct9S/S6WtkXsHllGbMjLnN3V2VPFrzNm7NR5piY29PFZlmJ9+ZcTcVaUUxtV3V28GrjUdJN1kodWTyp8ptuNUAVxVM5qPli7Aq8TtF3d7eyvrWJsqd6VxVVII5hs+8MDx3l07NEQ2TGawOie42HVe+zIRJSkqcwwxFbw8S3NaDccwPGsgz7cg2GaNXR5nrQC4c2+cM4/qO3/76bq5/6L3+Pm44VpPM2q9eSl66dfiD423rX+HFz0d+/O1/h9k3JSqacc2zfQfVH/kIBPuK6dhmzaL86aeQktQRHFjfwOp/HIjo2PmXlXLB7bGd6MTDW3/5HTtfe7H/8UUfvo8l19+cxIhCC7Z4aPrF9kFFXU6RnWYKv7QY2RH/BYOF6Ig7fiMzXP+o7T2M+tK74RuwW7F+9u6oXls7sAn15T8OeYz5/V9BLpkWVfuneE68R/Mboac4lNz5PCZn9PPBDm36Ds1VL4bcN2Pl98grvSzqtkfbb7Y+0F/wRZYU7lvwC6bmnBd1e++27uar+/4Scp8EvLjiO+RYopsnfdTdxse2PkdA10LuX5BZyG8W3xBV22d7raGW7+zb0f/40oIJ/L+5i+PStjBYT6fOu8/50ULUopkyz8Tspanb3+ptQfy/awR/mMRBAeu9BcilScgTToq1jxzXlzz+ubEq4qQPwK/qPLujLnEBDWXdL0Z2/JofJSSMc0HnE4/3J30Avv378W7fnrR49rwzdHWzM+1dU4ee5JLOajDInrcGVpbd8WroE6dk82xrCpv0Aei9Qbx720YxIkEYXdrGYSovev0YWuiT72Hb3rF62GOC7z4VVdtn6t7/dNh9nduGTjyHoqlemqteCru//siTUbc92uq6Dw2o8qkbGhtq/xVTm0/VrQ27zwD+XBV9hfHn6w+GTfoAdnY1UuuJTxXrp2sGViZ9u6metrFYYnKMOHFYC5n0AVTuV1N6WQdtR2/4pA9AA3WLe/QCSoBxnfjZLSNf5NxmTtLC6MoIbx2neCWzVCaFKC0VattoMZkj/xoqJjnpwyQkSUIxD7xiZ7Kk5tAHyTT8eyuN4P0XhDHHHMFwuWh/U8wRXLk3x35lXFLCtyFZou8LJUlGGqKatjzE66Yac4hYTTHGb5WH/vs6TdH3m9YIqpib5ficj1nPakeWJDHUM4GGGqGrKCT9HGZI5ghii+SYFDauP/n3rJyEbQQndS6HmZsWJqnK3xXfGcHBElz+7URFMu5lf+Ru5IzTJczTLroI+9z4lsAeicXXlCMrkf2QLL2uHElO7o+OYjKx7Ob39z+WJJnlt96ZxIjCc55XhGQLf/JgyrNjn5MzihEJwugyrRpmRFB2ZtTD3E3nDay0GYr5kth/GzLnfTj0ckeSQtai+6NuV1aslMwMPcxVki2UzvxI1G2PtnxnOfMLLu9/bFEcXFj2gZja/HDZZZjCVBk3SQofLYu+1sAtxbNwmUNUgz3pqvzJFNjiM/f+7klTMEunP+O3lU4iw5yaFyvHg4nTTdjCXI+ZvjB1h3kCmBalIWUOccHBLmNaPraXgRrXc/wAOj0BHlp9hJd21+PxqywsdaEhYZLBaTGxv6ELWZK5bl4hn7x4alR3CeOm+RC88z1o2AXOQjCZoHFv391AZx74OqBwLlzzI3BNTF6c44Da3o579WqU3FzSVq1CUpL4dwe6WrzUHGjHYlMI+DRkGY7vbMHd4adkpouMHDuFFZnkn70+XRI1HD1E0/FjlM6aS05JabLDCUv3qfSsq0Pr9ONYUoDeGcB3tANLaQbOhfnijl+KEXP8RiaS/tHo7Cbw9iZo7QRNBa8PJAl5/kzMlyyL6fWNrlaCG17AqD+GXD4HafYK9HefAosN5bK7UNLjc2FF7W2ma99T9Fa+iRHoxVa0iNwL/xvF4oy57c7mHbRUv4otrRhHZgUBTzOuohXYnLEVLxltuqFzpH0znb5GZuZeQIY1N+Y2m3wdvNi4iW7VQ6ktj9dbtlNkc/HVqXfgiOGOH0B30MealmrSzVamObP5w/FttAU83FYyi1V55XG9M1Tv9bC5rZlyZzoLXOJiX6IFAwYN1Roms4QjDTpaDFx5Mlm5qd/fGj4d7aAXvdqH4TNQFjmQdAnDraHMsCM5k3u+GGsfOe4TP4CAqlPd1osvqNHjC7L6QDPXz5/AgpNr9zV3+7CaFTLtKXAlQtegegOc2Ahly8GaAXVbYeKKvuGdKZzwGYZBnbuOfEc+lpEOXT3HdTT20lrbQyCg4Uy3UjrTxbEdLWQXp6H6NWRFwuY0k5ET/grpaPB7PLTVVpNZUIQWDJKRO3BhYp/bjRoMkObKTlKEp2m9QdANlHTxWRxLROI3MhElfoaB0diCruvozW0YvgCyDPLC2ShxGqZteHowtCB6exNazUGUqYswFaRuf3W2oL8LQ1cx0FEUOyZLfO42BYJuVNWDw95XgKbX04A/2ENWegVyBMMdh6PqQbr9LbhsRUiShDfYQ1D3xyXpA+gK9qIaGg2+NgKaxiRnIQCuOLw/AV2j0esGdCRJpsiWjinOQzBVXafJ56XQ7kAGGnxecixWrEm+2BupgGbQ5tdIN0t4NYM8W3yL8bt9BpIETmtiRhK5u3V01SA9S076aKWRMDQDo0tDylISHrfhDoAiIUWYg4jlHIax7mgrn3h4Gz2+gTNN/7SuinSrwrKKHN480IxFkfn4RRV86croFySNWe0W+MvVfcs2hJM/Cz78LKQXjFpYkajurubB1Q9S2VVJljWL75z/HS4uvTjZYaW8gE/l8f/dTE9rZBPNi6ZkcsuXk1ONbN0T/2TjM0/CGReLimfM4sb/+G/saem89+jf2Pris+iaypSly7nus19J2ty/zueP4d5YDwbY5+WRfcd0pAiH0wrCeKK3dxL8+zMQGNiv6ID+zlb0pXMxXxr9YtmGYaC+9Qj6rncGbNc2vYRmT8P6qV9E3fZoOb7zV9QffhzDOFlsRDJRNvseJs7+WEzt7j38N/Yc/jO6HqAgdwnBYC/tXX0VnM0mJ5cs/yV52dEvuH6odQOP7/s2vcFOch2lTHEtZUv9C2hGkJm5q/jQ3P/FrER/V+6hY8/zWO3b6Ay+QXBD4XK+Nu0OZCm6RO29lmr+Z//beLTThdZcZhs/mHclczPjc36zp7Odb+7ZRovfR47FikWWafB5yTCb+drMBazKL4zL6yTKhmYv39/dTldQR6KvoM7iHCv/uygXRwTz14eiGwZPbwmy84SGJMHSSQo3LjTH7S6rt9dg/St+3F19nx2zBVZcbcWVl/p3/LRKH4GnWsGtI2UpWO7KQy6K/7mMoekEnzuAvr8ZZAllSTHmKxNftT31/wIxMAyD/3h616Ck75Qev8abB5oBCGg6D60+yt66+FSRisrT9w6d9AE074d3vj868YzAT7b8hMquvspZnf5OvrX+WwT14DDPEra9UhVx0gfQcLSLw1uaEhhRaF3NTWz89xMDkj6AuoP72fzsUzQcPcTm555GP1nK6+iWjex9+41RjxPAd7QD9/r6vjNbA7y7WvDsak5KLIKQbOqL7wxK+s6kb9kTU5U9vWrvoKSvn9dNcMfbUbc9GrpadlF36JHTSR+AoXJi7x/p7TwWfbs9Vew6+Ft0PQBAU+vW/qQPIKj2smHH/4u6fd3QeOrAd+kNdgLQ6qlhY92/0Yy+fvdA63tsrHsm6vZ3d1XySO3qkEkfwAuNG1nTtjeqtoO6xvcPrhmQ9AF0BH388OB7UbUZyo8O7KblZPXOtoCfBp8XgO5gkB8e2EVQT26F7KGousGP9vQlfUD/X2Fbm5+nqnpibn93jcaOExoGfct6bjqucbgpfu/Hwe3B/qQPIBiAnWv9cWs/kYLPt4P75PveqRF8sT0hr6PtaepL+gB0A21zLXp1R0Je60zjOvHzBjXqO0dWsvdYSxLLtHY3RHZc6+HExhGF413HBzxu97XT5U9iEj1GNJ8Y+Q94w9HO+AcyjPb68EtOtNfV0FZbM2h7W92JRIYUltrkGbytefA2QTgXGJ3dwx8UiP4indFWP+R+vWpP1G2PBk93Zfh9PVVRt9vtrh72GLcn8qV8zuZT3XT7W4Y8prm3Kur2Kz2Nwx5T1RvdRciuoJ/OYOhzs2pPZ1RthmyrN3z/2hkM0BlI3USkJ6jTHgidiFW5h7lBEIGWnsEJfUt3/KZ+9XQObsvdGbfmE8bQDIy2s0ZHtCTmJobR2jtom96a+HOVcZ34OSwmVlREPonXZpZZOTk+4+KjMnFlZMdNuyqxcUThwpILBzyelTOLXHsS38sxYvqykQ81mXNhcQIiGVrx9JmYwlRBq1h0HhPnLRi0xMPkRdEvHBwL6/RsOGtMvm1G8uccCkIyyBXDFF6SJSRr9MOY5ElzYYjhfqYV74u67dHgKlyGFGLZAtlkJys/+mH1+TkLMZmGXmqiKH9F1O07zJlMzJw3YJt8VgXOmbkXRN3+MtcMzGEqegLISKzMmRlV27lWB9PTQ58frMwpi6rNkG3lhh8yOi09gzxbcufMD8VlVZiRGfp7uTI/9uWnphcqA+rxyhJMK4xfSlBYNritghDbUo2kSMhTBr6/yvTEfE6UqWflJ7KEXJH4c5VxX9ylpcfPN57dw7uHW/AHBw5auGVhMUsnZfPY5hOkWU187rKpLBtBohh3vm74x41QH2YxcXs2LL0fLv4qxGl9m3jxa35+vePXrK1by1TXVL64+IsUOlN7/HyqWPevI+x6qwbjjIt7kjRwVKUkgcVuYukNk5h/SXIqaNYfPsjLv/4p7rYWFLMZpyuHuZdcwZIbbkGSJE7s3c3Gfz9OwOtlwZXXMueS6Et9x8p7qJ2ed2pANUg7fwKOBflJi0UYGVHcZWSG6x8NVUN97i304zVw9tA2SUK5+yZMhbFdpNOO7ULb+CJGSy2cMXxPmncRlis+HFPbo6GjcTM1B/6Kz9036saeXkrZ7PvIzFsQU7st7XvYc+iP+AOdVJTdgKb52X/0H2ha35y/FQv/G6slM+r2u/wtvHzk19T3HGZazjKm5azg3ep/4lPdLCu+iWXFN8UU/5aOw/y1+nWO9NbhVn2AgVOxUe4o5ENll3Jx7rxh2win0efmF4fXs62jnqChYZXNXJBbxuemLifDHJ91dbuDAX575AB7uzqYk5mFVVHY3t7GpLR0Pjl1JoXh1hxIEc1eld8f6mJfpx8DSDPJXFvi5Nby+CwnsLtGZe0RFUWWuHCaiZkT4ndeaegG+7epVB9UMQwoKJGZf74Fc4KKyMST0asRfL0TvS6AXG7FfEUWkjUxSau2pxF1Sy2YFEznT0SZPHziJ6p6CoIgCOOGSPxGRvSPgiAI5w5R1TMCrT1+Pv7Pbeyq7UTV+xJdh0UmL91KU5cfv6pjMcl858bZ3LE0fsMMRqS3FZ74CNRsgDMnmZ8imyB7MhTNh5UPQlH0V9pidaj9EH/b9ze2Nm2lN9BLcXox37vge0x1Jb4aUay0nh7a/vAHfIcOYS4oQG3vQMnMJOe+e7FOnpyUmPyeINteraa5uofeDh9drd6Bd/9kCZvTxNQlBay4eTKmZK41edKBde+y/smH8Xs8WGx2NFXFVTSBC+68mwnTZiQ7PEEQzhB8awP69v2D7/gV5WO9+8bY2t75Nvo7T/StD9hPgjQXpkvfjzI19irEqqeVrl1/R+2px5o/F7WnDt3fTdq063GUrYq5/e7WvRze/B287hokSSav7AqmL/tWzO2ecvzES1Q3vIVZcWKgYegaU8pvYkIMQz0BDrSu492qh+n0NZLtKCHTmoc70E6FayEXln0QJQ7LRTxe+w4P16zGq/mRkNAMnYmOAr4980OUO+JXXfxAdwtP1OxBNXRuLZ7NQlfqr6Ho0zQeqaznQJebBdkZ3DmxKO7LUSRSTbvOuiMqrW4dXTfQDIksu8SyySZmxXj3r7db58huFb/XICtXpqfDAAkqZpvIzh8775HRqxF8rRPtuA/JIWO6NBPTjNS+Uzycc+KO34rvv0VDV2RFXl79/CpmFCZhkexfLYL2CCuIWdLhwW1JWdKhzdvG9c9cjzs4sAiOVbGy4a4NmJUUWAtxCCc+dj+9a9cO2q64XEx+43WUtPis3TQSz/9yBzUHIqvkNHVpPlfeNyfBEQ2tevdOnv7uN0Luk00mPvrT3+AqnDDKUQnjhbjjNzLD9Y/BjbvQ390cvoGyIqx3XR/Va2u1h1Gf+NGQx5hu/AzKlAVRtQ991bnrn/kQwY7Q/WPB1b/EXhz9IvQ+dz1bX74dwxhY0KGw4kamLv2vqNs95Wj182za9d0QeySuOP+35OcsjKrdY+3b+P32T0OYqpvnl97BjdO/FFXbp7zZvJNvHPhbyH122cobF3wP0xDzACPV6HPzgY1P4TtZ1dwkyfx16c1MTkvtudnf2n2E1Y1t/Y9vLSvk8zPKkxfQCHT06vz8dT/BEPcZAD56gYXphdH9bTXV4M2nfPhC1CmRFbj0FivOjLGR/Pl+14BRP7C4i+Wj+SgV8RmOHI1Y+8ix8c7HoKXHH3HSB/C7d6Iv3xy19uORJ30AgR44/Gri4hnCmto1g5I+6Jvjt65+XRIiipza0REy6QPQOjroXTv68XvdgYiTPoCjW5sx9ORerNn7TvhlGnRV5cim9aMYjSAIQ9F37B/6gJrhqzeGo20Zvh/SD26Kun2AYMexsEkfQO/xN2Nqv7XunUFJH0BLzeqY2j2lqu61MHsMquuij31n0xuES/oAdjSGe93IPVn3bth9Xt3P3u7hK5dG4r2Wqv6kD0A1dN5uDl9tNRWous67TW0Dtr3Z0JqkaEZuX70eNukD2FUzxM5htDXqIZM+AF2Dhuro2x5NentwUNIHoO0ZXI1zLBn3iV+6zXR2gb8hTSsY/Ts+2LOBEU54zRj9yo4ABc7wdxlL0kpGMZKRk51O5Izwd3PNhaN/B9VsVbDYIx+OY8+wII3kA50AGXlDF0pJzxHVXAUhZaQNMyzJFP0dGylr+KJJUpor6vYBFHs2DHFXSXHGVrjJag/9fLM1+qIrZ3LYwsfnCPPakciyDv3czGH2R6LQOvTfLj+GwjQD2rE5B23Lsw7elkoUSSLbMrDqZp4t/ot8J0qmfejziOH2D8XmHPq59mH2pwrJoUCInx4pY2zPkhv3iZ/NrHDvBZMiOtZpUbj3gooERxSCPQsu+2bkx8+6ESZfmrBwhrKiaAVXl189aPsFxRcwxTUlCRFFTrZYKPjqV5FOLTtwxlj8zFtvwb5gwajHZDIrnH/bFGRl+B9CSYaL7po+ClENbfF1N5GWHbr6bdmc+Uxbfv4oRyQIQjjm6y7qKwschnL9xVG3bbrgZhiqAmOaC2XJlVG3D32JX9bij/cvGSGZTpdWN7smkzHr9pjazym5mIzc+YO2T13y9ZjaPWXutHtx2AdXuM7OnM7U8luibndF6a0UpQ2cVy+dvIBsVRxcP+1zUbd9yhen3IJTCf33vSR3PhPs8amCfn7ORC7Indj/eGFWEVcXpvb5hCRJfHbGRCwnL8Q6FIVPT5s4zLNSx6wJMtPDLN9QkCFx/tTok5sMl0zF7NMZk3JG8pRfIlNUnvw6BZGQbDLmK7MGbswxYVqWhBtEcXROzPEDqGx189yOOrq8QTJtZia47EwvyKCu08Or+xpZUZHDXcuS/KXtroeNvwUkaD4M7oa+Yi5dNTDvDnBNBLsL8qNbOyeejnUeo83bxtHOo8zLm8ec3OTOOxsJtbUV//Hj2ObMIXDkCHJ6BtaKyC4OJIqnO0BnUy/2DCtHtjTS2x1AxsDv1SianIHVaaFsVg42Z2rMoTR0ncpd2/G5e8guLqGjvo6ckjLyy5Nw4UQYV8Qcv5GJpH80dB1tyx60hhbo6OpbsL0oH9PVq1Assf+mqHvXoh3YDGYLUn4Zkq4hlc5AKZ2OFKdiF6q7CdXdgDVvNqq7Ac3fjTVvFtIQawiORE/bflpqV2Myp1E87U4UU/zm8Oi6SmvHXpz2QlTNR1DtJSdrFtIQCXkkDMOgpnsfPf42smyFZNkKaew9RnH6dGym+N0xe7VpK0FdI8vspMbbwpKsqUxLj/8In2PudlRDD7vGXyrqCgQ57vYyLcOB0zT27gQ1dOoEdQPt5OhLRZYoyZaQY/xsQl+BF7/XwJUn09VuIEmQmTP27jcZ3SpapR8pU0GeaI35exsrUdUzAv/aVsMTW06gG31XaVZNzSXdZuKht49QkG7l2nlFrJqSl+wwIb0IkGHnI6DYYcbV0LQHOmrh5a9CwUy45BuQZwx5BTfRgnqQZk8zWdYsPjDzAwBousa2pm3YTXbm5s1NWmyRMOXmovv8eDZvxrFoEcoQwz9Hg64bHNvRTFttD51NXpzZVvLL0qk92IHNaSarMA0tqCfzTz6IJMu429vwuXuw2h0UVEwle0Jyhh8PRQ9o+Cu7kO0mdI+KuciJ7lXp3diAKddG2ooJSMrY64gEIVK6phF8eQ3UNYBfBZ+/b7Xm/Gxkrw9iTPx0TzdGcw2yqwCpoAzJ6sDQglB/DCO3GMkZ+++r6mnDfew19KAPb/02JLMDCbDkTENSYh9e11rzNp6eakpnfhRFsdLVsh2z1UWaa1rMbQPIson8nAVxaetMkiRRlnn6omtDzxE0PYApxIL00ar2NLO2dS8H3bWkmex8fvJNCUn6/JpKi7+XAlv87qZsb2/lpfoTFNudrMwrYEZGVtzaPiXTYmZhduIuyKq6wQs1biTg+tI0THGe6lGU1df/1XdoHGvRKcqUGfHUozCcGTKnvv4Bn0ZHi4HVDjZH7H2ur0FHDxjYS+WETH8xggZ6la8v2cu3YJo/ftKlcX/H78Ifvc2J9jCzTM+QYTPxxMdXMLMoSUmA6ofvl4AWGP7YooVw32tgsiY+rrO0elv5yCsf4UTPCQCunXQtX1/+dT766kc50nEEgItKLuJXl/4KOU5XYuOt/ZFHaPru90DXkZ1OSn//OxxLknODwdcb4J9f30DAN/xkZ7NN4fpPz2fC1KzEBzYENRDgD5/6KN6e7gHbl996F+ff8cEkRTVYsLGXlj/uRu8dXLjhFMksU/iVpSjpY2duxngn7viNzFD9o97rIfjrR4Z8vnzpcsxLo7tYpx3Zjvr8b4Y4QsL0vk+iTF0UVfsA7uNv0vr2fxOqkImkWJhw65OY0wcPpYzUtlfuwtN9/FSLmG3ZBH19RTsKyq9j2rIRTMNIoqf3f4/N9c8B4LIV8cklvyfLFtu89T9XvcofqwcX8Lk4Zx4/mHNvTG2f6YSnk89sf4nWQN+52p2lc/ns1OUxtfmVnZtY39o8YNvF+UX877yx89PS7tf4wLsNeLWTy5ApEo9eVITLGt+hkk9v9bOt6vRSL0VZEp+42IrFFJ+Eat3LPlobTn9/l1xiprgiukTKMAwanw3Qe7QvXkuuRPGdVpQY5iSeTW8P4v9zM/T0nZcpy9OwXJs6FWZFVc8hbKpsiyjpA+j2qfzyzSMJjmgIa38eWdIH0LAD9j+X2HjCeOTAI/1JH8DLlS/z6x2/7k/6AN6tfZd1dalZ4VP3+Wj52c/717PSe3tp/sUvkhbPhmePR5T0AQR9GhufS0LV2bNs/Nfjg5I+gM3PPklvZ+QVShOt+60TQyZ9AEZQp/Ol1K4eJwjRCr74zrDH6G9vwggO/T0JR33r0WGOMFBXPxZV26e0b/wZ4apXGlqA9g0/jrrttvq1ZyR9AEZ/0gfQVPUS7o5DUbc/WhrcR/uTPoAOXwNrqodO+IcT0FX+Uv16yH3vtO3GrXpjav9M/6ja1Z/0ATxRs4cGb0/U7XX6/YOSPoB3mhvY0TF2Km/+/lBnf9IH4NEMfn+oM66v0dilD0j6ABo6DXaeiE/lzZ5OfUDSB7Bn4+BKmZHyVuv9SR9AoNWga1d0v1/hqO919yd9ANpGN3pb9DGnmnGd+NW0RZb0ndLW609QJBFoPT78MWfqbUlMHMNo97UP2tbU2xTRcalA93rReweW4tXakhdrb+fIPnPenuT/+PS0h+44dU3D5x681EeyaO7ILqRoPUn83gtCIvVEUHbcMPrm/EUjGMFSSYHIl1MKxQgM/ZuieaO/2ORz1w97TNCXOhezwnH7B/dh7kBscQf0IBp62P1uNba/65k6ggOTSAPoiOSzFUanGv63vyMQ4QX2FNAS4qJwqz++SyG4faEvqrj98RkN6HUPbkeL4TRG84RoL8S2WBi9gz/3obaNVeM68btxYfGIlnK4dVESlyO4bAQLxcoWmPm+xMUyhOsrrh8whDPfkc89c+7BJJ++bZ9lzeLi0ouTEN3wTC4XaRdfPGBb5k03JSUWgEVXlo3o+Bkroh/SFC9L33dryO2FU6aRU1I6ytGE51wU2TCnjAtTb26iIMSDctF5wx9UVoTktA9/XAjytOFHG8nTFkfV9imOSZcPuT9j7l1Rt11Y8T4kKfyQM6ujiMz86IepjpZJroVk2yf0P5aQWFx0bUxtppnszHCGPifKMDkotMW2TMeZri0cWJ10ktPFjBgKvJQ700kLUWjFZbawPCf2ZS5Gy52T0gdvK4/vdKTyPJnMs77+igzzSuIznDSvWMZ01hTIwonRt+2oUJDPjFeG9FnxnX9nWjCwMJKUa0IuGT/TQcb9HL8D9V3c/ZfNtJxx9d8qQ7rdTIdXRQam5qfxyUumcMP8CeEbGg37noN/3Qv6ELet8+fCLb+DwuRV0dzUsIlnjz5LljWLD8/6MBPSJrCzeSdPHX4Ku8nOh2Z+iPLM8qTFNxy9t5f2f/wD36HDpK26gMxbbklqlaYjW5vY+Owxutt8YPRVLVdMMlpQx5AgK99BdqGTiXNzmLmyKOkVpQCOb9/Mmkf+hrenm/ScPMrnL2TxdTdhT09uoZyzeXa34N3Tiu7XkBQJc5GTQL2bQGUXksVE5rWTcC4cOycC5wIxx29khusfA+u3Y6zd3ndn72wzJ2O5ehVSDAVegm88jH5gA2ga2NPAkQ5+T98c6ulLMF/8/qjbBjB0lY6tv6P32GvoATeGpCBJMoo1g8x5HyJ9xk0xte/uOMSRLd8n6O8gv/xaMvPm01T1CmZrFiXTP4DVMfrru0aj09fEeycepyfQxuLCa5ieuyLmNn1agK/v+zvrO/b1D7YtteXyp0VfINMc33X21rRU8WbTcQpsTu4qm0u2ZZj1J4fR6vPxlV2bqertwSRJnJ9bwMcmz6DYkdrrA57tjbpe/nGsGwP46JQMLp8Q//i7PAav7Q1S3aaTkyZx1Rwzxa743Rfq7dbZviaAxw1FZTLzVsaWRAU6dLq2qegByJinYI9Tknom7aAHbY8HKUPBtDIDKT11lqCItY8c94mfIAiCMHaIxG9kRP8oCIJw7hDLOQxB0w2u+Nm7HG8dfp6DBHzz+pnck4wF3AFe+jJs+WNkxzpy4ePvQmYSh6aOMbrfT8O3vkXPq69haBpKZiay1Ur6lVeS/4XPI1mSdxu/5UQP6/51lPZ6N1pQJ+DX+iY5SGAyy6S5rOg6mC0KC68oZfryoqTF2hdvFe/+8890NtYz5byVXPD+D7Hl+X+z/73VOLOyWfWBj1I8PflrTZ5i6Abdb1Tj2d2CKdOK87xCerc3o7Z6sc/MJvOaSUim5I16V1WVN954g0OHDpGTk8NVV11Ffr64CynER2DtNox120PvlMB0720oudEN2zMMA23tM2g73oJgiLmyheVYP/iNqNo+m7duE23rf4LaXQcYWHKmUXDNr1Gsg4fDjVTtwUeoOfgPVH8XYCDLFoqm3sak+Q/GvE6gYeis3/4/VNW9DuiAQl72XJbO/RKuzNiWi/CpvTy857841r4NRTYxMXMunb4m7OZ0rqx4gGk5y2Jqf23bPn557FkafG3ohtE32sQwcJrs3Ft2FXeWXhRT+6esaz3BXyq349WC3FIyi9tKZsfc5va2Fr68azOBk4XcJjnT8Gkak9Iy+Oy02ZTEeOdvU2snfz5ag0fTuLGkgNsnJqZf/ldVD8+ecNPs0whoBk6TxOdnu2K+87fuiMrm4yoWE1w+y8z0ovjf0Wpt0DiwTcXvMyibqjBtfmqsQzwcw60ReLkD/agXdJDyzZivdqGUjX4l/UQY13f8vvbv3Ty2uWZEz3nrSxcxOS9+68hEpGot/O26kT0nvQi+dDAx8YxDTT/+Me1//kvIfbmf+hR5n31wlCPqowV1/v719Xi7I59wfutXF1M4KTOBUYWnaxp/evBj9LSdLi5UvmAJVTtPfz+tDicP/OavWOyxDdWJl573auk6s3KnxIAigekXl5J5dfloh9XvjTfeYN2601VwXS4XDz74IHKcFr4ea8Qdv5EZcjmH2kaCj7wwdAOKjPXL90X12truNahv/GPIY6T3fQbL1AVRtX+K6mml9ombQR9YFcKSN5sJ7/tzTG23nHiDgxtCJ6cVC79E8bQ7Ymp//9GH2bH/oUHb7bY8brr8WWQ5+uvvj+75Bjub3gi5zyRb+Nr5z5JuzYmq7XpvG7dv+S6aEb6oxc/mPMDKnFlRtX9Kg7eH9298EvWM1/nxvCs5P3di1G32qkGueefVsKVpKpzp/GPFxVG33+zzc+d7Owmecf783fnTuLAgviX/1zZ5+fr2wcXUJOCFy4tJN0fXR+yr03h4w+lzDkWCL19jJSsO6+udEvAZvP6ED+2MmUsLLzRTNjX17zf5/9mMfuSs4kI2CduXipGsye+XxXIOQ3htX+OIn7PuaBJK/e6IouxyT0P84xjH3O+uCb9v7dpRjGSg1jr3iJI+gJr9yatC2lZXMyDpA2g4MvAChN/TS/2R1CmB7jt8VnW7s651+Y4kt2rfsWMDl+jo6OigvT01q+IKY4t+vHb4gzSdaC8A69X7hj3GWPNUVG2fydewY1DSBxBoOxxz2x2NG8Pu6xxiX6RqGt4Oud3ra6GzJ7bleQ63bw67T9UDHOsIc6c3Ats6jwyZ9AFs7Ij94vO2jvoBSR/AxrYIPrdD2NfVMUQ9Ujje20OLL/rlKLa3dw9I+gA2t3VG3V44W1pDVzY1gPXNI6taf6YjTQMrg2oGHGuOb9XKtiZ9QNIH0Fw7Nipj6sdCvO8+A7127FSEHcq4TvxmRbEYe1IWcJ90wcifYxnlu5JjnG1m+KGHtunTRzGSgbLy7ZhGeNUupzh5f/vM/AIsdvugbWeSFSWlqnuai4Z+v8yFyZ3sX1Aw8P2z2WxkZibnjq4wvkj5kd2BiLZglJQbwXSDGRFUFh2GJXtKyO2KM/Yh0c6sqUPsC/26I5GTFXrYokmxk+6IraJwgXPSkPuL0qOPf0ra8MXupjhjL4g3JW3wZ3RKWnR3KU+Z5Bx6+G+OxYrLEv2wvSnpg0ezTE6L/wiXyenhh0bOyYo+/qLMweccRVnxTQcyXIN/UzKzk1+YLhJSQYj3XQY5L/XvVkZiXCd+//fBxZhHsJ7DJTNyWVoe31v1EVnwQcgJ3/kMJsPtf0tUNONS/pe/jKXijPmbJ4fR2ZcsJu9zn01SVGB1mLnk7hnYnOF/4GVFQpL7/jv34hImzY++zHWsLDY7V33y89gz+hKT4hmzuf7zX6Vi0VKgb5jnZfd+kvTs5MV4toxLSrFOzQJAsptwrpyAnNb3flsmZpB5VXnyggMuv/xySkr6TqCdTic33XQTZvPYmAshpDZ5+iSYMHRVSvnKlVG3ryy5Eql0iAtnZivW82+Muv1TLK5JuM57EM5YekEyOci/9Hsxt100+RZySy4dtD09Zy4lM++Ouf15Mx4g3TnwQpjZlMbyBd/AbI7tIt4ds75JuuV0kpRmdiEhYVHsXDf1wWETw6HMTC/jgfJrMIWZ43hp7nyuLVwadfunzMjI4/5Ji7HKCjISVxdO4bqi2OY+5tnsfKxi4OfScrLPz7Xa+PrsBZhiGEo/Jd3Jx6eWYpNlZOCKwhyuL4n/vOxrS5xcMcHBmWexEnBLWRrFQ5wzDGfJJIUFZQoSYFbgytkmJsQ58XNmyMxZbu5fyqFoosyk2WMjcbLcmIPkOiNWC5hvyEbKGBvxD2dcz/E75UBdF7vrOrh6dhE7a7pQZCjPTSOgaWyraifdbubCafk4LEn+o/a2wp5nQFZgwkJo2Q+lKyCrBGq2AAaYbFAqpr9EK9jSAoaByeVCc7sxueK3FlEsNFUn6NNQzDIBr4qm6iCBxWbCZJHRtb7vqcWWGj88mqri9/TiyDh9Z8rr7sFstWFK0aRF6w0iWxUkk4yh6eg+DSWGzjPeent7sdlsKErqlI1OBjHHb2Qi6R8Nf4DAvsOQ7gR/EFQVzBYssybHZXkYw9eL7vdgeN1ItjTU6v1IxVOw5MZ3jUxd9aH7utFVL5as6OeAhaIGetBUP6rai9mSicWWFdf2e72t+AMd2K05WC0ZMc3tO1u7twGryYHTnIk32INJNmNWbHFp26cFcKteDMAim/BqftJMdtJM0a39GP51VFRDJ80Uv0JrAV1jb0c7E9PSyLHa6Qj4STeZY0r6zuTTNIK6Qbo5sf2yO6hjkqHVq5FtU3DEqRiZL2ggS2AxJe5OnKYaaBpYrGPjbt8phmFAr44hGUhWBSmB79FIiaqew+j1q+xp6OaxzbV856WDaLqBWZFwOSy09QZQNYOyHDvpNgvnT0nyXQrFCrsfh/rtMGCEukz/Am+Fc+F9v4Ki+UkKMjR3wM0zR55hTe0a7CY7H5z1QZYVxVZRLB60nh7a/vQnApVVZN58E+mXXNK/L1WSPoC6Qx3seacWd5cfi82ExSbjdasoikxGrg1XoYNJ8/OwFKbGV1bXNap2bqNy5zY8XV1MXnIe6Tm5dLc0U7H4PFyFyV0TU+sO4N3TAkpfkqd1BZBtCrapfX9zf2UXlpJ0lIrUGVLpdI6t9aWEsUFr60B9bjW0nDVvVJYIVtdhuTa2yox6dzvBN/8JDcfBmdW3jl9zNUZmHtqtn0dxxD59QvW207n1t2jeDvSgF9VdhyVvDjnnPYgpLbZ19jw9J2ivX4vVUYiu+VEDPeSWXjL8E0fAMAw6uw/S3VPNhIKV2G3xG1mkGzoNPYdp89YhSyZ2Nr6GVXFy7bRPU5we2zSGem8ba9r2YJXNnPA28XLjVjTD4PbiVXx8UmwLxAN0BX281XSMI+526r3dtPq9KJLENUVTub1kTkwJmqrrvNfSRJvfx4STv62xDO88W6+q8nZjO5phcGlhTkKSv7pelXXNXgrtCucX2Gnwaqxt9rI018bkjNgTZJtZotdvsKNaRZFhbqmCNU4JTneHxpFdKrIiMX2hKSGJn2EYeI7rBNp1nJMULLnxu2spSRJ6t4Z23AcFJqgOoDcFUJamYZoW32G9+olO9Lpu5LJM5OLEn5OM6zt+3oDGDb9ey9Fmd0THf/3aGdx/4eQRv05caCr8bz4Y2vDHAtz1OEy/JrExRcgdcHPb87dR11s3YPtXl36VD836UJKiAq27m2NXXY3Wcbp4R879HyP/S19KWkyhbH+tmg3PDD/JX1Ykrvv0PMpmxTb/IVaaqvLoN75Ec2XomBWzmdu+/h1KZs4Z5cj6BFs8NP/fLgyfOuyxGVeVk3FJ6sxHFMQdv5EasqpnSzvBv/xr6AZcGVgfiG6Rdb27jeAfvzrkMebPPIRsjf7ukObvpubR60EPVVhBZsLNf8eSPZKpEqd1NG5m33tfwNAH/laYzOnMv/zPODLic1dx487vcezEcwBIksJF5/2E4oLoh9ie6dG932Rn42sh99274OfMyI3udfZ2V/HpXf+HP0RRHYCFmRX8dkH00yRa/R7u3fIMrYHQRUpmp+fzx6XRDxP+wvYNbGnvK9ZnVxT+b/H5TMuIz0l1r6rysY17qfX0FQHJt1n48/K5ZFniN4Jkd7ufL21pJnDyHkCJw0Stp+9zKgP/vSCHS4tiS0B6fAa/ftNH98laJnnpEp+5zBrzHcCmWpWNr53+3EgSXHyTlYzs+A4nbX4tQPfuk+fMMhTdZME5OT4jZtSdboLPtA8qBgdguiwT80Xx+Syp66tRVx8/3fbV0zAtGXqkhKjqOYRX9zVEnPQBPLT6aAKjGcbm30ee9AG8+f8SF8sIvVb12qCkD+B3u36XhGhO63755QFJH0D73/+BoQ6fEIym7a9VR3ScrhnseP1EgqMZXtWubWGTPgAtGGTri8+OXkBn6d3QEFHSB9DzTk3UFQ0FIdUF31g3/EEd3RjqCPqeM2hrnxn2GPWdJ6Nq+5TO7X8Kk/QB6HTvfSLqtmsPPTwo6QNQgz00HH066nbP5PW1cfzE6SU1DEPjwNF/xqXtdm992KQP4JWj/xd124/Xvhs26QPY0XWcQIj3LlIvNRwKm/QB7Otp5mB3S9j9QznQ1dmf9AF4NY2nao4P8YyRebuxvT/pA2j2BXitIb4V4Z+s6ulP+oD+pA/6xoM9erw75tfYVqX2J30ALT0G++qi+y0408FtAz8XhgGHd8X3vEvtNejec0asOnRsjt9rqGu6QyZ9AOq62N976Ltjqa4feE6nrovsfDAW4zrx00dYOVZP5gmgFv4HNqSRJIkJpocpnKwPUwo60Qxt8Htk6Hrfr1AKMfTI40mFJCWSeA09eZ/PEb1HBmF/3AVhzIv4tyXKL0Ekv/Gx9lXDvIYRS/tD/FYYceu/DIyz3t949Y3D/dbF8m+IJMaz/10ja3/45+pRth/qefE8v0t0+5G0N4LThrBCvUSi2k3IucvZTcbzJUbrvODsN3wUzvHGdeJ31ZxCyrIjvxV+/6qK4Q9KlOWfYkR/jku+lrBQRurKiVeSZ88btP2jsz86+sGcIePaa5HTB5Z1dt15J1KKFR+Zd1lkQw0lCeZfVpbgaIZXvmAxOSXh45AVhUXXxF7JL1ppy4qQLJF9l9IumIA0gsq/gjCWmC9fMfxB6U4kU3Tzk5SVw3/PTRdFN4z0lKwF90LYQigSGbOjb7942vv75s6fRTbZKZp8S9Ttnsluy6W8+Mr+xxIyMyffFZe2cxzFzM4LP0fziooHom779uILMUnhh83NTCvFKkffl15bNI1Mc/g5d5Od2czKiK5S5qyMLOZlnZ5HaZFlbimNvsLp2S4pyCHfdnqOXbbFzJVF8a0RcVt5OsoZXVO+beDf4o7yoZesiMSiiSacZ0wVdDkl5hTHPlRy+sKzvq8STJ0X3/Muk1MifdbAWLMWx2+epen88HOTTefF/t5D3zxCZdnA8z/TssRPPRnXc/wAOj0B/rWtloc3VlPX6UU3QJEhzarQ49PQDYO8dBv/ff1Mrp2b3IIUuJvhL1dD+3FCX26QwFUO7/t1dGv/JVCHr4PHDjzGmrqTxV1mfpDLJ16e7LBQ29tpeeghAlXVZN74PrJuuinZIYV0ZEsTe96txdMdwGxV+qp7+vqKu6S5rGQXOZmyuIC8svj84MTK7/Fw4L23ObptEz53D+ULFuEqmEBXcxNTz1tB3sT4dbLRUNu8eHa39GXLmoHa5Ue2ytim950M+I93YSnLwD4jCcu3CEMSc/xGZrj+UatrRn3hLegKMe2hohTLbVfFVNlTb2sg+NpfoLUebE6w2qGzGZwulFs/h8kVW/EVgGB3PR1bHjpZ3KUXzdOKOXsKOSu+HHN1T3fHIdrq3sNqz0PTA2jBXvLKrsCeFr+KpLqucqJhNd091RQXXkBOVvh1ZUdK01V2Nb1Bq6cW3dDY1/IOFsXBdVM/Q4VrUUxtH+9t4O2WXZhlE8fdDbzbtgcdg6vyFvO16e+PuSJsi7+XVxqOcLinlXpvD51BL4okc0XBZD5SvhCrEv2JvF/TeKOxjla/j0sLJlDmjO/6t52BIK83tKIZBlcW5ZJjjV810lOO9QR4r9FLocPEJYV2Nrb4ONYTZGmujbmu+BSq6fYa7DyhosgSCycqOCzxuRDa1qhxZLeKrMCMRSYyXPGvVm3oBu5DGoF2A2eFgq0ovveytCof+nEf5JnQq/wYLSqmxWmY5se3EJt2tA29tgu5LAulYvhzklj7yIQlfpIkTQfOHHxfAXwT+MfJ7eVAFXCHYRgdZz//TLEu59DtCVDd6iHTacJhUch2Wmno9KHqOiZZItNuxmkzx6WsdUx0vS/5M5nB0wVBL/h6IH8atFeDNQ3MVnAl/67PKUEtiCzJKHLql6A3NA00DckS/x/oeAh4VXRDx2RW0II6wYCKbhjISDgybcgpcGdK1zXUgB+TxYosK6jBIGrAD4AWVLHYbWiajs0R/8Vso6X7VDBJSEggS+IOX4o7VxK/ePWRkfSPqteH5naD2wtmMxggpzkwu2KvuAmgeT0YhorW2QaZLuhoA2c6Vld81jYzDB10FSSlb+joybt0UpyWRDAMHTXgxmR2YhgashL/PsIwdHRdRToZezyXcwhqvv7lG3RD6+tHYrgbdyaP5sevBekK9pImW/HoAYoduShh1vcbKb+mYpb71pSr93QzwZGR0HMxn6ZiiyGhHG26YRDUQTN0NEPCaZKQk32uOgKGYaAGDUymsdX3GoYBqgFIYALDpyNZ5ZT4N6Tscg6GYRwCFgBIkqQAdcAzwH8CbxmG8QNJkv7z5OOhy4JFyRNQWfG9t+iKoNCDzSTz548uTd6SDlv/Ci9+PvLj738XihckKpphabrG9zZ9j2eOPoPNZOPTCz7NB2d+MGnxDKfjiSdp+dnP0Hp7ybzxfRR9+9spM+SzvaGXZ3+2HW/P0PM8F1xRxvm3ThmlqAbb/soLrHn4z2iqiqQoZBcV01YbuthMRl4BH/7hr7AlcYkCrSdA8292onX4+7fJDhMZV5eTdl5R0uISBBidPlLXNIK/fhh8g4uj6IAfMN13G0pudEvb6GqQ4J/+E3q7Qu73A+b7f4CcEX2/6j76Cu2bfoXu6+wb8qmrfXfyZQuZcz+Aa3H0wxkBag78g6o9vztjLqJEfvm1TF3yNWQlPn1EVd3rbNv7c3z+DiRJRpIUpk+6g4WzPhNTklPVuYsn93+HVk8Nk7IWMi1nGWuqHyWgeVg84Tpunv4VlCgTzI6Am0/u/BVV3uaQ++8svojPT7k56th71QDf2f8O77VWY5VN+M4oFPP+4jl8bnoEw5RH4ESvm2/v3c7hni4mp2XwrTkLqUiLz4WPRFnT6OFn+zroOKPKi1mGr87J5ori1F/+58ThILvWq+gnr9XMOc9ExezUOO8ainbcR+CZNug6a/6wDKarXJhXpMbIq2iN1hy/y4BjhmFUAzcCfz+5/e/ATYl60a8/syeipA/Ap+p86uGtBNQkFCTxtI8s6QP4W3KXcnju2HM8efhJgnqQnkAPP9j8A452JLEq6hAC1dU0fvvbaF1doKp0/evfdDwRW6W5eHrtj3uGTfoAdr5xgp5237DHJUJbXQ1v/+33aCcrohqaFjbpA+huaeLlh348WuGF1P7EoQFJH4DuUel85ihqmzdJUQlCSAnpI9WX3gmZ9A045p/PRds86st/Cpv0nRL8e/QVqFVPK63vfRfd1wEYoAf7/mvooPno2vkXvHWbom4/6O+kavdvzipAY9Bc9VLcqnr6/B1s2PH/8PnbAQPD0ND1AAeOPUxt45qo29UNjUf3fpNWTw0AlZ07eO3Y7/Cq3WiGyua659hS/3zU7f/k6NNhkz6Ax+ve5ai7Pur2/1a1gzWt1RgwIOkDeKJuLx51hAXvhvGDA7s43NP3WT3m7uZ7+3fGtf14cwd1vru7fUDSBxDU4ft72ukOpE6Bv1B8HoMda/uSPuj7yu7ZqOLuSm7Rv+EYmkHg6dbBSR+ADuorHRjdqVUZfqRGK/G7E3js5P8vMAyj4eT/bwRCTgCQJOkBSZK2SpK0taUlupK+G4+3D3/QGbp8GnWdSTghbN4/8ucEw5dBHg37WvcN3tY2eFsq8O3fP6hSkm/v3iRFM1hHQ+R/y9aangRGEl7z8ZEn9a3VVfEPZASCDWGWcjEgUB/5Mi+CMApG1EdG2j8aNY3Dv3Ig+hNsoyGCEvlDlOwf9qntR/ru8A3B33ow6vbd7YcIV76vp/1A1O2eqbP7KHqYZRHaOqN/jd5AJ52+of++td3Rvzf7uocvK3/QXRN1+wd7hl7+oLJ3yBlAI3+97s4Bjw91D33BItmq3EF8WujPpmZApTu1k4/udj3kV6uzNcUTv24N3EPHqDfG96LEaEt44idJkgV4H/DU2fuMvgmGIT/ZhmH8wTCMJYZhLMnLG1wxMhLXzCkc0fH5aZYRVQGNm6L5ISuLDcmWlZBQIrW0aOmAx4qksLhgcZKiGZp90aK+eS1ncCxblqRoBsufFPlwk8KK+CwaOlLFM2ePeEjShBmzEhRNZCyTwrxXioR1YnLeR0E4WzR9ZKT9ozS1fPgA7LYRRHtW+xVzhz/ImRV1+9a8WUimoeOzFUXf76Tnzg7b92blx6c/y86aiUkJfV5RmBv9a6RZssl3lp+1deBv9OTs6Ntf5po+7DELMydH3f6irKGH209Nz4m67ZCv5xo43HihK77tx9uUDDPp5tCfTYsMUzNSe8hkVp486KslSZBTmNr1IKRMBWmoQjQSyCWpWSciUqNxx+8aYLthGE0nHzdJklQEcPK/4ccSxOhr185kUk5kiVxBupW/3HMeSjImblrT4a4nIdLJ2LIFPrkhsTEN4+ryq3lw4YPkO/KpyKzgRxf+iJL0kqTGFI65oICSX/4C69QpmPLzyf3Up8i8KXnLDZzt6vvnkj1hmM+pBBfeNR17enJ+cDJy87nhC1/DnpGJJEnY0tIpn78ISQ79E1I4dTrXfvqLoxzlQNm3TcNyqgqqBJJFxlTgIOeDM1EyxvYPtzCuJKyPtFx5PriGuMghSZjvuy3a5jFf/mHIG6r8uIzlo9EP9VSsmeRf9kMs2dOQLGnItiwksxPJkoaSNoGc8/8TW/6cqNs3mdOYft63UUx986UkyYTJ4qJ01j0UVLwv6nbPZDGncdF5P8aVOR2zyYnZlIbDVsjiOV+kMG/p8A2EIUkSH577fSpci3CYM1lQeBXvn/1NCpyTyLTmcUXF/SwsvCrq9j8/5WaWZk0Lu/8/ptxKsT36uZsfmjif20pmkWW2UWQ9XXFTAr48bSWWOBeM+89Z87kgt4AMs5kVOfl8ffbCuLYfbzZF5nuLcpmSbh5wop5plvnh4lwcptRejc1ilVh2hRmr7dRjWHKJGbsz+cVRhiLJEpa78pBKLX1VUCTg1EfRJmG+IwfJkdrJ63ASvpyDJEmPA68ZhvHXk49/DLSdMXE92zCMrwzVRqxVPQVBEISx4Vyp6nlKrH2k6B8FQRDOHSlb1RNAkiQncAXw8TM2/wB4UpKk+4Bq4I5ExrD2SAuffHgbPf7BEzVlCfSTeW9RhoW/3rOMGUVJqvK0+nuw5oeRHXvLX2DerYmNJwxVV/np1p+ypnYNDrODXFsuXf4u2nxtmGUz01zTcJgdzMyZyR3T7sAcp6po0dADAToffwLfoYM4V64k87rrkhbLUA6sr+e9J48Q9Gt9V5d0QALFLGFoBrY0C1fcO5uS6dFV3os3X6+bHa+8wJEtG+hubkIxmymsmEJaTi4zV11CyYzZyQ4R76F2Op8/huYOIFv7fuYkq0L6BcWkLSvCf7wLz85m5HQLaSsnoDhTe9iMMD6NRh/pf2s9bA0z/9qkYPr4XShp9qjbD9YdQ3/8+6c32ByY3v9VlNz4rYN3Suu6H+M+8gLoGibXFAou+x7mjNhep7nqVWoO/gND71vGIejvxNCC2DImMnXpf+LMiH5NUk3zc6jyKU7Uryao9mKzZjNxwuVMmXhjXJZzqO7aw9b6l+j0NeHXPLR769ANjZL0mVw26R4mZkUwFHcIh3tq+dzu39Kh9vZvs2Hh/oqr+WDppTG1rRsGLzYcYkdHAz5NJd1kYVKai1pvN5lmG7cWzyLHGtvUmyM9XTxWfYw9ne2ouo5FVrDIMhcWFHF3+VSsSux3bt5ubGNTWydmSWZ/Vw+6AR+ZXMzFBfEZSurXdH6xt4O1LT7STBIPTM/ikqLYpyTphsHm4yrbqjQUGVZMMTG/NL4pQXuTRs1RDYtNwmyGE0c0zBaYu9JCVk7sdywDbTpdu/rmOmYuMGHJjt9dUL1LJfhsO3p7EKwy9GpgkjCdn4E5Tgu4J8u4XsD9eIubS3/6bsTHS8Cub19Jhm2UTwKPvQP/HOHQw/tXQ/Hoz6n7+BsfZ339+oiOva7iOn6w6gcJjii8ui99me6XXup/nP8fXybnvvuSFk8olbtbePk3eyI69sPfXUFGTvQnaPHyyNe/SOPRwyH3SZLMbd/4X8rmzBvlqE7z1/TQ8n87w+53LC/Cs6mhf+aUKd9BwecXpcT6PMK5d8cvVkP1j8Ht+9DfGP732vrV+6N6bV0NEvzlJ0Pus9z/Q6SM+M2jann7W/Qef23gRtnCxI+8jRTlsMDm6tc4tPGbYfdLsokVN7+FMsw8w3De2/I1TjSsHrR9ysQbWTb/v6Jq85Sqzt38btsn0I1w1R0lPrXk95RnzY+q/RpvC7dv/m7Y/Z+ruIm7Si+Oqm2AXx7ZwBM14YusTbCl89jy2zFH+betdPdw3+Y1BPTQhTpW5hbwowXnRdX2KU9VN/CrQ6GL4Pxo4XRW5MV+sfYT65s40DWwMu835sW+nMNLu4KsPTKwQMx1881cMDU+yV9rg8b6VwJn19UD+ub6Xf1BKxZr9IlasFun5q9+9JNvjWyFsntsmNJj78cNw8D33VoIhM6PTFdnYV6ZvKVAYu0jU3uQcIx+/kbok9NwDODRTcNXsoq7f39s5M9549txD2M4QS3IhvrI5xa+WvkqniRVH9XcbrpfeWXAts4nB9VOSLpNz0VQFe+kLS9WJjCSyDRXHQ+b9EHfIsV73359FCMarGd1+GUmALzbmwaUy1CbPQSquhMclSCMPv2dzREdpzUNXWEx7PM2vBB+38HIXjtSvVWDEyj0AO6jrwzeHqHagw8Pud/QVRqO/Tuqtv2BLk40vB1y3/ETL6GFqfQZqS31LwyR9AEYbKkP//cZzsuNQ//9Hq0N/W+L1Av1h4bcX+/rYWtH9MtFvN5YGzbpA1jf2kRHwB92fySerw0//faflXUxtQ3QGdAGJX0AT1XFXt178/HBVUG3VMavUuiJI1rIpA/6iqwf2xvbchTuA1p/0geg+8F9KD5LXOiHvGGTPgB1Y3Kqq8fLuE78ctNGXsAhL82agEiGEU2FzvTRX4BakRVMIxieYjPZRnR8PElmM7Jt4FVaOSP1Fmu1jmCIYZorCZ/Ns9icaX2X64ZgdaYNuT/RZMfQnzkpRKW04Z4jCGOSJcI+MNrKnkPc0ZNs8a2QLSmh/y0mR/QFRhTz8L9VFlt0dy0V2YqihP7NNpudyFJswwzt5uGHm9lN0Q9JyzANfUfJEebfFqk00/CfzfQIjgnf/tB9q1mSscZYQCbNHP75GabY+xSLLBGqt82wxH7qHmpgm938/9k77/A4qqsPv1O2S7vqXbLce8XdVIPpxRACJIFQAvmSQAoJCUkICQmkQCAJECAFCCl0CL13G3Dvvcu2bPW+2jrl+0O2saytM7uScfZ9Hh4e79w5czQ7O/eee+/5ndTterHE+epsJjcvifa+vorGBYp7kxX7uRBMrFQeDXy+vY/DTaePQkriOXbbZeZPHgBlymsMrJDM+2Xq/YiDKIhcOz7x1cnrJ12PNUpnnW5Em42Cb3/70L8Fq5XC73w7xhkDw9zLRyXUTrKITDmjOr3OJIC7sIiJ886OetyVk8tx58zvP4ci4D5rMMhRfvgCeM4bipj1Wa/nnFSIpcTctpkMGY5GpIsTUHW0W5HcxiZrLBNPinzAakccldqSObnTbujzmeSuxFEx07DNoVO+jxAjALM5iymsOt2QbVm2M35EpNQCgYmjvoGQbAmnIzi+8lI8tuilPLIt+cyputSw/fNKZ+ASowd3N4/4omHbAN8YOg3xiLDm8H+dVFjNOE/EMs8JcW5ZFRWO6O/1KwcPx2kyOPva0EqsEVIEZEHghlGDTNkGcMoiFw7q/duUBLh2RI5p22dOsPS635IAp41J3QTo0LEy0VI0bXYYPNrctbJHS1iLPvsLbMUCWSNTo7YpVdgQSqJMHAhgOTsnJdcZKI7pHD+AsKLys5fW8/G2ZjRNp6EriFUUGFfhJqTotHiDCILAxcdV8J1TRyAOVJ5PyA8PzYaOvfRo7mgcWsfOrgBfC6h+KJ0M17wOloHL9drUsomXd7zMYM9gHLIDf9jPXu9eREROrDiRRn8jI/NGMsQzZMB8PEhwxw4CmzfjnDYNS1HRQLsTkWBA4aPHN9O010tOsQNvawAlpDFofB51O7ooHeJm9kXDEKWjZ56mfvtW9m/bwv6tm7A5XQw5bjpaOMygiZOx2gc+D1ELaXR+uIdwfTeWEhd6SEWQRLJPKEfKsqIFFQJb25HcVmyDjr6V4P9lMjl+yRGvf1R8PtR/vQQd3t4HRAEmj8V22izTPgSf/SPs2QCSBaaehXX2OYbz7mJep30nrZ/+CS3cSfbIC3GPMl+WJxzsZN+WxxElO5I1m2B3PeFQB9l5oykdemHS9UuPpL1zJ3WNi1C1MFaLm5LCqbizqkz7DRBSA2xtWYyiBgnrYeq6thFUfYzIm87owhOwSuaWQBRN5Z973uHp2o/QdA2PxcXwrHJ+NOKL5FnNvzf3+zvZ0NmEQ5IJqgrjPcVs6mrCY7EzKU6dv0QIaxqLmhvZ0NFKWNPItdrwqwpzi8sYlp2aWq6twRCr2jqpdNpZ2txBSNO4rLrUdFB5OOvagrxQ00WJQ+ayIdm4ran5bbV2a6yvVZElGF8hkx1hFc0MSlincZ+GzQ5ZHoHt61XsDhgyVjb9uwLQNR1fjQYCOAeJKc/TV9Z40faFoMyCvieEYBGRT3AjxlkRTDdHtarn0YBFlphSmcueFh+D8pxouk5Y03DJMtlOGZsssnJ3O6ePLRm4oA/A6oATboKPfguyC+weCPuheQv4m8FVAJoKI84Gg4nmqWJ0/mhG549G1VQ2tmzEr/g5Z+g5uCwuajpqKMkqoTwr9YpuRrANHYqlvJzg9h1I2dmIjs+CksDWrUg5OQMeENrsMjPnD6V+Zwf+zhC5JQ5a9vsIh1Tyy12UDPWw6IXtlI3IZfCE6DO8/YGvswNvawvFQ4ahKGFyy8qonjDl0Eu8vb4OH+3klPT/VuTDEa0iOadXE9zdieZXsI/MRRAEtJBKYGc7WreCXGjHWjKw21Ij0djYiN1ux30Ubk3O8PlDdjpRRw2GLbvBKkOnF1QNrBLixPhFuhNBGjsLtbsD1DBsXUKobgfyjDORqkanxD5A155P6Vz9T+ScKpz5J+AafHJK7GpqEJurDAQJd+5owp52RMlOdu7IlAxOLbITTdPRtDAFueNpaduI3ZaP1WJ+l4FVsjOu6ORen4XVAA3du+iVyGyQkBbGIsrcM+7rvNWwHJ8WZGRWJTu768mxZCGaXLXMkmyENAVFVWkL+alyejip0LiK6pFYRJETi0oY4XYTVFVUXWd3t5dqV+pUGfNsVk4t6dlunCXLqLqesqAvrGosbPBjlwS+MSqHIkdqh+x5LpETR/Z8hx0+nYZOjWJ3aiaYVUXH26FTVCEiywLhkE75YAl3npCS3xX01NxzDekJwnRdJ9igIWcLSM7U2JdGOBELrWiqhuCUEQfbEVK4HVbvCKCHVcSC/t1xdEyv+PlDKuNvexMlen5vL8aVu3n12yckfR3TqArcUQJ6EsneN24Ez8AFV7s7d3PNW9fQ6OtJbpYFmeG5w9nUugmA84acxx3H32G6YzBL95Kl7PvOd1A7OhDdbsr/+AfsY8aw99rrCGzYAJJE/rXXUnTj9wbEP13Xee+fm9iyuD6h9jaXzLX3nJhmryKz8o2XWfCfR1EVBVGS0NSeRGq7K4uv/v7PfPDY39i2tEdBcPiM2Zz73ZsRUyCXbQRd1Wi4dyVKox/oKeWQM38o7f/djh7+7IVgrcqm8LoJEfP++hu/38/jjz9ObW0tgiAwc+ZMzjjDeAHmzyuZFb/kiNU/aopK+J5HYxsoK8R2xXxD19aCfsIPfA+iiYw4srFefTuCw9wEy+7/nIUebOvzed7sm3GPvtCw3V1rHqB2878iHrPYC5hwyoM43ca37H2y8jZqaiOJzwjMmnwrQypTW2JoV9sq/rn2ZnzhDuxyFl8ZdwcjC4yt6L5St5hfb30q6nGP7OJfx91Esd2YcuVze9fzh219xeLGu4v461TzK7kHuXPjGl7dv6dXGGwRRP583GzG5qSmRJKm69yxfgfv1PWIJM0qyOGOSSOwisb7lbWtAW5c2oRymOMXD8ri22NSX9bp5dUhFm9X0YHqfJGrjrdiMxHgNO1XWfZeiHCoJ9everTEzg0qqgJ2J8w83YYnBeUcDhLu0Nj/bIhwmw4SFJxsIWeKuSBZWdNN+OVWCB/2Bchg/WoRUrX5xZfwa5tRV9UBIFbnYLl0AkKMnNHDyah6xuCW/65NOOgDWL+vk+YucypPhvjkvuSCPoBnvpoeXxLkz6v+fCjoA1B05VDQB/DKzlf4ZN8nA+FaLxruuAO1owMArbOThl/dTutj/+wJ+gBUlZa//pXgzsTVNVNJ7Za2hIM+gGC3wpo4qpXpwNfZcSjoAw4FfdBT1+/lP/zmUNAHsG3Jp73+3d94F9cdCvoA9KBK2xFBH0BoTxfdKxv6272ILFmyhNraWqBnQmDRokXU1yf+bGTIcCThFxPIH9/fhNEJYOXtf0YP+gD8XSgrzKn8Blu3Rwz6AFoX3Y0W8kY8Fg9NDcdU9QwHmqlZ96Ah2wANzSujBH0AOsvX3WPYdjRe2vIHfOGe/i6geHlhy+8N27p7+3Mxj3co3fyl5rWYbWLx5x2RVUPXdTaytKXWsN3DWdnazCtHBH0AYV3j1xtXp+QaAIua2w8FfZH+bYTfrWvrFfQBPLfby5YIKp9m2NuqsehA0AdQ06KxOILiZzKsXRQmfMDNcAi2re0J+gACPtiwzJyi7ZG0fqL0BH0AKrR8GEb1G1/U0hWd8OttvYM+AAVCL7aY8LQHtabtUNAHoNW0o66ui3FGajmmA79N9clLrm5vGgCZ1r2Jl0g4RFtNyt1Ihtqu+C/mWm9qXt5mCNX29iG0bx/hvXv7tAvXDoyvnU3++I2OoGFX/z+j3taWQ0FfJDqbm/p81t4wcEFLuL47woeRZ4GU1kCavUmMtra+g9tIn2XIkDANCQ5S1CRmSA9Db4k/WNFbzU2sBBqiFJ8H0FVUf6shu0q4E4j9dwe8xssJeH2x5fzDSvLv/ni0+ntfs81fh6Yb+25DWvzB/x5f3/d+IiiaRkiLPmGwqcuY3SPZ749eTqo1lLr3fp2vr606v7lFhPZQ5Puz35e6kgvQk+fX9zNzOwF9XUecr8c5bpJwe297ugqKmWv4tZ7/ItFpvmSE3t73edHbUv8+iMYxHfh9e+7wpM+ZOcS4NLRhTr0t+XOmGqj9l0LmVc+Ledwm2TipIoriWz/iPv30I/49j+wjts9JeXk4pw7MzrJB4wqQ5OR+hlPPrk6PMzEorKomtzT61uJxJ5+GKH22tUKUZIZNNa62Z5asmX1zDOXiyBJjjrGpKzJthjFjxvT6t91uZ/Dg1OW7ZPjfQ5g3J7F2srEt2dLU+IqX0mhz6p7Zw8+MekzMrsDiMSaUYrXnI9tyYrYpqJxryDZAWdEsYsko5LqHGbYdjfHFvf0dV3Sy4XSLcnv8sdDZxdMM2ZZFkUpH5BxmAZhflprc0JkFRdijiAzNLjCuGNrHVmFuL3VPSYATivJM2Zya33c7oUuCqQWp1XgYViRhO+IxHVduLkWjrLr3+VZ77ONmOVLN05InYC00vlVVyJYQqyIr2oqjzZepkYbmwRHbOqVR/affcEzn+AH87IW1/GdJ3xWeIxEFeOLamcwcOkCDwLduhUX3JdZ26KlwhbGisqlC0zX+uf6fPLnlSUJqiBPKT2BO+Rxe3PEiFtHC1WOvZkrxlAH1EUDz+2l+8CF8K1bgmDSJwuu/hehy0f7ii3S8+BJyXh4F3/wGtuHJTxKkivqdHSx4agvNtV5iTc4KIsw8fwhTzqzuN98Op7OpkU+ffYKOxnocnhz2b96ApqqMn3sGJ3z5SnavW83K118CYMrZFzBo/KQB8fMg3uX1dL69GxQNx5QiPPMG0fFGDb61TeghFdFtJeecITjHDsBkTxTWrVvHypUrcTqdnHDCCZSUlAy0S/1OJscvOeL1j8GnX4Wa6Ctz0tUXIRcZ7/dC7z2OvjpyMW/ppEuQEwgO49Gx9VXaFt7R6zNLwSiKT7sL2WVcnMvv3cfGhTfh66oBXUeUnYiijCQ7KB16IRWjv2qq7EJz23o+XvYzugM9918QZERRJj9nDCdPvweLJbW1DsNqgHd3PcqutlVUesYxb8jXsMvG8ivDqsIVK3/PHl8j2hFLNnbBwlcHzeOaQca/245QgJvWvsmWrmYUXUcA3BYbt4w6ieMLzZdCOMiGjjYer9lOg99HUyhASNOYlV/ELWMnI5vIwTuSNW2dPFVTR1jTuLiqhJmF5nLxVF3nV6tbWNQYAHRGeazcMDqXEZ7Ul8ja16bx4eYwgTBMHyIzvsJcYKaEdbasUmht1MgrEqkeJbF9vUJna4/Yy/AJckrFFHVdp2OlineriiVHIG+2jMVj7rvVvSrhDzrQdgbQvSoIII1yYjkvNyWaANq+DpRP90BYRTquHGlk4oGf2T7ymA/8MmTIkCHD54dM4Jccmf4xQ4YMGf53yJRziMONT63ihdWJ7dO/4ZSh3HRGYgW1U85bP4dF9ybW1l0O31kNcv8XR1c0hT+u+COv7HgFURCZUzaHPV172N25mwJHAadUncKGlg2gwxVjrmBOeWJbjdLqc1MTDXfehXfhQvRgECkvj/xrv0bel7880K4BsHdzK6/cvzqmRoIoCZSNyOGMr43DnhWlsGia0TWN1+79PVsWL+x9QBCQLVbyK6sQBJHiwUOYfcnlON2pqZNkBKXFT8tTm1Ea/D3CFQfz+yTgwH2WCx0Uf28KwlFUH7G9vZ0PPviA1tZWRo8ezcyZMxFTOCud4X+P4HufwvLoeXKWb34Z0W1MTlzXdZR3/4O29qPIDcpHYLvsR4ZsA2hKgNpnvoDmj5SrKOKZch25k682bB9A11S2Lf8tjbvfQj9QO1cQZMpGXMaQSd82ZXtfwyesWP9HvL56dL0nN0uWHVSWnMTE0d/E5TC33VDRQry781G2ty2j2DWY5u697PduxW0r5LJxv6TSbXzLZFhTuG/HSzy//+M+K34AI5ylPHbcD029n/62fRn/3LO6j3URgZtGzGJ+xVjDtgECqsJNq5awtr0VjZ7cJqsoMT2/gO+MGEeJIzUrroqm88+de3m1tglV15lTlMv1IwaRZTE3xH6ztpvXa714FZ2wphNQdfKsEudXuTin0rhSrq7rfLxN4ZNtCmEVhheLnDvJSpYt9SXN6veorF8awu8FUYTCcpHxM604XOav1b5SwbtZRXYL5M2Rseamtq9U1nWjfNyJ3qUiuGUsx7uRxqV2lX4gOKZX/P67opbvP7smqXP+cfU0ThnZz3Xdgl74bZKlGfKHwbdXpMefGPxpxZ94ZP0jCbWVBZlnznuG4bkDt40SoOayL+FfvbrP56W/+y058+f3uz+Ho4RU/vqdKIOmCBRWZnPJLcbyKsyy8InHWPpSbKW3g1SOncAlP/9Nmj2KjK7p1P16CVp3fOUwudRJyXeP6wev4qPrOg888ADNzZ+pwc2bN485cwZ+8qQ/yaz4JUes/lHt8qI8+GRcG7abrzN0bWXJa6gfvxCzjTj+RCynG1Oh3vv0RahxBFZKznkIe8lkQ/YBdqz6A/u3Ph3x2Jjj7ya/3FiJp/bOnbz24ZeJVk8vJ3sY55zyuCHbB3lx8918WvtsxGOyYOW2k9/GKjkiHo/Hn7a/wFP7YvdNM3JHcu+Ebxqy/079dn6xMfIW4YM8NeMSqlzGJxC/t/xTlrdHFjiqdmXx75knp6Sm3N+27eHfu3o/pycV5XHHpBGGbS6o93HrqujiTL+YlM/cUmNByKIdCi+v6t0/VucL/N8pqc0fbG/W+OilviI3nnyBk+ebu1bHaoWmdz77G2SPwKBrbSkr4q5u9xP6V1+RIetVRUhDBraWdqacQwz+smBH0uf869Oa1DsSjw8NSC63JP+3pYI3d72ZcFtFV/hgb+wXe7oJNzZGDPoAut55t3+diUDd9o6k2jft7SIUSK2qV6Js+Oi9hNvu3bCWQLcxmXWzhOu6Ewr6AJT66Kpv/U1TU1OvoA9g06ZNUVpnyBAf5Z3ESuroEVQJE0HdEL9ki7ZlmSHbQNygD6BjfeSgLVGa90R/r+3d9Jhhu7UNC4hVRL29azudXnOledY3fRj1mKKH2NW22rDtd5tWxW2zom27Yfsv7Iv/bnth/0bD9gFWRgn6AGq6vdSkqI/6qKGvsuzCxlY0EwsrCxpiqzwuMNF3bdjXd3tRTYtOdzC1C0F1uyNvY+po0fF5janNHsS7tbdtpUMnWJ86/9WNke+/uvHoGTMY5ZgO/EaXRFaNisXY8uTPMc2wU5M/R46sOJRuqtzJKahVZRtTXEsVUk4Oojvyd2qtrOxnb/riLkxu5shil5CtA1MU3VOcuNCI05OD1W5sptksUo6tRxouAQTr0fMKzM7ORpZ7bw3KyzOnDJfhf5yhCb7jbMbSBoTcBLYqZuUYst1zgfhb5az5xldVAGyuvgrAB3HlGk/9yHZWxDwuSw4cNnO/73xH7J1CeXGOx6LCEV9swmNCnGZoVvy/fXS2OeEtd4x0GKsoUmBLzcpNmbOvnRKHDdHEamK5M/azX+4yvo00P8I2S6cV7CnOInG5I//9sgVsdnMrc5acI84XQY5yPSMIeZHvrxjl888TR8+oJw38+qLxyEks+2bZZL55UuolluMy9ER6ko+S4PwH0uJKPH407Ud4rJ9tvbBJvQPQPPtnL/N5g+Zx2qDT+s23SIhWKyU//zmCtXcHYB06lPzrBrYkBoCn0EnlmJyE2goCnPyVkSlVw0qGs2/4AaIU/zm1Ohyc9rVvJdQ2HUguC+55ianC5V4yMs3eJI7D4eDMM888FPzl5+dzyimnDLBXGT7P2CaOgXg5rMeNNZznajn1chBjD4TkC43nyeWf9MuYx0VbDjkTjW0jPcjwaT9DlPpOpEqWbIZO+p5hu5WlJ1NaGLmkjSDIHDfu+1gsxvO0AM4b8T2yrT3BkSzaEA6b8ZpWeh6FLuMTr98fdiEOMfaEwJ3jvmbY/rVDjsMlRo80Cq1O5hWbG4/dNmFKxDlASRD4zoixZFtSE+l8a0QVudbPfgd2SeSmMeZK8Vxcnc3YnMj3f5THyiXV2YZtzx1tIe+w4E8SYf4UK1KKxxYVQySKKnq/WwQRJsyyIMnmrpU3y4K14IANCfJPlJGzUue/PC0Lsbr3e0EcbEOaau43ezRwTOf4HeSZZbt5ZlktgwuctHSH0HWdFl8ImyiSZZdw2KxcclwFJ49KXV0XQ6x6El67CaxZUDIWwj5Qw2B1giMfwn4oGgmn3grSwAh8QI/Ay9qmtYiCyITCCTT6Gtnv3U++I59B7kHs8+5D13UqsmPPePYnqtdLcOtWtGAQOS8f+0hzs8Sppq3By8q39tDV6qew0o23NUDT3i5yihyMmlmKKIlUjM7Dah/Y2SZd09j4yUfs3bAOlyeH/MoqlGCQvPIKiqqH0F5fR05J6YCt9h2O5gsT3NWBVOwkvKcLrCJyro1wox+1PUj2CRWISdZQ7A/8fj+dnZ0UFhb+Twq7ZHL8kiOR/jG4fjssWApd3Z99WJiH5UvnIDrMrXrouo66Yw3qpqWgBHsUHDpbYeRUbNPPMmUbQFdDtCx9CNHqQs4uRleChLsacJZPx1mRmnxnXVNpq1+MEvahhDqwOUvJT5EwWWd3LV3ePahKiGC4g7ycUWS7yrBajA/cD0fVFBq6d5LvqEAQBLa0LKEyexQ5DvOlYBRNZU3HTt5tXIVFkGgOddAUbGd23jiuHHRaSt5PS1v28mFTDbmynVJ7Fus6mzi7ZDgT86KvxCZDSFN5p34fDkFEFEVyLFaGZLtxW1IrjqdoOtu6vCiazgh3FrYUiYbt9oZxyQKdYe3QCmJ1CgTedF2nrl0jEIbyXBGbJX0Tyt2dGt5ODUkU8BSIWKypuZau64SadeQsAcmRHv+15jAENbCJiAUDN+4+nIyqZxwaO/388d3t1HcEWLGnHR2wipDjtNAZUCnKkvE4bby8po4JlTnkuQZmCyVqGNY8AYq357+d9YcdlDkkRdi0CSZ+GYoHSH0U2N6+nS1tW6j31rOsfhkXDr+QKcVT2NK6hdd2vkaxs5h6Xz2SIFGalZqXtxmCO3YQ2LgR53HHYSkrI7BlKx2vvIJz+nQsxQMc7AP+7hAr39pLR7Mff0eItrp6ckqcFA/2oARVNi6qx2qTaGv0Mem0KqQBVKHct2UTq996DVm24CkqZv+WjeSWlOHKzePDfz+Cr72N4sHDGHvSqbgL+1kk6TCUtgAd7+1GaQmg+RUQwJJnRy52YSlwoPsVOt7YhWtqMdbSo2sGz+Fw4HAMfOCc4dhAU1X4aAl4j8hNaWolvGwdthPNBU+atw11wbPQ0QwIoGs9/3W1EC4fjqXc3KqNd+f7BOuXYS0ch6766N7xPlqwjcD+pdiKHkSyGlMkPZyu1k001LyBt30bdmcJuaWzaKtbTE7xNIQoBcATJRhsI6x4yfOMprV9I13de+n07qIwbyJZTvP9oyTKeGxFrGl4l65gCxbJhqYpOCxubLI5BcJt3fv4/bbnaAy04ddDhzIWi625KQn6vOEgb9Zvpz7gRXW4EUSBWQWVjM5JTd/xQcN+3qzby3hPHpOLy3lx3y7yrXbG5JirsXeQla0dvLS3kRK7lYuqShjtSU0wf5BlzX5eqOnCKQl4bBJNAZUyh8wVw9y4LOaeS0EQKMvtsREI66zdq+B2CFQXpGanjr9bp7lORdNAlqGoQkpZwHcQQRCwmSjUHgtd1dF2BFD3BFD3BBFsAmKxDfm4LMTc1IVOuqKh7WgBSUQckpcycZpYHNMrfmv3tnH+A/GTzw8iCPDqt49nbFk/y9CH/fDrUmIlgvfh3D/C1GvS5lI0Hlz9IA+teajXZ7Igc+7Qc3lx+4t9Pr/n5HuYWzW3Hz3sTet/HqfhjgOFf2UZ99ln0fnyKwAIFgsVDz5I1gnHD5x/dd08+aslCX/1VofMlb+dPSArfwse/wfLXn4+4fbn3fhjRszs/3vrX99My38SF0XxnFVN9kkDn++ZoYfMil9yxOoftVCI8B//GdtAtgvbt4yVtlH2bEZ99u6YbcSZ52GZc4Eh+/VvfJvA/tjiMOWXvogly/jq1s7V97JvyxMRj7kLJjD+lIcQ42xnjcaSNb9l++4XIx4TBInjj7uDqjJz/ePezk38dcU3Cam9xSjctkKun/YwuXZj9+bxPe9z/66Xox63ILHwpHsM2QZoDnRzwadPROz6qpwe/nbc+bgtxlejv738U1ZFEXdxyxaemjPX1KrfHzbu5IXaxkP/FoA7Jo3gxKLU5GX/dm0Lb+6LLCQiAf86sYQKl/kVqMZOjb9+GMTXU8mESVUSl043txrauE9lyTshtMP0V6w2OP5cG9k5R/8uFj2sE3y0AX1fKOJxyxfzkcebn3DSA2FC/1iJ3tLzPQvlbqxXTEaIsxMpo+oZg68+ujSp9roOv3w5er2jtPH2z0gq6AN465a0uBKLrlAXD697uM/niq70CfoOfv7A6oHJRQTQFYWm++47zCGFzlde/ex4OEzTn+8fAM8+Y8GTW5L66kN+hVXvmFOCM8qK115Mqv3CJ/+VHkfi0PZqcoq3ne/uQdeO/gmwDBmSJfxcAirMXd3oYWNKwerrf4/bRlvymiHbuq7FDfoAGt/5oSH7AKFAK/u2RC930dm8ltb9iSmjHklX976oQR+Arqus2fxXQ7YP54Ndj/UJ+gA6g018ujdyqYdE+EtN7O8tjEqNr8Gw/ds3fRS169vj6+DVuq2Gbe/p9kYN+gA6lTAv7K0xbF/TdV46LOiDnm784e17Dds8nJCqRw36oGf/1wOb21NyrYVblUNBH8DqPSoNHeYUN7esVHoFfQChIOxYNzCK5MmibvRFDfoAwm+1p+Y6a+oPBX0A+r5OtC19S0ikmmM68AsoyT+83mCMKtrpoqsxfpsjURKTq08lQTVIWEvuut7QwEj6Q08+muY/okM8YoVb6xo4/6AnkEuWgLf/v3sATUvu9xTydcdvlAb0JH/DuqJBJvDLcCziTaxMg64YHJCFow+OPjNucBCZ4HlasMuYfXoKxMebeVPDxvqIsBL//ZdIm3gElOj+xToWDzWB+98eNG6/S+lb3+1wupUEnq2o58Z/njsSeXajoOk6ke5Odzg140clgZ143WFzwdlBAuG+1woo5vrDcCjy+eGBGbokTzDOvY13POHr9H1Okx2/GOGYDvxuPj35PLhvnDQkDZ7E4QwDha4nXJx6P+JQ4CjglMrIKoOj80ZH/PziEf3v50FEq5Wc+b23GNlG9BZ1yb30kv50qQ/HnV2dVHtBgMnzBqZERuWYcUm1n3j62WnyJDZZs5OTMHeML4i7tSJDhs8j8sVnxG8kCIYFXsSZ58ZvVBW5b4iHIMqIjvhy/nnH32zIPoA9qwxP0XFRj1vseeSXn2jIdp5nBPm5Y2O2GT5oviHbhzOj4sKInwuITCs7z7Dd4/Ni+w4wKXeoYfvfHhZZ8RTAJkicUWI8N3SU20O+NbpegwhcWFlt2L4sioz19M0Nv6AyNZoBTllkSFbs7cVXDE1N6bFpg+VeyqelHoHKPHP9YfWoCL4LMGjEwCh9J4s0xgnO6PdAmp6aXE5xXDEcnqvptCCNMlfCJBGO6Rw/gNteWsdji2JvjZNF8Dis/OK8MZw/yXjdG1Nsex8e/wJEnEc6gslXwQX3ptujiASUAM9tfY4P9n5Ao68Rj83DVWOu4oTKE3h2y7NsbduKLMpousaM0hmcNdi8qpsZdEWh/bnnCWxYj3PGTLJPn0f7M88S3LIF1/HH4z7j9AH1D2DLsnoWPbcdvzeMpvb8HkUJLHYZTdXRNR1REsgtdXHCJcMpru7nHNQD6LrO6/ffzbaliwBw5eSCAO6CQsqGj2bTJx8S8vnILixkypnnM+6UeQgm6hiZoevT/XR9sAfNp3y2mmcVkdw25BwbSlsAAQHHxALccwchSAPjZ4a+ZHL8kiNe/xhatRH97SjbFS0ylhsuR7QazxUKffxf9CWvRz44eAK2i75j2Lamhql/7ZuEWraA7ECUrGj+5p6DgkTOtO+QM/5Sw/YBVMXP7vWPUL/zRdRwN4JoweUZTE7xdEqHfQG7y3j+YCjsZVvN83T76nE5y/B27yUY6kCWnZQWzWRwRQKBeQJsbVnCotrn6Qg0IotWCpxVzKq4iErPGFN2f7npP7zVuALtiFVRCZGXZv6CApu5vujdhh3cu20RXiWEQ5TJszkZ7ynmixVjGZJAnb9YdIXD3L5hJes72ii2Ozi+oJiFTQ1kyTLfHjGWke4cU/YVTeeeTTv5pKkdlyRy1dAKziiLX/swGfu/XtPCsuaeVXuHJBDQdHKtEv830sOcYnPCPYezq0llzV4Vj0NgxlAZZwpEWPbXqNTtVggHwe4UqBwmkV/y+Qj8ALRWBWVpZ08h924VECBXwjItG2l6VsrGNlpzN+qq/SCJSFPKEHPiC7uZ7SOP+cAvQ4YMGTJ8fsgEfsmR6R8zZMiQ4X+HTDmHOJz1pwVsqk8sB+Cc8aU88JUpafYoCn+fC/tWJNhYhO+tg5yBqZP3zJZneGTdI2hoXDX2Kr4y+isAdIY6+b93/o/1zesBKHGV8MQ5T1DoSN0sWDJ0L11Kw+9+R2jnrp4cFlXFUl5O5aOPYKsamO2Skdi3rY0X71kVt509y8K510+gePDArPh1Njfxrx/dQLC7Jy9FEARkmw0lFEI/LP9PtlqpGD2OedfdMCAlHXRVo/GB1YT3H5Y/45TBd8R+eouIY0QuORcNR0qBOppRuru7eeWVV9i1axcOh4NwOIzNZuPkk09mwoQJA+ZXhmOD4H3/Bn+MXL8TpmKbPdmQbaWjGfXhH8dsI156M5aK4Ybsq/4WGt7+IaHmTT373A/LOxMsLgpOuAXXYOOqmL7OXWxe9HO62w8XEhEQJDtZOUMZNuWHZOUZL520ZeezrN70AIoaQBQkRMlKVelcpo2/CVlOXcmWx9b8kI1NCzmYryiLVmZXXMw5w79jamXi4iV3UBtojnhMROCNmXfgsRlTN2wPBbh+5SvU+NqREFDRD60rDnPlcf+Uc/CYUPVc197Kd1cuIhQhN32CJ5dfjj+OwhTUm20Phbl74y5WtHYwPNvFTWMGU+Uyb/enK5r4pLH379YiQFWWhetH5XBcgbn6m/1BS73KsvdCBAM9hdtFEdy5AuNnWcktNL6dVPHqNL4dIlCrYSsRKTrdgiUNaqHKmm7Cr7eBv+cZEootWK8tQrSlbuVSVzWUt7ejbmxEcNuQ5w1Dqk5NuZFoHNOJLc8s25Nw0Afw2ro6/ruyNo0eRWH1U0kEfQAa/O2ktLkTizVNa7h98e3s795PfXc9v1v6O5bV9yiv/XbJbw8FfQD13fVc/+71A+Kn5vNRe8O3CW7chB4IgKKArhOurWXvtdcNiE/RePEP8YM+6BF1eeX+NWn2JjpP/eLmQ0Ef9Gz9DAcCvYI+ACUUombNSt548A/97SIArc9v6x30Qd+gDyCs4d/QQvvLyamApprXXnuNzZs3EwwGaW9vp7u7m9bWVl544QWamyMPujJkSITwolWxgz6AhcsxuvNH/cfP4rbRnr7TkG2Apo9+Rah5I6D3EXvRw900fXArSledYfsbP/7JEUEfgI6u+ulqWc/GT36MfqQ8YYK0tG1k+fq7UVQ/oKPpCoriY+feV1m75W+GfT6S93f9k41NCzhcpEbRQizY8wTL616NfmIc7tr6bNSgD0BD5wvL7jBs/0dr32KXr6e2snJY0AewvbuVX2380LBtgBtXLo4Y9AGs7Wjjt5tS05f+cXMNHzW24lVUVrV1ctvabaZtvlnr7RP0AYR12NEV5mcrm1Mm7pIuNE1n8ds9QR/0/HxVBdqadJa+G0QzIajW+HYI3w4NLQj+3RoNr6deNUZrChN+vuVQ0AegN4QJPx1dLdYI6qd7UFfsA38YvcFL+Nn16KH0Crwc04Hfk0uTl71/fZ3xTsQwK+PUWYqEb2AGhMvr+24pOvjZ4v2L+xzb0T4wg+rA5i1onZ0Rj4X37EEPGVf0SjlJvP+CPsWQEmgq8LYk98zVblxveEBphtCujqTaB3e2p8eRBKmpqYn4ua7r7N69u3+dyXBMoW3YnlA7vdOguqSa3ndRsGFt7Aa6SqAxTpsohIPt+Lt2xb6+r46Az9iYoKFlZfRjzdGPJcum5o+jHtvZZvw6C1rWxW3jjVBGIlG2e2MPoNd1GC8V0RkOEYgTsK9qTc0YanVr73HGti4fXoPlUQ7yXl30Ug4APlVnS+dRNIaJQHenHlV8PuDrOW4U/97eQW9gn5bykkza7siqs9r+1N53bU977w+CCnqDcaXiRDimA79zxpcmfc5JIwZgW+IYA8VtrX0VpfqDcQV9lR0PfjahsO+2tPKsgRHLsQ0fhuCMnPwsFxcjWM0VKB0oLDYJq2Ngdmg73MltMS0eMnxAxF0s5cn9NqwVqVHoMkp5efTfSKxjGTLEZUhiW9qFbINCEUJ6hxDW/BFxWgjYCoyphspWDzZX7N+XxZ6HzWlM3CWWomc8tc9kGJIbPT2lwm1c3GWKJ76qpl00vkW+ypkT8/hwl3Fxl2zZgiXOsznGk5rtdKOPUPesctrJspjro2cVxt7GaRUFhmYPXHpCIjizBcQoOyKt9p7jRrGX9P5ubUUCgpjasYZYHnmMKBSm9r4LZUeos1pEhELzxeFjcUwHfteeOJQSd3RJ3yOZMTiPK2ZVp8+haMz8BuQMSu6ca99Njy9xmFE6g+snXY/L4sIhO/i/Cf/HCRUnAHDrrFupyPos79BtdXP/qQNTIF3Kzqb893chlx4I/g8EIGJODhUPPTggPkXj9K8lNnCRrSJnXJdcSYVU8sVbf40o937pCWLkV0hR9VDOuv7G/nCrD7lfHIGYc8RLW47cKVir3eRcYFw2PBWcc845VB3IOXU4HEiShN1u58wzz6SkxLiiYIYMtrkzQIrTzY8bEfV3HA/xstj5fQCcbXxrfcFJv0DOjhKciTL5c27G4jGWry0IAqNn3Y7VEVmC355VwahZdyCKxgbxxfmTGTv8agTh4OhXAATKi49n4qhvGLIZiTOGfp1BnvFHfCowueRMZpZHLvWQCLeNvpwcOfYA9N9TfmjY/m/Hz6PAGnnCocjm4hdjI5eOSgRBELhjwtSoA9wqp4sfj5lo2P7h3Diqmok5PZOHg10Ofj7BfH8yf1A2YzyRA49Cm8QtE/LwWI9uhUxJEpg214J0xM/HmS0w9RQrkgkl7aLTLdhKe863FgkUnZ36iXyx1IrlrBw4/Da7RayXprbcgjynCnF0Yc8YNduGZf4YBHt6g/r/CVVPRdGo7wzgtEpoukZ3SMEqCARVFZDIc9lwWiXkga7lpSrQuA0UX89/qhUkHeweaNwMngooGgbO9CZ+JoKma+i6jhRhSiekhFB0BacldXLDZtDDYZBldL8fMcoq4NFAd2cASRaxWGUC3SFkm4Su6dgcFsJBFav96NBiCvi8yLIVSZbR0REEESUURAmHcGS5UZUwkjzws5FaWEULq0g2GUES0XUd1RcGQUCyy6DpR1X9PkVRkGUZVVURBAHR4GD8805G1TM5Eukf1XAYZec+QANNBacTRBlbiuqOhTra0MNesLkO5FNroIvY8lMj7qQpoZ7gVJBQupsR7R5EyZI6SXU1jK6rKEoQm92DpimGA74j0XUNVQsjS7aU2j2SsBpCFHrec4IgIKXoOn4liKIptAa82CULEiKCKJDvSI3ImF8JY5N6asl1KyEsooTtyGjBBJ2hEOg9OYQWScIiiljS8G4Na1rK7YZVjYDS0x/YZREQkAQGrEySURRFQ5ZFNE1HTOHKnK7qaS/FpGs9JbXQQbSkr0/WVQ1EIaHvNqPqGYdFO5q5/vEVtB4QdxCFngBeAw6UTMMiCcwems+dF0+kxD1ASkmLH4E3v59Y29nfg9N/mVZ34vH+nvf5ycKfEFB76qENdg+m0l1JZVYl29q3YZft3DjlRoaaKPCaCpoe+gvdCxbgmDSJcGsrvkWL0Px+UFV0USRrzmzKfv0bpKz0Lq3HwtcR4rnfL6frQL0ehJ4dVALCZ3X9RBg1p4zZFw7F5hzYoMruzKK9vo6X/vAb2uv2I1lkwoEgOjqegiJcubmMOfFUJpyamhpVRlA6AjT/ayNKnQ90HawCglVGsEoIsoDaEgBVR8q3U/h/E5GzB37rryz3vI4l6eieyc3w+SK0pw79ycgiH0EBrDd9zfCKH4CyYy36W4+Bv29OdbCgAtuVtxm2res6je/9GH/tkp7fMTroKqItm7w5t5BVfYJh2wfZu/Ff7Nv2NGrYB4JIVs4QRs683VT9voMoSoCtNc9TU/s23f4GVLXnGm5XFSOHfJHq8jOQJOPvHl3XWVH3Gp/sfY72QB2aplLuHs2Xx99OljXHtP9P1X7EY7vfpkPp7pWK7hJtPDDpekZlm1PH3tzZxJ+3L2FjRyMhXcNtsfGD4bM5tcT8uKE9GOQ3G1ezqbMddFB1DRWwSxJnl1Vy9ZARWKPtRUyAvd1+Hty6h11eHz5FpdRhY1q+B4csc2ZZAfk2c33KptYAP13VQkdIo9QhctuUQoa7U9tP1XeoPL88THdIZ3q1hNUi4g/pTKySKMgyH+Ts2hhmx0YFJQS5hQLZeQJWq0jVcBmr3XzAJkgC3q0KnetVRAvkTLVgLzXvt67phD/sQNsRQMiW0CXAqyHYRaTJLuRRqV1A0IMK6roG8IUQxxYj5qd3geKYXvF7Z2MD1/0r8fNsssDa287AJvfzwGvHB/Dv+cmdM/mrcMHAbKN8dsuz/Grxr+K2EwWRVy58hSqTnYNR9lz3dboXLozbTszNZcTHCxEGYMAdCij8/cYFCQu8ZOXZuPyXs5DSOPMUj/b6Oh75bvztW5PPOp+5V329HzzqjRZS2f+LTxMXzRGg/NfHpzxHIIMxMit+yRGrf9Ra2wn//dm4Nmw3G9uOqa7/BOWtf8Qx7sR2w32G7O99aj5qd33U44Wn3omr2rjC9ebFv6Bp95t9DwgSsy58F9nErhVd13lr4ddoad8QtU1Z0WxOmflHw9d4YfNdLKp9vs/nsmjl5ye+iT3OVs1Y3L75CV5rWBqzzbPTbqHSaUwX4dPmPdy09q2Ix24ddRJnlcXL74yOpuvM++B1glFUPQHGuHP423RjEwcN/iCXfrzq0OLBkeRZLTw2awK5NmOTtHu9YS5f2Pe5f2ROEcOSSF+KRX27yr3vRhYqsUrwzbk2SjzGxxmrPw6xe0tkgR1nlsDJF9qwmCwU3/JxmLZFvYV0SuZbyRpubiwXfLQBrSayuAuAPNeD5eTUrHjrmk7o0eXo9d4DxkWsV01BLImuPWC2jzym9xL98Z0jZZpjE1R0/vlJTXqcicWTX0n+nNX/Sb0fCfKXtX9JqJ2mazy4amDy6XRNo/vj6Gpnh6O1teFbsiTNHkVm86d1Sal6eluD7F6fWjnhZFnxxksJtVv3fuROPd10Ldib1D1Fh+7F+9PmT4YMA0X4lQ8SaqfHK/kQBWVxAuUCgrEVCqOhq+GYQR9Ay5I/GbINPYFZ0+4o7yhdpXbzvwzbBmhp3xAz6APY3/gpnV5jyr1hNcCSfS9GPKZoIdY2vGfI7kHeboxfYuqubfEnFaLx9N7oqqEP7Vxm2C7Aq/v2xAz6ADZ2trOn22vI/mM790UN+gBaQ2HerTeuGnrPhtaInz+8NbJSuRHe2xS9BEJIhaW7zCmT7t0WXVXV59Wp222+ZEHb8r4+tq8w57ce0GIGfQDKp6n7HrSats+CPgBFQ12Z3vHIMR34yQb2/vb7ah/07OP7HCEJid8jiwnVL9Mksw8+hTkFySAZyDET07ynPe71E8wdEdOs+BcNQyu3A/G7z5Ah3ST6WzCaM5TOviuhXBezv9vo1xBN9l2J+mb0bxAEESHGEE4STPof494cxGJiq6Qco3+QTOawWeMJGpm8jpzAeYm0iYYlyu6TaJ8bQY7z2zX7HcR7fFLx6oj0CJkediTyZ6fwtRcxRzHNu48+XxFHkvzkrORknrOsEl+ZOQDbEq80UGR11vdS7kaifP+4xHIRZVHmhsk3pNmbyAiiiPusMxNqK5WW4pw+Lc0eRWbkzJKkXlS5pU6qxhqXuU4FU8+dn1BO0HHnGleUM0PWCeWQTHAsQtb0jHpmhmMPy/lzE2on2I1tH5OPvyh+oyxjYmSCKGPJiZ3rVXB8Aqqi0ewLAqXDvxDlmIWKUZcbtg2QnzOakoLpMdsMKj+dbFdFzDbRkEUrJw76csRjNsnJhGLjqpgAF5XNidvmJ8MvNWz/8kGToo6xvz8i/rVjcWZpJVly7AnKaXkFlDuNbYW9Zmh5zCCs1GHjtFLj6o8/HBe5j/+/kanZXghw2lg56v13WGHmUHOTKkPGRD8/O0egdJD5yda8WUd8xwLkTjc3iS/YRMRRjphtLCfnmLpGr+tV5SBUHfa92mWkacbeCQlf81jO8QPYWt/F9Y8vZ1tTz3YTl1XEKgmEVR1fSEMH3A6Zs8aV8rNzRpOVZhnVqNQshcfmJdBQggv+DJMjv/D7i3VN6/jO+9+hJdCCVbQyqWgSVe4qqrOr2di6EZts44ZJN1BocP9/qmh/8UW63n4H15zZhBsa8H74EarXC+EwSBKec86m6LvfHdC6fqGgwqv3r6ZueycIIFtERLEneA0eKNZutUlMOWsQE+dWIlsGfnXK19nB6/ffTeOuHVidLvxdHaBD0ZCh2F1ZTDj1TAZPOm7A/NP8Ci3PbOkpzq5pCE4LotOCaBERbDLhOi96UMVSkU3hNeMQj4J7mqGHTI5fcsTrH8PtnWh/fTryQZcD2w3mAhytoYbwG49CS4TtScOnYDv/W6bstyy5n+7trwMCmqaBFkJ2FlBwyu3YC0aasg3QuOcd9m54lHDI2yO8UjCOEVN/jGw1X99T0xR273uXXfvexttdSzDcgSTI5OaMZvigCygvnoNgcoliS/MiPt37HM3+PYTUEMNzpzJ/9A+xSuaF6j5oWsNDO1+lLtBKmM+25pXZcnlo0ncotptTGK/1dfLIrhUsbanFr4UpsLm4bcwpjPGYV4MNKAr3bd3AmvYWJEEkqCoomoZTtvCFysGcXzEI0cSqVlswxMPba9nl7aY9rDA4y8n0fA+yKHJycR6uOIFnPBp8IX60vIV6v8IIt8zPJhVQ7Ejt+LTTp/HiqjBdAZ0TRkjoCPhDMLZcIjsF4it1u1W2rw8TDugUlIm43AIWq0hZtYRsSc2qlq9WwbtBQ7CCZ5KMNTc161nKyi7UzX6EXAuCCFqXimATkCdlIVamJs/yILqqoW1pRveFkUYVIGTFtm+2jzzmAz+A3S3dfLKtGR2NvW0+pg/KY+3edkKqjsdppSrfwZRB+RQPlKLnQZp3wds/g/0rATu4cnuWnRu3gT0LcofCyLlwYoLqn2mkyddErj0XXdfpCHVQ4ChA0RTaAm0A5NpzkdMkW50MoYYGwvv24ZrSU+Q2sHUr4oFC5JLTgeR2xzq93+hq9bN1aT32bCuVI/NQQmF2rWuloaadgC/MrPnDKR2cM9BuAlC/czuaqlI0aDC+zk6621soHjKMpj27kWSJzqZGBk+aelRITqveEOH2AJJVRlNURLtMuMGHpdCBnGM/qso5ZOghE/glRyL9Y3BLDby7EIKhHjlrpw2Ki5DOPwU5BZNewTUfwb4dkF8OXc0QVqBqJLaxM03bBgg0bsTfuAY5qxLZkQNqAEdZah6RcKiLrub1OD3VIIgEuvYhSFZc7mpka1bc8+PaV7rRNBWb1Y0/0IKiBshylqXs/djQXYOmKRRnDcYbasNtS22dseZAO/ds+y92JFRdJ4jCjNwxXFQ5OyX2G/xdfNi4iyKbixybgxyrgyKbC5ecmsnYvd1eNF0nrKt0hcOM8eRhS7GQW0c4TEsghNtqocCkmueRtARUsi0C7SGNuu4wVdkWcm2pHVt1+TVauzWy7SI5LsFUQHw4uqYTDIDdKRAK6ggCpgVdjkTx6giSjhYGLQTWXCElJR60LgW9U+1R9fRpIOiIuRYEa3rGDHpIAVVHSCC4zwR+MdB1nal3vEtLd2TloiMZU5rNs9+YjSvFP6qE+E0lhJJIGD37Hph+bfr8icLuzt3c+OGNbGvbhtvqRtM1vGEvgz2DaQu00R5sByDPnsddJ97FjNIZ/e7jQXbOv5Dg5s09/5AkkGUIHpa0Kwi4L5xP2e23D4ii50H+dcsndLXETiY+yDcfOBkxwfyFVNNcu4d///i7aOHoSeGHc/a3f8jo440r7plBVzSaHllPaFdH9EYi5H95NI5xqR0oZTBHJvBLjlj9o65phH7/SGwD+TnYrv2ioWsrLXWoj90as418+lVI4483ZD/UsYf9z10S5ahAwdxfkzU4se2skdj06c9o3vtO1OPFg89jxPSfGba/etNDbNrxBLqmYLF6CIV6Jkbt1lxOnf0AOW7jZQuCip/ffTyfbqX9wCcCoFPsGswVE35HkavasG3oGT+d/cmttKnRBVD+OvE7TMwZYsh+UFX48qJnqAt1Rzx+YflofjjS2HMDsM/XzdeXLqRD6dtfXTdkJFcOMa4aeji/XLuNd+s/E1wb5LRz15RRlDnNLSTUdoe5dVULO7vCB77Zz5iSZ+OPM8yvioZVnb99GKS27TPrDgtcfYKNyjxz44zmOpUVH4UJdOvIFlDCIEowdJzMmKnmVy7DHRp1L4YINR4Rw4hQdKYF91hj43hd1wk+0oC+J3LcIJ3sxjo3x5DtaCgLdqF8ugdUDXFMEZbzRyPEGOdlVD1j8Md3tiYc9AFsrOvi7wt2ptGjKHx8X3JBH8DrN6XHlzjcufROtrVtA6Az1Ik33NMp7OrYdSjoA2gNtHLrJ7ei6bGVtdJF+8svfxb0Aahq76APQNfp/O8LdL7+Rv86dxgbP96fcNAH8P5/NqXRm9i8fPcdCQd9AG8+aFym3Cze5fWxgz4ADVqe3oIeNq8uliHD0UjoqdfjN2ppR1ON/QbUf98et43yjnF1zIa3boxxVKflI+P1bAO+hphBH0DDrlfobI6uPhmLxpbVbNj2GJoWQkc7FPQBBEJtLF59hyG7B3lu4x2HBX1wMDRo6N7FS1vuMWUb4J2mlTGDPoAb1jxg2P6/dq+OGvQBvLBvE0taag3b/9X6VRGDPoC/79xCfcCY2uzhbGjv6hX0Aez2Bbh/izGl1sP586Z2dnb1+H/k8szK1iCrW4wp8R7Op9uVXkEfgD8Mzy1LfNwcCV3XWbWwJ+iDnqAPQFNh2xqFlgbzfW7zB+G+QR+ABk1vhdFCxha11FXdUYM+APXDTrQGc/fncLS6LpQFNaBooIO2oRF1dV3K7EfimA78Pt2RvJzuun1xBovpYIcR2eWBWand1r4t4bZ13XV0hbrS6E10vB9/knDb4Nbkyn6kkpp1yT2jtVva0+NIAnQ2NyXVXlPNySqbIVyb4HMX1lDaEw+8M2T4XFHXmFi7LoODYDWBAZCJyT/VF/v9qKvGf7tdLesTatfdscOQ/fbO2Od1dO0yZPcgtV1boh6r8243ZRtgRVv8vv7wvL9kWd8R/9nc0R25rEEi7PHFDlprvMZKORzOqrbIE/Y7veaDyoNBXzRWtprvt/a1Rf5tNnbpmNkNqCrg64p+fmer+fFrqDm6DV0FpdPYNbTd8e+r1pD4BHhcW419n0O9MfqESCo4pgO/q+cMTvqcM8YNgLrfLAPKlwOUP3d8eeJbLyYUTMBjS50KVTLkXp54bUTXCca3k5hlyhmDkms/bwBUZw9QNjw5lVyby3x+jFEc4xITFZI8VuT82ApeGTJ8bpk2LqFmYo5BIRN3AtukLcaFEKwFsd85oglxkbzSxJQjc4qNKT6XFk6PWaqhtMhc/uOUkuiq1SPzZ5myDXB+aXwbebJxAZzTi+Nvc52RZ1zdcFpe9D5AAsbnmBOmATi9JPLzP7Mgx7Tt6YWxt4qeXe40fY0xZZGfz+HFoqkcVNkikFccObwQBCgsNx96OAdHtyE6wJJnzH9pUhylVxGkwanTA5Gqc/uokItD06vcfkwHfudMKOOsBAM5Abj2+MFcMrUyvU5FYsQ8GHlecud8d016fInDD6f+kEtHXkpldiUzS2cyvWQ6VdlVfHH4Fzmp4iRcFhcui4u5lXO5+6S7B8RHANeECeReffWhOlZyRTnWsWN6iseIIlgtyGVllP7mN7imx5bcTiclQzyMPb40oba5JQ4mnDIAz+cB5t98K/mVnwWqksVySJHuyBxJq8PJFXfe16/+HY5jVB7Z86pAjlGnq9hBwdfGI6S5Zk6GDAOF7cTpYIuTT3OS8VI2lmvu6EnciYYoIV/xc8P2S8+6DyGrPLJpWw6l8/9p2LYk2xk27VYQIk+iipKDkTN/iSPK9eORnVXJidPuJD93LDnuYZQVzkaWnYiilbKiOcycdIth3wHmDb2WUfmzDtTbE3DKHnLtZUwvv4ALRpoXgBvrHsR5RdH7RgmBF2bEzu+MxTllIzm/NLIqa47Fzu1j5zI0y/gA+CdjJzI9r6BPyQKnJHHvcbNxyebzzIocNn44ZjAuSUIArKLA/IpivjnC/ATtt0blcEGVixKHRIFNPDRYl+gp61DiNO//pCqZk0dKh8rGCcCwIpFLppkXqJl6ipWywRLObIG8YoHsXIHcQoHpp1nJcpsPPfJPtOCZIiG5AAsc+BlgyROouMxmuF+XBtuR53p6bvSRZIlYryhCyE6dJoTgsWO5ZDxChRuh0IV85gikEenVHTimxV0yZMiQIcPni4y4S3Jk+scMGTJk+N/BbB858Hr7aea+97Zy77vbUOPEty6LwANfmcrJo8wrJRnikwfgnZ8m1tbqhp/uTa8/UWj1t/LjhT9mY8tGbJKNsqwyWnwtNPobUXQFq2TFJbsozSrlGxO/wYkVJw6InwBd779P05/uRfP78Jx/Ac6ZM2h/5lkEUSSwZQuhXbuQ8vIo/8MfcE6eNGB+Nu7u5LWH1uJrj50vk51v5eQvj6ZqbH4/edaXbUs+ZcET/6CrpRlVUUDXEUQRR7abQeMnk5WfT9v+WkqHj2LK2RcgW/q/LqbiC9Nw5zL04IH8Ews9KbERUg5dc8rIPc+4sp5Z2tra+PTTT/H5fEyePJnq6moWL15MbW0tgwYNYvr06UgDqDib4fNP8P5/gy+6EIT4zS9hcRvflh18/l6oiSKAUjka2yU/MGwboGXxvXRteLLvAUEi7/if4h5xjmHbIX8z6z78Nr7OmkPbMnU9DIJEVu5oRky/BZfHmGrlQfbWfcTG7f+mq7v2gNALuBzFTBr9LSpKTjBlW9NVnt34a7a1LkEWbARVP4oWoCJ7NJeO+wU59mLDtnVd5/bNT/B647KIx0/MH8dd44wri6uaxo/Xvc0nLX3HMiNd+Tw49Twckrn+Y2NHG3dtWktnOMRZZZVcN3SUKXtHsqy5nb9u20tnWGFOUS5FNgvrO7yMdGdx6aBSbCYVuJc0+bljdTOdh/VdhTaBu6cVUZ09cLWHkyUU1Pjk9RDeDh27E2adaSXLba5f01Wd9pUKgVoNXdcJt+mAgHuCRM5U2XS5FGWTj/AzzRxKY3UJWL9VipT9+Q+bjukVv78v2MmvX09OBXHhj06hMs/83umkaNsL9yaWi3EIzyC4cW16/InB3Gfm0uRPXOTjwVMf5IQKc52bEboXLWLP1dck1lgQGP7pJ8i55vf8J0vQr/Dw9xckpdVz/vcmUTkqvXvAI7Fl0UJe/dOdCbcfd8o8zvjGd9PoUWRqb/mYuDM9h5Fz0XCypvd/bm84HOa+++6jq+szIZqhQ4eyY8dnohAzZszgrLPO6nffBpLMil9yxOofg8+/DdvjKwzabr7O0LXDrz+MtmlxzDbC6BlYzzZmv2PD07Qtjq0OXHbR01hzk8uVPsii/56GEo4uBCVKNqad+wJWu7HJtj3732fh8p9EPX7qrAcoKTT+qD+86rtsbYl8/52WHG494TUkg3oA92x7nmf3L4zZ5tSCSfx67FWG7F+/8lVWtUdXL6x2eHhiVrRSHvEJKApnfPQm6mFj3CsHD09Z8Le2rYvrl22IenxeST4/nzDcsP1dXWGu+rg+4jERePW0clyWz0e21huP+wkdNvckinDe1eZy65veCdGxOrK4UO4smfzjjU8aqC1hQvdGeDZlcPx84HQWDpIp5xCDx5ckL6n794UDUM7hNQP78TvMywUny57OPUkFfQCv7HwlTd7Epv2FFxNvrOu0P/dc2nyJxbal9UkLtG5dHLkzSDcbF7yfVPtNCz8wpQxmBF3Rkgr6ADrf7f/fEsCuXbt6BX0AO3f2fv+sWTMwubwZjhESCPoAw79TbWv8CVl9c+QVo0RoX/vvuG3alhrLJe7u2Bkz6APQ1CAt+2IHP7HYVRu7VNDOva8Ztg2wozX6/feF29nVvtqw7Vfql8RtszBBZdRIrIkR9AHU+DvoVozL5r+0b3evoA/g9f2p2yn1Tl1sxdn3G1oIa8YVbV/aE/3Z1IAlzebLOfQHAZ/eK+gD0DRoqTdX0qFzQ/TzO9eZUxRXPo5SXk0B3fv5L/90TAd+ea7kl8Kr+nu1D6AoObXEgcJj8xxIJE+cQkdi6oqpRi5K7rrWCuPqYWbIzkteHcrpMa6SZwanJ7kVUYcnx/R2i6SRkr+elN3/21EBsrL6bq+zHLE1NlKbDBkSJsGfg+HfqTWB95cJVU/ZEV/kQM4xNgNvSVBx2uhqH4DdFvtch91c/2iRYq+aZMe5fsxz5fjfrV0yvt3QGksUiJ5H12ZCvbzC2ffd6Ulh6kFeHNEkj8WCZKL/K3bE/tvzbZ+P4Xs0DR1HlrmxgeyKfr5s0raQH+PeWz//YnCfjyfHIL+5cHxSYYrHLhkqAWGaeQaK0J5iXE3LKB6bh/nD5ifcvthZzFfHfDV9DsUg/8orkQoO6/QkCUtV5AGCpbyc7DPO6CfPelM1Lp+cksQnG5w5FibMHZggdcb8L2LPii3ffXAAKckyJ19hPP/DKIIgYK1OTmK84MqxafImNmVlZUyaNOnQv/Py8jj99NMP5fTJsszpp58+IL5lOEa4PAG1aKOlHADpzPjb6eVzvm7YfuFJcRRBRZncaQbKIdET0BVUnhqzjbtgInmlsw3ZBxg77KvYbZGDV7stn1FDLjVsG+Cc4dH/9onF8yh2GR/P3DbqirhtfjriMsP2vzU0tpr2NdVTkEXjQ9Q5hcUMcX32bEsI3DRqgmF7R3JhZTHF9t6Br3yg/5MFgetHDkI0EfjNr8oiL0rQNDTbwkQDk8YDgWwRqBja+3vMLRJwZpkLPwpOsRCpWoogQf5J5gJ8y0w3RJjTEKqtCNbPf9h0TOf4AfhDCr9/azMfbG5EEgXafCE6fD3LwIIAbrtMaY6TL8+o5MszqlPotQH+fhrsi7MtRrDAd1ZC7sDtM97YspEFexdQnl1ORVYFjb5GajprqO2qZVjOMOyyndKsUmaVzcIiDsxqCoCuKHS+8y5qexues89GzM7Gv3Ilgt0BskTb40/gmjUTz9lnD5iPB9mxqpFNi+rwd4XoavGhaQKyVQRFQxcFCsqyGHdKBYPG5COaTBg3gxIKsXP1Mmo3bUC22OhsasBid1AxaiwFlVVkFxTSsHM7RdVDcKWgTpJRure00vHSdkSHTPapVSiNPgKbW1G7Qog5NrSOINaybPIuHTmg9xOgoaEBn89HVVUVkiTh9Xqpq6ujvLwcp3MAdiAMMJkcv+SI1z8qioL6p8ciboEWzj0J69gRpq6vBrpRnrkHmmp76stqB7bn5VcgX/YjJLu5Z1hTgjQu/A3BuhUIshPB4gDFj6t6LnnTvmHKNkBn8wb2bv4XLs9wRMlCW/0yHO4qigfNw1M42bR9VQ1R37wMb/c+NF1FUQJ4squoKDkJMQX1eDsCTSyve5VK91ja/Ptp9tcysehUKjzmdxJ1KwFu2/QflrRuInRYsfaZnlHcNuZycqzmdiTU+7t4YNsS1nc2IgsCXjVMud3NbeNOocKZmhrACxvr2evzMr+iGqecWmEOVddZ3NRGQyDEiUV5WCWRTR1ehmY7KbCZF1/RdZ339vt4elcHTQGVcqfM5UM9zCr+/PULbU0quzYqlA2VKKlIzfeg+nQCDRrWHAF/nQYauIZJSPbUrMqFF3eirOgCUcRyugd56NFx3zOqnnGwyRLF2Q6sFok2bxARgclVOdhkgbX7OtF1HQGdXOdRoJCUyLZIPQydDQMa+BU6CplcPJmOQAerm1ZT5ChiWO4wvjjiiyypX8KW1i1MK5k2oEEfgNLZSWD9OnRFpXPBAvzLV2ApK8NSWoLn3HPJv+YavB+8T2j3bqyDjIkDpIrsfDsWq0RXWKOwKpu67R10exWcOTLZeQ46mnzsXNlE9bj01neJRzjgZ9+mDQS7u2lt20vZiDEUVA1i48cfsOnjDxk8eSqgUzZyYLcvWwvs2CqyCDYH8K9sRA2pSLl25GIX9sEe0EBp8aG2BBCLBvZlXlzcW3kvKyuL4cONiwJkyHA4kiQRLStF9xvPoTqEpkFHE6B9FvSJEmhhNFWJWA4rGRRfM6GGdeiaiijbUb31oOuogTY0JYQom+u7JdmGO38C3R07CHbX4fQMIeRvIhyMnf+XsH3JitNeiKL4qG1YRCjUQVjxkeMegTvLfF3Wmo41dAVbeWPbgwzJnczogtnUdKwh31mBw2J8NRegLdRFR9iLRZCRdIkQCi7RhixKuBLYChqPFa372OJtptjmIsfqwKsEqXLmIAmpmYwLqArtoSBd4RDP7tlJfcDHyUVlTM8vTEkagiQIjPJksbxlH4ua2ih12hnhdpFrNT/2UXWdje0hcqwiJ5a4cMgiF1S6sKRwojKk6Gzcr1LbolLgFpk+RDa1Snk4Ha0q9XtUNE3HkysRCuq4cwVcJrdhHk6gUaV7h4pSIoAqoGv0JECaRFM1lA860ZrDSBNc6JKAss6P3qgiT3UhpFBURw8oaHWdiEVZCAbS04xwTK/4NXYGmPO79wgn+CBU5TpYcPPcpK9jGk2DXyW5OlI5G74WO3E8HTy/9XnuWHwHih4/efYro77Cj2f8uB+86kv7iy9R9+Po1xasVvTQZ4Oe/G98g6Lv9b8CpabpvHr/KvZuak/4nKvumoPL3f95fpsWfsjrf747obaCIHLhj3/B4EnHpdepCHS8XUPX+4kn8Q90SYcMvcms+CVHrP5RC4YI/ylOkXOrBduNVxm6dnDVh/D+f2K2EU+5DMuU0wzZb158L95IpRwOo+zCx7HmGfv9bln8Sxp3vx71uD2rgmnnPG/INoCuayxc9hP21n8Y8fjooZczZey3DdkOq0F++8l8vKHWiMcFRK6c+HvGFB5vyP4DO1/h33vfi9nmyak/YbDLWMmI8xb+m5ZwdIGS6wYfx9WDpxiyDbCls51vLvuEkN53AFjucPLojBNNF3F/bncd927pLaBkEQR+Om4op5Uan6RtD6p8d2kjNd7e4yxZgH8cX0JVlvnAcm+rxt8+DKIcdnssEvzgDBsep7nAZsVHIWq3RxdBqR4tMXG2uSBn778CBBsixy9F58i4xxi7R1pzmOD9ddFF90SwfaMEscR8kKbubCX83HoIqSCJWC4YjTQmfkm5jKpnDH7+0vqEgz6APW1+1uxtT5s/Ufnk3uTP2ftp6v2IQ1ANcs/yexIK+gCe2PwEYS2cZq8i0/DrX8c8fnjQB9Dy97+jhVIw+50ku9e3JBX0AbzzSHQJ6XTy3qMPJdxW1zXeffjBNHoT5bqanlTQB9D96X600OdfqStDhiMJ/+Wp+I1C4Z6anEaIE/QBaB8+bcw2xA36ABo/iJMHGAV/156YQR9AwFtLe4NxVdL9jYujBn0Am3Y8TjDUYcj2e7v+ETXoA9DReGFz4uV3juTxvfFVnG9c9xdDtnd722IGfQCP1qw0ZPsgD23bFDHoA9jn9/HKvj2m7AM8uLWvjbCuc/+W3WgmFlWe3+3tE/QBKDrcvaHNsN3DeW1NuFfQBxBW4eXV5sZs3k4tZtAHULNJpbvT+NKcb58aNegDaHpXMaxUHHqpJbbSugbh11LzHSjv7egJ+gBUjfDb2/pFCf2YDvz2tycvd7ujyZsGT+LQ0P/1+IzgD/vpiiN/fTg6OiG1/4MpAM3vT+4EVUX3+dLjTAy624NJn9PVMjAyzuFgctcN+gbgt6QZeGnqoAcygV+GY5BAYu8XPcF2hkjzQEYNtBg6L+iPLcd/EF+n8XIv/kC88kc6gaCxQWSrf1/cNgHF+DtYS6DOUKdirM/c5Yv/N6u6jmKiHEJTnP4q3vFECEd5tttDYRQTz31TjP6oNZiavqrTH9m/aJ8nSqA7sfMDPuPXUVpjn6sHMbzlU++Kf6LelZrvQO864r3bHTY2hkmSYzrw+/qJQ5I+5/yJZWnwJA6n3W7gpP6XlM2x5zCnfE7C7UucJbgsrjR6FB3nzJlJtbdWVyPl5KTHmRgMnlCAJCf3Xc64IPnnOhVUjk1OEW3o1OS+g1QgyCJSQXK5J5LHiuQ+CnJ8M2RINaefkFAzOcvge9qTwHa2nPhbl6IhJFBywT36YkO23QUTkK3x7AsUDz7XkH2A8uLjscjR763LWYYnu9qQ7ROrvhK3zZiCxL7/SBRb46effLHMmP2Ti+L3YYOcHlOqnueUxc6fPK243LDtg4zIjvzdnlych9WE76eVOaOO8M6rTM2Y6rjqyNm3s4aZk/7IKxbjVnCxOSC3yPj9yR4txRwCO4eICAZKOwHIM+ILFknHpeY7kMb13iYtji5E6AexuWM68Dt3Yhk/PmsUiYyrHRaRF6+fjTwQCn85FXB6klsyfpGapeZkufvEu7lu/HVMLJxIvj0fh+TAY/Uw2D2YeVXzyLflY5fsTCqaxLPnPTsgPgJU/eUhsuadBhYLSBJYrSCKIMvIpaUU3fJTXHPmIOXn4zrhBAY9+8yA+OnKsXHxj6eSV5bYi2T8yRWMmFaSZq8i84Wf/JIhx03vkcM9gCCKSFZbr3/bs7KZMO8szvrWjQPhJkXXT0Yuj3E/LQLYJbCIWAe7KfqO8TySDBmOZmyTR4E7TgmWq79g3P61v4NYIh+uXKzXxN52H4uqL72KYI3uv3PYueROMVY2RhRlJp/+LzxFUxGlviNVyepm4ql/QzIhYuKw5zPv+L9RXX46Vvnwv0OkuGA6Z57wqGHbFZ5RfGXcr/HYDh88CjjlHLKt+cwov5BLx91m2P5z039KZZRSFAAn5Y7jm0OMB8V/mXwuUoTRuwBM8BTz6NQLDdsG+NKgoXxz2CiyZQsyAiI9A94im50/Tp7BaE+OKfsAD80Yy5RcNxZBwC6JjHI7uWZoBT8ZZy5nfGqBnd8dV8DMQjsldgmbCNmywDXD3Vw62G3ab4BTRsucMU7GZQVRALsFzplgYcogc4GfKAqcfIGN/GIBUQJBBNnaU89PtkBxpchJ59sQReOLF4IsUHG5FdlNz5cqg2gD0Qnu8RIl5xufyLXMciPOyf4sOhIOXEMArALSKW4sJ6RGcVY+bSjyaUMRh+cjn1iN5bxRKbEbj7SKuwiCkAM8DIyjZ9fsNcAW4GmgGqgBLtF1PWYUY6acQ4YMGTJk+PzwvyLukukfM2TIkCFDshzt5RzuBd7Udf1iQRCsgBP4KfCeruu/EwThx8CPgZvT5cDlDy/h4+2J7eU/fUwxf/vqAI03XrgB1vw78fZXvApDjW/jMMraprV85/3v0BInr8IiWjhn8Dn8dOZPcciOfvKuN2pHB7XfuxHfsmWg60h5eSBJqI2NPUqqB5BLSii76y5c06cNiJ+bF9fx3j83xU4oPoCnyMFXbpuJYGK2zAz+rk5euOt26rZuitpGEEWGTJnOBT/4KYKJ7S5GCTV00/TQmvh5eyLYxxeQ/8WRCPIxvfkhw9FJv/SPwTv/HrvBeSdhG2Oslp+ua4T+9C3QoojDOLKxXHcnosX4DHzjB7fi2/lOn88FyU7O1P/DM+5Lhm37vbXsWnM/7Q0rUI/IX5etHkbN/CW5pbMM21fVEGs2/4Wde19H00I47IUEQ+095Ryyh3DCtN+R5Sw1bH9Ly2Je3/Zn6rzbDn3mkNxcOu7njCk0Nz5QNJUzPrmFbi1yLpxNtPDenN8iG6xF2Bjw8qdti1jQtDtiPuF3hs3ksqrxhmwDdIZD3LJmGava+wrgjHHn8Mvxx1HqMF7KZ117F49s30tbKExHSKEl1COKIgBfri7lGyPMlYh6d5+XO9a2RRwWSMDTJxZTaFD+X1F1Xl0TZs0eFR0YVSoyf4oVuyU14wpV0dm4PMze7SrhI9LYLHY48VwbWZ7U9bmBeo3WhWEUr072GImc6bLpch3hTztR3m7vmys43I79iwUI9s/vmCFtnguC4AFOBB4B0HU9pOt6O3ABcFBf+p/A/HT58MjCnQkHfQBvb2zg4YU70+VOdJq3Jxf0Afzb+BYLo6iaytfe+lrcoA8grIV5cceL3LP8nn7wLDL7vv99fIsWgaKAqqI2NaHW1/cK+gCU+nr2fu1rKC3GRALM4OsM8t5jiQV9AB2Nft7/d/SgK928+eAfYwZ9ALqmsWP5Yj5+OslnOkU0PbA6MbEWDQJrmml/Y1f6ncqQ4TD6q38MfrA4fqNXPjJsP/TMPdGDPgB/F+Gnf2/Yfse6xyMGfQC6GqBtyb14t79pyLau62xY+ANaaj/sE/QBKKEO1i/8PkFfgyH7AGs2//WAcmcbYaWbTm8NwVA7mhaitWMz7316g2Hbrf79PLb6pl5BH4Bf7eSxNTfR2F1j2DbAl5ffGTXoAwhqYS5b9jvD9m9Z/x4fNtVEFZG5b/ti2kJJirQdxq/Wr4oY9AFs7GznB6sS+G1EoSuscNOKzaxo7WSn138o6IOervzxmjpWtRhTawXwKxq3Rwn6AFTgSx8bfy7f2aCwZKdKQIGgAmv2ary0KnUK7BuXh9m5oW/QBxAOwMKXUycmpYV09j8XxFejEWrWaVmg0LnWnPiKVh9CebM9skDMtgChl/t/rJhK0hmyDgaagH8IgrBKEISHBUFwAcW6rtcdaFMPGCsCkwD/XpS8Gtezy2vT4EkcjJRzGAB2dOwgoCanhPXh3g/T4ksidC9ZmnBbPRzGt2RJGr2JzOYl9Umfs2NVPKW49LFr1YqE2275dGEaPYmOHkpOzsu/IfHJoQwZUkT/9I/L1ifUTDeqnli7JX6bRuOqmIkEdf69nxiyHejej7+zJnYjXTNZziG2b15fLf6AsffPttZlqHr0wfqWlkWG7B5krz9+P1Nr0PfOcIANnY1x271Wl8DzFYWlLbH93+PrpilgLLBc09aJT40dXLyyL/7fF42P6uOrpSZTquxINtX1nazZtD91ytYNe2M7FwpBKJiaNLNAnYZ2xNfYvcPc36Isj62Gq201PiFxNJDOwE8GpgAP6bo+GeimZ9vKIfSeBMOI374gCF8XBGG5IAjLm5qMDXQnVuUkfc74itQkbSbFsHn9f00DlLnKEJJUEx2WMyxN3sTHUp6cQqt1WP/7Wj48J+lzcooGZussQE5p4ve0oMrcVhfDJLnDw1I8MMqzGf6n6Z/+sSAnIWcMb8m2x1fAwxFbXCYW1rzhcdtYcgYbsm1zFCBb4wtlON3GVZQ92bHPlWUnNmuOIdvFrth/d7HLnPqzU4y/jdCeQJtIuGQrhbb4793jcowrb5Y7Y2/jzJJlcqxx5CejMMjliNvNTMg1LsIyPje+X2Y2Mha7+/7ei92pSx/JzoltSxB6dPdSgTVP7HMzrAXmQhuxOvb9FwpS5PwAkc7Arxao1XX94DLKc/R0dA2CIJQCHPh/xGkRXdf/puv6VF3XpxYWFhpy4K4vTMBhSfxPzLZJ/OqCsYauZYqx50MCHVAvKmekx5cYZFmzuH7y9Qm3L3IWcfP0tKVvxqX8nnsQXAkM6gWB/K9/HfsIY3kuZiiu9jBkchLPtwDnfnti+hyKw1nfuhFRjp/TYXNlcfrXv90PHvXFfWZ1wm0Fl4XcCwZuciLD/yz90j9aE1HszDU+2SlfEb94unyh8e2M+XN+hGjLiXrcVjIF97jLDNkWJRvDp/0UyRI9MC0dfgnZ+WMM2QeYPOYGPNmHB2ifjVBF0cLsSb9ANJgjV50zgZMHfZVIIcDsiosZkW9ujPDnifHf33+daOy7lQSRn446kWw5+gB7bHYRoz3Gxn4At46djE2IPP6zCCI/GzsZi8EJj0qXg28Mr8IW5fxKp43zK4yXMSl3WZhTGFtN9lujjP9uz5pgIe+woVGWDeZPSV1Jo3EzLLg80YO/iXMsKdMpkLMFCuZaEA7EYo4qkdzp5uRL5HEuqIpyP6wC1gvyTdkfaNKt6rkQuFbX9S2CINwGHHzUWg5LXs/Tdf1HseyYVS1bvbudT3Y0IosC2TYLBR4r4bBOuz/IvvYA+U4rM4blM64sft2atNK0Df75BfBG2BojuMDqAGc+3LCop0TBAOFX/KxuXE2+PZ8d7TsAmFw8mZ1tO/HYPAS1IAXOAiqzKk0n2JpF1zSCW7aA1YolPx9kmXBTE2pLKyhhBKcL25DBSFkJzFynEV9XiO3L69m/o41QQMPhkhk1u4xNH9chWXQsdpnKUQUMnmC8I0wVmqbSuGsXtRvXMmLW8bTV7UfXNHJLy+lub0OyWCgebE7O2iyqohLc1IrgthDc04HFZcNSnk24zguygOSyIbosWIuMJ/dnSA//Q6qe/dY/Bhevgo+OaGOzIH3zS8g2Y6sevewvfQuWvA6SAFYXOFww5TRso6ebtg0QbN2Ob/9KAvtXIGWVkDXoeKy5Q5Cd5gdgmhoiHGxDVUI07n6brNwRSBYn2bkjka2p6Re6/Q3omorNloOua3i7a/G4hyKJ5lcO/IqXYLibTc0fU+gcRJl7BE5LaiT/AV7Y9yl7/Q14Q0FqfY04JRuT84bxlUGnmrataBpNwW42tDewqHkPTtFCsTObM0qGU+gwvxND1XV2dHXQEQrRrYYRgFKHi8FZbsNB3+H4FBW/qpJntbCmrZM9XX6mFHiocKVmV05HSOWj/V4skkiuRWCPN0xAE7liuDslY6tWr4qmC+RlCYhpGKv5vBq6BqGASrdPR5YECsskpDSUTdNCOloI5KzU/R1ah4K6OwDZIoJPg0IrUkHqglajHO2qnt8GHj+gWLYTuJqeVcZnBEH4GrAbuCTNPtDiC/Dq2nq6AmFCqkanXyGsaDhsImUeJ1l2CX9YZ2SxB8tA1PED6KyDB2J8j3o3BLsh2Az/vhiueqH/fDsCm2Tj5W0v89H+j8i35/P18V9n4d6FPLvtWRp9jeTYcji9+nQuHXkp+Y6BnRnRurpof/FFOt9+B83vB0HANmgQthHD6V60CK29g6zT51F2xx0DFqTqus7qd3ez9v1aVFVHlgWUsM7WJb23cG1cWM+8a8cwdGLa0mJjoqkqK954mU0L3sfqcJBTWs6OB/6IJFvwdbajKmE6Ghpw5eRyyS9+i6fQ+IynWdTWIN5P9hNu9KHrek+StgiEVTiQ3iBYRbJOrsQzt2rA/MzwP02/9I/Blev7Bn0AwTDqI88hfyt+IfCY9reugIXPcWhXqt8LHcDrfyO4dTm2C75lyr6mBPHXfopv5weEO/eC4se3+XmknGpKzrgXi8tcH7Np0S9o3fd+r88EyU5h5TyGT/0RomR8JUTXNTbvfIYtu54iGOzCIjvIcQ9n3IirUhL0ATR37+GTvc/QHeqgW3kFX6gThyWbU6q/yoRic8HZe42r+NP2FwjSO5fw085NZFucnF9mXPEU4IW9G/jTjsV99jO/Xr+Vh6aeh8diPIBSdZ2PGut4dvdOav3d6JqGT9OwSxLfGzGO08sqTPnuDSvcunorGzq8ZFskimxWrLJIm6JwVnkhRXZzEyqrmv3cvaEduwTfG5vDu7U+FjUHyLKITCm0MS7XeH3Jg3icIpvqNLY2qAiA3SIwtlzCmkjx6wTZvUUlHNIpGSTi90LDXp2SKt1UHb+D6LqOb5eG0qnjGiohZ6fOb7UmQGhpJ+wIgCqAS0CstCPMykYqNz9Zpu1uQ2vqRhych5jfvxPQaV3xSxVmVvzufmszf/5gR0JtK3IdLPjhKSl5IJMi5IffJFmUO6sUbtqcHn/iMOeJOXSGO+O2c8pOnj73aao91el3KgLhhgZ2nHU2ui9+orSYl8fIT42JBJjlyV8toXV/d8LtZ8wfzNQzjeW1GEXXdR774Q207k1cqOGKO++nqLp//QTwb2qh5Z8bE25vqcqm+FuT0udQhqT4X1nxSxWx+sfg8nXwXnz1QtvN1xm6dmj5O+gfPR27kacY27XGirhrSpB9z12C2h1dwbDiS68jO/MM2V/04pkowehlEkU5izlfeM+QbYC3Fl5Lc9u6iMemjvsBI4eYi+uX7X+VZzfeHvX4jLL5fGHMTwzZ/vOOl/lP7fsx21xcejw3jbjYkP1b177De801Mdu8c+KVuGRjgfdNKxezuDV6/uuF5YP4wegJhmz7FIWz3l8eUfQRwCoK/HnaWEZ7jK0Yv7K7i7s3tsds87MJucwrN74ires6f/8oxK7m3n9FYbbA9XNt2EyWdmhtUPn4tRCRQoyCUpHZZ1lNT7bXvxzCu6VHyEWwQPllNuwl5hdvwu+1o3wUfYxrOScXeYbx3OXweztQF+3p+YcoYLl4HNKIgoTPN9tHfn4LUSTI35Ioz1Db5ueTJMo/pIx/nJX8Od66+G3SwPqm9QkFfQA+xccTm59Is0fRaX/6mYSCPgCttZVQbf8ruvo6Q0kFfQDLXqlJjzMx2L9lU1JBH8A7Dz+QJm9i0/F2TVLtw3u60IIxJOkzZPi8kkDQB6D5k1NrPoi+4Nn4jTqMy877di+IGfQBNC+MHvjEQg37YgZ9AJripWnPu4bse7v3Rw36ANZuediQ3cN5a/tDMY8vq3vFsO0naz+M2+b5uo8N2fYp4bhBH8Ddm43Z39zZHjPoA3hpn3G12cd27Isa9AGENJ2navYbtv/glvilIB7YbLxcBMCuJq1P0AfQ1KWztta8wue2dUrEoA+guU6jpd6ELCkQatEOBX0Aehjal5nvx/WQhvJJ3/IuhxN+3/i914MK6tK9n32g6SifGH8WjXDMB37JqlQHlNRJ2iZMOLmB/0CSbDmHkBpKkyfx0cPJXVsPpK62TKJoavIvv4FYpVeV5Gv8qKGB+e51xUCHoh79Ox8yZEgbmsHnP93vIi3+O0SPVCwsAXQ9sfeEqhiTblfj+K7FKMWQ8DX02ANdM32FnkBxWaPWo9XuOxKfamwgH0pg4GfmyQ0mYD9k9DcFaAl8b6rJ316sbjIVw2Atjg2jFWQOokewryspeB/pxH8fmhkvaHpf+0bGLCY45gO/+ZMSlwP2OGROHjkAeUlXvpr8OfLASPpPLZmKJcHcBEmQ+OLIL6bZo+h4LroIElCgBBDsdmzD+l+QJCvXjtOT3FaWMceXpsmb6FSMGYczN7ntVCdfaWz7mFncJyeXsyfl2xGdn2955gwZIjJpVELNRKNiFJNPi9/GZryvcg46GdEae0tV/gk/NWRbtmYhiPFydWSKB59jyL4nu5osV2XU4yMHm+8bT6j6UszjowpmG7Z9auGkuG2OzzWmgp4lWxmXHX+sdfPI4w3ZH+fJZWRWbIGbOfnGc+WvHBx7XCkCF1UZt3/p4PhbOL882JyAz9AiMWIJh2w7TKg0Lx44ZEz0sZc7V6Cg1Fz4YSsSsVceZkMAzxTzsiWCTUSaHFtYSJ5lfJun4LAgju+d2iVNN5dvmrQPx3qOH8B972/jsY934QupqJqGon022+O2yzitEtMH5/GrC8aR40ydpG1SbHkLnkxwv7/FA7fsSa8/MegKdXH1G1ezvWM7dtnOJSMuIaAEeLPmTbrD3dgkG7PKZvGtSd9iaM7AqjuG9uyh7he34Vu1CsJhEAREjwdLeTnBrVshHMY2ciTVTzyOaDefLG0EVdF4+b5V7N8af/vApNMrmHNR/5edAAj6fHzw2F/ZsWoZsmzBlZOH39uJrmsowTDhUAAlEEC22jj/Bz9h8KSBS9PybW6h/b/b0byhHmGXg/3bEa8725g8Cr4yBkEaWJWuDJ+RyfFLjnj9Y/CpV2F39NQA6w+/ZryOHxB87wlYHSUXzJGN7Vt/NGwbQPW30rr0z/j2LkIPdsDBTXZWN0Xz7sJZMsmwbV1TWfrqxYT8fbfluXLHMPbEe7DZjeUPAqhqkCVr7mTP/vdQtRCiKONyFDN2+JUMrTrPsN3DWVX3Fotqn6Mz2EJQ8RPW/FglBzPK53PGsP8zZfve7S/w5L6PIh47o3AKvxzzVcO2VV3jZ2vf5aOWvtvcnKLMnyefyygT5Rx8isKze3by39oaOkIhNHQ0QAIuqKjm+6PGG7YNsNvr4wcrN9EYCGMReuoC2iSRsTnZXFZdyki3OUXYp3Z28O8dXciiwFcGZ/FxY4AtHSFsksC1IzycX2U8+DhIIKyzvEalrbvnN5VlEziuWsbtSE1/2NaksW1NGEWBojKRcBisNoGqERIWq/lraGGdrg1qj7jLSAl7cWrWsnRNR13nI7ygDQ5uh5WBIguWOe6ecg+m7Gto6xt7xF2G5iFVJ1dRwGwf+T8R+EHPlgdFUZAkCUEQEASBcDiMeKDDkwawPEIvWltBUXq20Fit0N4OdnvPypWqQk5Oz78HmIPPjaZpCIKApmmIooggCIeOiSmQSzaLrusIgoCqqoiieOjfB/3Udf2o8BMgGAwiyzKiKBIIBLBYLIfuZSgUwul0Dnh5DABVVXvdR1EUCYVCh35bR8v9VBTlkI+KoiAfWP093Pej4X5m6E0m8EuORPpHXdcJ7dsHDgd4vT39SVYWNo/xWmCHEwqF0BWlp4+SJFAULFlZKXsXaJrWp49J5XvmYP+gadqh90MqxwRH9pepfvcctJ+O95nP50NVe/bVybKMIAjYbLaUXuvgu1rTtEP3PVXf7+F9/0H7qfL9oM0jv89U2j/Iwb8j1f3rwXFQuvrDg/fnIOl67iN9D2bRDuxHPfjcHC3jxaO9nMOA4w0qnHr3BzR0xc8VuHBSOX+8bFL6nYrEHWWgJJHrd/G/YNwF6fMnCpqu8bNPfsarO16NmwOQY8vh2fOepcSVpGJpCtACAep/8Qs6Xnk1oc3krjlzqHrEfLK9Ef77hxXUJbDaByBI8M37TxmQOjJ127fyxC3fT6jt4CnTuOjmX6TZo8gEatpp/kt0UYVeyAJ5XxyBc+LAlZ7IkCGdBO/8e/RjAHkebNcZU5cM7dmC/uzvIx47mMFm+frvEbON1chVfM3UPvMFUCPk8UlWCk74GVlDTzdkG6CzeT1r3v965IQhYNC4b1I19irD9oOhDj5Z8XPqmvqK7DjsRZw8/ffk5SS2HTcSAaWbpzf8kg1NB1flBI4rPYtLx5p/9766bxF3bI+u2OoQrLxz/G+RReMB8m0b3uPthsgCfIVWJy/O+bLhgfxLtTXcvXldxFHKILuT306eQZXL2Kqcput86eNV7Pf3HVcKwNySfG4ZN9RwrcCwpvODpY2saetr3ybC0yeXkWszNzHx3sYw721Uet0fATh1jMypY8ynPuzaFGb9YqXP8GvQSIkJsy2m1PO7Nio0vRdGOyg5IXJoI4CUBWVfsGErMh6ghT/qQPmgg8MVfA5l5LpEbN8oQfR8fsOngQ9d08ztr25IKOgDeGH1Pj7eFlsJKi1sfiO5oA/gOeNbLMzw0vaXeGXHKwklfrcH2/nO+9/pB6/60vLwI3S89HLCGcTdn3zS076f6Wz2JRz0Qc/45K1H1qfRo+g89YuYdaR7sWvlMnYsX5JGb6LT/HAS90fRaX1yC2pn/wv7ZMiQboJ/eSp+o9YOwyIg0YK+wwk/+jNDtgHq3rwxctAHoIZoXvArdBMCYus+vCFq0Aewe/1DqIrxd8OqjfdHDPoA/IFGFi7/iSkBlnd2PnxY0Aegs6LudTY0LTBs8yCxgj4Avx7ipxv+Ydj+R401UYM+gKaQj99uXmjIdlBVowZ9ALsDPm5fv9KQbYC/bdsTMeiDnmyC9+pbeH5PvWH7j27riBj0AQQ1uGmpuXHqriaVd48I+qDH93c3KuxoNKfu0t2lsfbTvkEf9NT1273FuP1wp0bDa4cFfdArQFO9PWUejKJ1KSjv9Q76etGtEfxPo2H7RwPHfOC3cGty5Rne3mj8x2qYT+/r/2saZG3T2qTa72hLrIZiqvGvWZP0OV0ffph6R+KwY3XyL/A9G1rT4El8NCU5hbVtyxalyZM4GFD2CtV60+BIhgwDTEdsWfKDKLVpLA9kInBS22tiN9AUwp37DNvX1PiKnV2tidcEPZLmttiTUF7ffkIJlkeKxJ6OyPa3NH9q2GYyrOow3r+vaIv/vS1rNVZiabu3I+7U9KYu4xMeCxpjlwEB2NhhvE9Z1RL7N7O725wi7J7W2BPie+Mcj0d7U+zz2xqN2w/Wx//Owm06WtDYd6vtSOB91fL5Lv90zAd+c0clt4XrvAmJq4CmjJNu7v9rGmRK8ZSk2o/OH50mT2LjPO64pM/JPt34liGjDD8ueeWvIZMSL/SZSiRrcsJHo2afmCZPYiNYknytCWCtNJ8onyHDUUd+TkLNLJVl6fPB6jR8qpw3LHYD0YLFbVwRT5TjizS488cZtl+YNym27awqbFbjeZaDcyLbH1t4kmGbyTAjz/g21Rn50RVPD3J8/iBDtodne+IObifk5BneRjqvJD9umwm5xlU3pxfE1nEY6ja3FbM6P/bdqS4wFxrkxtlmmW+iyLq9TPxMrC0K1gIB0WbsuxWHxVP6BaFogEQgU8QxH/jdcs4YqvISk5O+fGYV0wYbV/AyzNCTwZHkYP7yl9LiSjzOHXIul468FEmIv7+8yFHEn+b+Kf1ORSD/mqvJufRSBFv8HzFA1rzT8Jx1Zpq9inDdXDuDJiT+3ctWgVOvHJNGj6LzlV8nrs43cvaJVE9MbpIgVRR+c2LcjuEQFpH8y8cgZX++X+QZMkTCdm0CJQPKjCsnCpffGreN5ZpfG7ZfeuafQI4cOAqyg8K5v0GQjA+CJ576VwQxeq7OkMk/QDRhf/KYG6gsPSXisSxnJSdMvdOwbYDThnyNySVnIhx44QmIzKq4mJEFs0zZBbhr9LUxj7slJ78cfYVh+3MKqriwLPrEcJk9mx+MmmPItlWUuGXsJKQoHcGobDc/GzvZkG2Aq4ZWMNgVOTgTgfPKC5lfYbycw1eHuZkRJfhzSQJ3TzP+mwUYVCBx9gQZ6YgIQBTg7Aky1QXm8gedWSKTT7IgHfHTEgQYMlaiaoRx+3KWQMn5VuQsevp5gR6p1gNYcqHkfOP9uZglI5+V08tmL9wi1ssHZvI9VfzPqHpmyJAhQ4ajn4yqZ3Jk+scMGTJk+N8ho+qZAB3+ML96ZQOvr6vDH+7ZW2yXBbJsFnRA0TTKc5zceu5oZg0doEj+3d/AxwnO/jkK4ebt6fUnBqsbVnPLJ7fQ6G/EITkYXzCe7e3b2d/dUwtJEiRmlc7iwdMeHFC5/OaHH6HpoYegu0c4R3C5espkcKCcm98Pooh94gQqH3gAOdeY8pxZPnh8MxsX9q0jdSSyVWTGBUOYdGpyBcpTha+jned/+0sad2079Jkt203Y7+uT/zfy+JM454abBuT711Wdut8vRWuPkeAtAhYR+6g8cs8fhuTKFHDPcGwSfOFt2Nq3VtpB5O9+Fcme2M6IiPbvvT56Hp+nENu1vzVsG6Br5/u0fPxbCPfkTAnWLGRHPrK7nLzZP8SSZU41umXfx2xZfBuq8lk+pMVeyJg5v8NdYHyb5+F0dO1iy85n2N+4GJ+/AYC83DHMm/0AkmT83u9oXc5TG35FR7Ch1+cO2c21U+6j0m0u1eLqFXezyRs5z+6r5afxrWHnGrbdFQ7wzRWvsNPX3ueYBPxp4jkcl29uC/I+XzdP7d7B0tYmwpqGU7Lgtlg4taSMC8oHIZuU5lc0nUe27+GVfY34VQ0ByJZlLh1UwmVxirwngl/RuH1NMyuae+oQygIU2WVuGpfH+Dzjzw1Ad1DjxZVhdjVpBMKg6iCJcOIIkdPHmbMNsGdbmI3LFEIBQADZAqIIuYUik06wYLMbv/dqQKdjVRhfjYYWBtEKolXAXizinigjZ6Vm3KGs8BL+tBO8as8NsolI07OwnOAZEGX1VHHMr/hpms6cO9+nriMQvzHw4rdmM6mqnwOAbR/A4/OTO8eeCz+uSYc3MdnduZtzX0jsZT/UM5QX57+YXoei0HjvvbQ89JeE2wtOJyOXLUXo53qOi17azso39iR1zqyLhjLldGO5D0ZRQiEe+vpXCPnjiyEcZMSMOZz3/Z+k0avI1N76MYQTf6+JbgulN8/IFHE/Ssis+CVHrP4xuHg1fLQsrg3bzdcZunbMoO8g+eXYrvqlIfvduxfS9O4Pox4XJDuVX3kd0WIsj7CjaTVr349e5HziqQ/jLjBX6Lujq4Y3FlyJqvYdg9isuVx85puG7G5rXcbfV94Qs82vTnofu8VYsemvLr2LrREK2x/Otwefz1eq5hqyP+/Df9CtxRbJeGrGJVS5jOVANgcDXLHoQ7qUyEIoZ5VWcIuJ7Z4AP1q5mUXN7RGPXVJVwrdHVZuyf9mH+6nzR1bA/MusIkbnGAvQNF3n168E8EWZGz1huMTZE41vl9y9VWH1wugCNFYbnHV5YilYR6LrOrX/ChJsjNzHy26BqqttiCYLxIcXdqC8E1lxXZrkxHrRwG33NNtHHvM5fqv2ticc9AHc+962+I1SjZHSDIH4qlLp4C+rEw+mdphQ/DJL2+NPJNVe9/nwLev/7VKr39mb9Dmr3k4uUEwFNWtXJRX0AWxd2j/KcoejhdSkgj4ArTNMcGd7ehzKkGEgSSDoA1BbDPYniSh2thhX3WxfGb0GIYCuBvDufNew/Zq1D8U8Xrf9OcO2D7Kr9vWIQR9AMNSGP5Cc8vhBFux+PG6bN3Y8aMg2EDfoA/h7zRuGbG/ubIob9AH8ZcdSQ/YB3q3fFzXoA3irbh++JJWqD8enqFGDPoDX95srudAcUKIGfQDP1CSm2BuJ3c1a1KAPYPFOc+Uctq6OrToaCkJznbFrBPZrUYM+AKVTx7fLnCopgLI4+v1V1/jQtaN/0Swax3zgl2VLbjdrtn0Adr8anK0cCLJtnw/1QyFJBUoA0WVsZtQMRoqYysmqVqYAqz22ylgkBmKbp9HtF4LJYrgZMhyVJPpzMPC+7A9ES/xVAclqrAg3gBRnNUxKQPUzHrIUu38XRWP33p6Ab1mW9O5eshoUvsmWE/ub3bLxLYeOI5VFjsAqikgm+ihJEGIOoI0Wbz+INU5f5jKxQ8UW52s7UvQlWeQEhtEWo6qbCazkCSnI3BDkGNeRSPzdehRyzAd+I0uymZGgUqdFEvjJWQNQfuC6D5I/p8zcFgWj3DDpBuQYKmiHc/qg/i+PcJDinya3xdBSWYljfGryOZLh1KuSV+g86Usj0uBJ9464gwABAABJREFUbCrHTiC3LDnZ9DmXXp4mb6IjyCJibnKDBesgN7Yq49LbGTIcrQiXnhW/kSgiZRsMcBKQ5Gf0TGO2gbzZ0bd5AkiuYpyDjJeNGTYlxjZSQaJ81JcN2z50jUHn43KWRjyWlzMWm9XYu+e0wV8jVughChJzB19lyDbAeSUz4ra5Y7SB3UpAudNDtTMnbrtvDZtuyD7AvJJyBruiT1RfOXg4NhOpHTZJ5LLqyN8rwHVDjZcZAXBbJabmR+7LLAJ8ZajxMiBlORKlnuiRy3kTzS2AjJ8VO7D35Al48oyFH7ZCkayR0b83e4WIs9p8aCOfEX3SRJ7rGVD9CrMc8zl+0LMn+JU1+3lq2R5W7m5DlkQmVHjwOCyIQJtfYXRpNt89dQRuxwCJPHQ1wD1jgAS2HpzyczjpB2l3KRq+sI87l93J1pat5DvzmVs5l61tW3mr5i2CapAsSxY3HncjZw1JYNCRRgI7dlD/q9sJbNwIgoDr+Dko+/aDzYpgsxHath3R6SDn4ovJv/rqAfshN+/r4rk7l6FG2npx4P1ltYvkFmdx2tWjySnq/5VJAE1TWf3W6yx4/FHUcJjs/EJKh4/E29ZKw87t6JqGjo7d6eK8799C5ZixA+InQPtrO/Au2g+SgGiX0bxhEEHMsqJrIFhFJIeFrDllOMcXfq4TtY81Mjl+yRGvfww2tcCj/418cFAptsuMC3QABD96HpZH2fJ3xnXYxsUPIGKh+FppWvgrwi070AWwFY1Htnmw5FTjHvOFmOUYEiEc7GTL4l/S2bKmp6C3aKGgbA5DJ9+IbGI1sdffoPipbfiYhqYV1DevQNNCjB52OaOGJFBuIwa+cAdvbHuIdY0fEFaDaLqGLEoMy5vO5RN+jWTy3rzfsIqfbv5nn89dgo1Hj/sBg1zJ1Uk+kv/UrOKRXSsJ6r235o3JLuC+yefilM2Nx0KayidNDSxqbiCkaRTZ7ciCyMlFZYxwGw+cDmd1aydP1OynNRjCKork2y1cOaSCYUYnU47grX1e/lvjRRJ6yi0Md1u5dkQOLpM7f3RdZ3mNyqb9Cl1+nTYfZNvh0hlWSjzmd8D4vBrrF4fpaNOwWMHpEtB0KKmUqB5l7nvVdR3/Hg3/XhVdBdEGokXAktsT9KWqP1dbwiifdKJ3qhDSwCliOcGDVG5e/MYMGVXPBPCHVXIcFs4cV8oP5g1nXW0X+Vk2nFaJ8RUedjR5KfU4Bi7oA8guhuFnwrZX47edYmyWLVUE1SBj88Yyr3Ie61vW47a6mV02m1H5oxiWM4yx+WOPitkQ26BBlPz4ZpSuLrSODqyjRhFYswZLRQXdixdjHzsWx6hReM7s//p9h1NQns2ci0ey5v0a7E4LnkInkiSgKiq+LoWuNj/hgMagCbkDFvQBiKLE0CnTyCsvp3zkGLYs+hgEgUBXJ8OmziAYCIAokF9STsXogak1eJCcc4ZiHerBt74ZS5EDXQMtqCF7rIT2exFsMvbBHuyDczJBX4ZjGlthPsECNzR39j14xvGm7VtPvIhQVytsWQ4clrdTORrrmGmm7Ut2D3J2FVo4hKVkIkKgA120gMVpOugDsNjcFFWfSXb+eELBVpRgF5Kc1VN0LAX4As20tG3AKmcxfuTVVFecjs2aQ457iGnbTouHUwZ/lTOGfR1fuIuOQBNhNYAkyuiYn9Q/uWgiQ3aWUBOqR0SgwlJAWFCZXzqLKqe5WnIA55SOwq+qtAS6aQsF6AwHsUgSVw2eZDroA/ArKo0BH6oGM/KKsIkCnYqSsqAPoMpl56LKYnR0imw2RFGgwpl8akQk3tzrpSus8qWh2QxyWZAFgWyraDroA1A1qMoXmTzIRnegR6G0qUvDbU/Nc+/MEhk91YLdKRD067Q3a+QViTizzfsuCAL2MhHJ1aPirXSD4tWx5AopDfrCy7oQimXEiQ7YHoISGbHs6NwWnwzH/Irfm+vruP7xlagJ/JnTB+fy+LUzsZjd4Jwsmga/SnIvvmcQ3Lg2Pf7E4K5ld/Hvjf+O2abAXsAT5zxBaVb0bRDpJrBxI3uuvQ61tTV+Y4uF4UuXIDuMqUyZIRRQ+Pv3FiR1ztW/n4Mzu/9nnP575y/ZtTIxsQhBFLnqngfJS3J7aCpQu0PU/WYpCf3oAc85g8k+of/9zBCZzIpfcsRU9WxphYefj23AacP2bWOTicH6Gnj8jphthDOuxjrOWCFu7873aP7glljWKb/kBSzZxko6+Lr2sOKNy0CPLDRRMfoqBk/4piHbAJ+uvI1dtZFXQ3M9ozjzxEcRBWOrKyE1wL/W/IitrUsiHhcFmWsm/ZER+ca2Sz6x533u2/VyzDbPTPspVU5jq353b/6Y/+7fFPW4U5B452TjO3Ee3LaRJ3ZHFpgTgKdmnUx5jK2gifDHTbv4796GPp/nWS3cMWkE43OM2d/nDfGVhQ0RQ3cJuGKYm6uHGw9edzapPLE4RHcQZBGUI7RQThopc+Z444G3v1tn8dtBOlv7/gVFFSIz5lkN6RscxLtNpeH1EHqEXVKOQQLll5gLvAOP1qPXRFG/EcH6nVKkvIFbKMqoesYgpGjc/PzaRMd/LN3Vxitr4itZpZzfG8jZ6ohelyldhJRQ3KAPoDnQzJ9W/in9DsWg/je/SSzoAwiH2f+976XVn2i8cv/qpM95+f5VqXckDrWbNyQc9AHomsbL9/wmjR5Fp/W5bQkHfQAdb9Sgh82rgGXIcNQRL+gD8CWgzBmNJ38Xt4n+1j8Mm2/+8OfxrNPw1vcM29+w4AdRgz6A2k2PoUXcgx+fxpY1UYM+gLaOzezcncAOnygsrn0hatAHoOkKT2+4zbD9eEEfwE3r/mbIdlBVYgZ9AD5d5a87E+9zDmdPtzdq0Ac9dXy/u3KxIdsH2ecLRAz6AFpDYf64aZdh2z9e0Rx1vVYFHtveyW5vbOXMWLy4Mkz3gZ/9kUEfwEdbFLqDxheFtqwMRwz6ABprNfaZUA3VNZ2mtyMHfQD+3Tq+Pcbtq23h6EEfgAah54wp8R4tHNOBX2cgTIc/ObneHU3eNHkTA//n4yFqTkJ2env7wBWYBwjVJBcYB7cOQBkPoL3el/Q5HQ3JlVVIBY07k/8+u1oG5rlWmpK8p5qO6jPeiWbI8D9LApL8pogRlB1E9RmXzQ8HWuK2UUIRtsgmQFd3/LI7LR2xg5+Y5/rjlwLqCiU4+WmQ+kC7ofNaQ4n1Yes7jH23tf7uuG3awsYC+kPX8MUuE7a3O/EyYkfSFIz/3Nd2G//ttXjjB3XtPuOBn7cz9rndcY7HQguCGqeLD9YZn8jV9yfwXLSm+b2XZo7pwK8gy8bEiuQUs04fY2zLiCkmfKX/r2mAsqwybFJiWwzPqh5YYZfsuckVlc276so0eRKb8ackv8Vw3ABsSxw156Skc16GHmdckc0MruOS+w2LWRZkz8Ama2fIkBYMbjVL3H5x/DZW41vopQS2EToHnWTYfm7JrNgNBAtWh7FCzaWFMxDibOMcPuhCQ7YBxhTGVzMdkmtc/VtKYHg4t3CiIduljmxkIb79K6uN2Z+Uk481Tn81I89cjuL4nOyYJReOLzJeSmN2YezfTJYsMCnPeJ81ujT2vbfKUJpjfCtm6aDYz31JlXHxGMkhYC+P7X/2OOP2xVHx31fiuIHTWkgFx3TgB/D3r05j9rB8Iv0+RQFcVgmHLFLstvGHSyYysTKn333kogdASPJHfN1H6fElDk+e8yR59ujlMWySjavHXs0146/pR6/6UvzTn5B7xeUIHg+IYs9/shwxeMmaO5f8Kwcm8Jt+7hBKhiY+OMsptjHn4uFp9CgyTk8O5//gp2Tl5SPbbFji1PWrGD2OM6+/sZ+86437lEpsExMbrEnFDoq+ZWxwkSHD0Y7t/y6L3+jiMwzbt15zO8SpyWb5xj2G7Zd/8VmIUa/OWjiOwpPibQeNzqjZd+AuiBwcCaKN485+2rBtp6OIU2fdj8tRQs9QS0CSHEiiDZs1l2kTfkxezkjD9kfmz+Sysb+kOmcixa7BOGX3gfIOAqIgMyJvBldO/L1h+x8ef1fM41XWIn4+2vik9SPHzccRQ5znSxXjmZZnbJLTKcv8ZdoJ5FgiP5sjsrL5zSRzE5NOWeL+qWOpcNgO3HWwiQKldhtfrCrhh2OMi/f8fHIBY3N655BZRci3icwqtPHH6UWmBF4unmZl5lCJ8lyB0aUiVXkCNrmnfl9hlsA3TrYimhA3GjJWYux0mZxCgdxCAdkCCGCzw/TTLOQUmAs9Si6wkj1WQnLRk/R4ANEGxedbkF3G7YuSiOXLBdGjo2E2rGentz5mujnmxV0yZMiQIcPnh4y4S3Jk+scMGTJk+N8hU84hDrqu89BHO3j04120eENRE2ZF4B/XTOOkEebq0hjmDxOgM4m8tB/vBfvAFJ1+Y9cb/OKTX+BXP9unLyKi0Xtftdvq5slzn6Qqu6q/XURXVVofe4y2Z58jXFsLSoQ92ZKEa+ZMim7+EfYR/V8U/SDrPqplwZNbE2o7Y/4Qpp5ZnV6HotBYs4PX77+HjqYGBEFA10EJRspjEBhz4lzmXXc9srX/pY9D+700PrA6IYEXuSqLomvGI9qP+Vdhhv9Rgnf+PXaDebOxTTFWc1PXdUL33QBKFIEYwYLt+w8Zsn2Qxo9+hW/760fYlbDmj6TwlF9hcZvb+r59xT3UbX8mwhGJcSffR26x8TmI+sblLFh+M2HlM+0ASXKQkz2MIVVnM6L6IsO2D/LCprtYXvcqihZGP6wPHl84l8sn/MawKmazv41zl/4y6vGT8sdz57ivGbIN0BUO8oVPn8IbQTxHAN44/grcVnPqjP/atZWnanbQqX7W/+fJFs6rrOar1eYKuCuaxhc+WklruPfYYniWg7/NHI8smlvV0nSdHy9vYklz39/WBZVOvj8u35T9QFjn/Y0K+9o1hhaJnDhSRk5RKYSudo3lH4TwtvcUFbHYejZchYPgzhOYcZoVi83c/WleEKZjpQIa2MoFis+0YvGkZhOjujtI6KlG6D5iDCGCOMiG9YoiBPnzWwbqmN/q+cjHu7jrzS00xwj6ADTgykeXsb+9/4UzeP/O5II+gN9VpseXOKxqXMWPFvyoV9AH9An6ADpDncx/cX4/edabpj//mcbf3024piZy0AegqnR/8gm7L78C1TsAoj7A3k0tCQd9AEte3MmWxXVp9Cgyuq7z5K0/pKV2D0owSDgQiBL0AehsXPAeb//t/n718SCN969KWNVT2eOl6eF1afYoQ4aBIfi3BLYqvvOpYfuhR34aPegD0MME/2F8K2bbmn/1DfoAdJVQ80b2v3wNugmBmaa9H0QJ+gBU1n94PUFfZOXGePgCTby3+PpeQR+AqvppaV/HsrV3snXXc4ZsH+TN7Q+xaN/zhLVgr6APYN3/s3fecZIU5R9+unvy5hwv55yP4+DgjpxzUEBERUFAUEBRBATRnxFBREQUUCQHyRkOjjuOyznntDnvzs5O6O76/bF3eGFi9czucczjx4/edvU7tbMzXfWtqvf7Nszmrc3yz+Boog9gTtNqnt41Wzr+RRFEH3S7bp4xL7aDeDTeqNrJo1s3HiD6AJr1EP/evpn7Nlh77l/06fJDRB/AZm8X1y5cYyk2wK9WNoUVfQCv7fbxyIZWS/GfXxRk7madbQ0mH6zVeXdVcgzOhBB8+np3KQfTBGFCsAt8HRAKQlOt4NM3rRnrtCwK0bpQR4S6/Z/8uwR7nguQjBOMpm4SfLzuUNEHYIK5PUDgP/WWX6c3OeKF36vLqxJq/9GGXviDzpM/h9/TvLf9vYTah8wQu9tju48lm4533o27rdneTud8+cmPFdbNS1zErZ3X8yVHdqxahh5M7GG9acFnKepNZIJ1nSRatzi0x4sZlLd/TpPmsKUlPkfK0K5aufjxuC42yz+vOtZGEmXdiEA7gXr5SfbutY/HbNNUlVid1S9iV38cs83O6o+kYu9jeW308XhxdeySDFZ4ds8n0vd2xCiTYbXAzmtV0V1VZ9dZG0ebgpGF0qaOxN26D2ZeDPfuj2rkXyOoCzYe5Hy5ak9yxsDWJhM9hob0tloTaO1rDu2r0Q6BOuvCz1gZew4hdloogXMYcMQLv775noTaV+b1fBFvMnrpeKkEFVkVCd9T4LZ2JEEGe3l5Yu0rEv+9kkFuSWKfT4Cc4p7/jBaUJ77DnJkX2QQoVci4cyp2FcV2xD8K06SJTKF8MehUYsuK/Ry3ZcThLBoBd86AmG1cGYmNJfvIyoh9BDXTUyYVex/ZzujOlLlO+fcmHvq4rTljppIKV/SxtdRtbRyNNmI4k3BkMieGeUuhS/6Yqk2DzINO0eZ5kjMGejJj/+6qfNcBsGWFfw1bHK8dC7UsjvQUi8dUe5svd+/j4NZTh5HnscduCAwtzuD4Ib3wIPvB0sTvyRuU/H7EwYVDLqQ8M/6B8OS+J+OxJy5urFJ86y1ohfE5O+ZdcQXuUXI5LlYZf3Jf7M74n4I2h8q0c3v+b59dVMzQacfGf4OicMo1N6auQxFQXTbsgxLLfc29YAhKknIb0qQ5rLjinLia2T1yk2DlzO/FbnPBTVKxAYqO/wXdGV/hyR71NWxZ8uJpyKTbiDYN8uQOI68sRsmHCJQVH01ezvCI1zM9FYweKp8jB3DxyDvQlPDzGwWFr4/5pXTsfs7YC9J3jrhMOv43+42Pen1mQT/p2AA/GDaKLFv43G23pvHDYaMtxf/e4MjC/iej5B0993H3hMjzF02B20bLO0uqisI54x3Y9049PA44Y1xy8tydLpW+Q6LPaUZOsfZaxafaUQ4KkT9DS4rw08qdKAOjLyDbz+/5Re1kkpCrp6IoHiGE9T3sBLHqWqYbJp9vbWJnUye7Wny47CrCgMIsO/+YuwOXTeP3F49lYr9e/mM+Mgtql8Vud/0KKIq9UplKFtUu4qMdH9Gpd+LQHFw05CLe2PoGITNE/+z+rG9ez3fHfZf+2f17rY8iGMS/fj3Bqio6lywhsG4d9v4D8EyZTHD9BlwTJ5Ixbmyv7fbtz+ZldSx4ZTMBv4EwQLUpIARGSKDawZPpYupZ/Rk0oaRXRUrjnl3UbN5Abmk5gU4vHU1NNO3eSb/xE1k/71OCnV6GHTOD4UfPwO60lphvhWCNl+ZXNqPYNTzjilA0hY4ltRg1neCxo7o1XEPyyD2+L6o7bexyOPFldfU8nMfHiAYvMybhnD7R0uubepDQv++B1oNy4bLycVz9WxSLJhfC1Glb+wL+utXYsipQbS5snjzcfY7FnpmcHa3d65+hdttrgB0j1IrDXcDgybeRXTDScuzG5nVs3f0GgYAXjyuP/pWnoSiQlzsMNUadv3gwTZMlNW9hmEH8oU52tK2kf+5Yjut3OVqUcgnxsLFtD99e8Uf2P1jnxslFlcdy7cAz0eKoxReNRr+Pu9d+xKaOJrxm9/nAcmcGD008m1K39RqUphDMb6yjORBgZWszgzIyGJNXyOCsbNya9ed+RzDI79ZuQyDon5FB0DT59uBK3BEEZ6KETMEz29pp8IXY1hHCriqcWpnJaZUZlsot7KMrKGjoEJTlKti15M4rOtpMmmoNVEXgydLIyFao22NS1lfF6ba+5ySEwLtBxwgoZA5OjujbH7MmQGh1JwBKrgYGKDrYjspCcfTunlmPuHoqijId+CeQCfRVFGUccI0Q4jrZF+5JbJpKhtPGit0tfLSuHrtd5aenD0cIhVFl2VS1+Vmxq4VxffLQenPlv2VbfO0+fwjOka+NlAyy7Fns7tjNxuaNZNgyaO1qxabZyHfl88KmF3CoDtr97dA7xqNf4P18AR0ffIAwTWwFBbhHj0YRArWwgPZXX6VryRJKfvZTVHt8u8KponRgDqAQ6NhviFXoPmvuh6DPR+3OdvqOKsTRiw6UDTu3sXnR5xSUV6IbBrvXrgQB25YvoaujHUVVySkpYfDkab0q/MyggV7ng6BJW50XxaWh2m1ohW6Mli7MjiC+liDOfjlkjOj5o8hpjhwO9/ExFIiSj7JiHVgUfqGmukNFH0BHM8GVc3BOmGUpvt7Vgt62G8wQpreaQGcDhrcG3d9G/gTr9WKDgVZ87VsRQNC3E0W1k1N0Eln5kXfr4kUIk0CoFZcjD8MI0erdymdLf4HdnsH4kddRXmytlhyAqqoMyB3HjrZVVLUsxWnzUOjpiyFCaBaN2xtDbYekO3UR4PXq+VxYfgylbmuL5StaqtnU3oRX/C8prCbQyX/3rOG6IXI7rfujKgqVbg+z66owTEGN3w+tzZS63EkRfg0BHRSFGl+A9pDJyJxM9CRVSGvy6zy0vhW/IegyTFqDBtkODZ8uouyBJ4bboRAyus1dNEXQ0AHTh9gYWGR9QSIjS6GlHuqrBGV9BZpNwelS0JLkhqkoClkjuudtgSaDlsUGCMiZoOHIs95/tcyJI8+Oud0PLhVzWxeiw0S0GygW6xAKIRC72jADIYRfR+xsRa3MQRtX1iML+3Ht+CmKshC4CHhdCDFh78/WCCGs7ZXHidUdvxufXc7rK2Mn8uZ77My97QQynD08sTYMuDfBB6jqgbt63t0R4MFlD/KP1TEswvdy2bDL+Nm0n6W4R4eiNzWx5eRTEL44FuA1jcGffYY9t3fyXLavauTth1fF1VZR4bJfTJPKDbSCEIJ/33o9TXuiJ8x/gaJw2b1/pGyIfIFiWVpe30Ln/Pi/G87heRRd1SOPsjRx8GXb8Tucx8dAfTM88XLMGM7bviv12oGFb8G8V6I3yq/A+a3oDpGR6Nw1l4YPfhy5gTOH/lckZji2P631S1n9cXh9rqh2pl8wG1WTK0ljGAHem/ddWto2RmzTp3Qmx039nVT8fczZ+TRvbX7wkJ9n2vO4bso/KPTIOYDftvox5jRHd768d/iVnFwit3Bw/dI3Wd4W+Tmdqdl5//irpGLv4+kdW/jblvWH/FwBfjV2MscXyx8T/ve2Pfxzy55Dfq4Cjxw1mhE5mdKx59f5+NmypojX8x0qL59QbnnX7+nPA6ypOtRGZ2I/jYunyJdiCgYEs1/2EwjjT+N0w7FnOcnMTs6uWfPCIM2fHmj2Uniyjdzx1hbzzboggcfroevQ98d+Ri62aXK7GsI0CT27CnN7y6EXM+w4r5+G4oiuQayOkXG/80KIg60ZvxQ2eGuq2uISfQDNvhCvreh5x0Re+Ebi95g9fqKo+2WFyWOrH4u7/bMbn0W3YLctS/N/nopP9AEYBrW3357aDkXhwyfWxt1WmLDknR2p60wEdq1ZGb/oAxCCz158OnUdiviyIiHRBxDY0JIUG+g0X10O2/ExDtEHEGwKMwmJh1iiD6A5MWftA279PMbJlkAbXdUSOfJ72bz4/yJeE2aInWviW+AMx87qj6KKPoDdtZ+g65HK4sQmaPj5YFv4PnpDLXyyU74kQizRB/DLjc9Ix48m+gC8RoimgPw8xxCCf24N//4L4K+b10nHBvjPtvBzRRN4eGOC5bkO4o9ron8fm4Mmn9RamwO2dYmwog9g2U7D0pi4c6MeVvQBBLpgy6rkzAnNoKD5s0MftU1zrMfXP20PK/oAQh+2Ssc1tzSHF30AnSGMZanf0IlX+O3ee5xFKIpiVxTlVuDQZZTDkBZfYhb0ibZPCq09X+5AFkMYYWv2RUIgekX4Gc3NCbXXmxpT1JM4XjuUmHG139vzn1G/tyPhe7o64rOSTyqyY1Va96WR50s7Pn5Ba+Lf755AhGJPbvVO+RJMRqgz6nW/ZA0/gGCwLb4+mPLW8CEjQMiILBx9cfZBFl2kdmzviFYjMgaGMNFF5LG1PWRtHA1Fid0SslYTzx9HHdomv7WCF/5g9NcwLQi/YIw/WzCQnAFX6IRdYhMhLC/mCl+U99fCx150Rf9sCG/qS0XEK/yuBa4HKoAqYPzefx/2HDWggD5xlmhQgLPHylk3W+KSf/f8a0piV+2MKxwXd/uBOQNx2Xo+1yv3kksSal/845+kqCexGXF0YsdNRs3oeTOaAeMnoSWYBzn2hFNT1JvIKKqCUpBYSQfFraVdPdNY4fAdH4+J7xieY1BfufgFqX0WZQ45K3abQadIxy8bcnHU6wPGXCsdu2/5Cdi06HMPl7MAp0M+xSDDkcPIouMiXp9ScbZ07BwtdjrByUWTpON74jCe6Z8h71zpUDUm50d2xjynwppr6IS8yEf9vtbP2jzyjD4ZUa8rwOmV0dvEoiRHJSfCxzM/AzQLpkx9BmnRzHjpNzQ56VSaR8Ez4NAXyhiqolg8BqtNjPz+qkPlS4FoQwshSqUBbVLq53cJuXr2FlZz/Orb/fz5o808v2jXF4m3BZl2SrMcbKzzYQpBcZaLx66azKjyXqpnNO8h+PDn8be/O7UredEImSFum3Mbs3fNxti73KKiYlftmKZJiBAKCuOLx/PPU/6JQzJHwiqdixdT9aObMZqaQAjQNGzFxWg52eiNTRhtbageDyU/vY3c88/vlT7u473H1rBlcYyVaxVOv2Y0A8f1Tt3H9oZ6Xv3Dr2iu3o1ms2PoOkaYVVNV0zj5mhsZffyJvdBLEIZJzQNLMRtiH6FScx2U3joZ1WY9GTxNcviy5fj1NrHGx8Cjz0KLN3KAK8/DWSZfxijwyC3QGXk8ct7yT+nYAC1LH6V93YsIvQtMwRdL/LYMys95DEdef0vxd6z+O3s2Posw/nc2TVGdjDjmdxSUWzMYaevYzsoNf6exeTXBkHfv7p4AFPJzhnPi0Q/hcMjngkH3cc/5u19kWc07NHbtQUGhMnskJw34FkMK5M1jTNPkzM/upMUMvys6OXswD024QTq+IUzOnfc0zaFDn9MaCq9M/zqFLmviJmSa/GH9Sj6pryFkmtgVlQKniwv69OfCPgMs5ciZQvDbNVv5sLaJkOg2XMmxaVw9pC/n9rHuNvvw+lZe29VByDxwU6vMrfHrCQUMkqhZezBdQcHLS4LsbjYJ6N3TpL75Kt84xo7DYm3blgaDFfNC+DoEGdkKeYUKpqlQMUijuCJ5460ZEjR9FsK7rtvcJWuUjYLjbElZzDU2dmGs9WF2GoiaIBgCdbQHx1n5loSl2dKFsWQPotWPaOlCtAcg24n9jGFolbE1iNUxMl5zl0Mzh6ENWCKEeE32xePFqvBLkyZNmjRfDr5swi89PqZJkyZNmp6iR8o5AC5gOPDi3n9fCGwHximKMksI8UPZDqSapxbs5O7X16KbBwrcokwnGU6NRm+ArqCJosBZY8t44GsTeqejdye40zjrXji+5wtkh4wQ57x6Dnu8h7pZHUyGLYNnz3qWATk9X3Mw1NjIluNndjumxsA1fjz9//MkSi+VdHj23gU0V8WXqO3MsHH1fZGP9qSSHatW8PKv74jaRrM7yMjNZdzJZzD13It6qGcH4t/dTuNfV8bdPuPYCvLOsl5wN81XlsN6fIxYw28fFcU4rzhXKrZpmoTuj1LEXbPjuOlh6dXxUEcNNW99H7Oz9tDQWRUUHHUTnn7Wnoet9ctY++mPMMPkyo067i/kl8nvmi1a+Xs27wxvsFOQO4oTjn4Qh93ajl9Nx2ZeWv8bdrev43/JygojCo7hG+N+i02VG9d2+Or42uLfRLyuofDxjD/gkKwVWN/VwXmfPxfxulu18dHMb0nFBljR0sidq5bSctCpFA0Yn1fIz0aNo9Ql7469oc3L79dtY5vXx8EpeXeNHsTJ5fK76ACv7fJy/9qWQ9LPNQWmFbm4Y1wBHsldOd0QvLEiyLKdJob5v0+NQ4OCTIWTR9kZUS6/Kxf0C+a97acjnIeJAsMnaAybIH8SzAwJ6t8N4t1oHpKfby9QKDvfgSNPfsfSaAwRfKwOOg/K83MpOK4qRiuX320V/hChdzdjbm9BLc1EO34gxsLdmDtaUMsysZ06FDXO9DRZ4n1nxgKzhBB/EUL8BTiJ7oHufED+gH2KWbqzhTteXXOI6ANo8AbY0eTDGzAwhEA3Ba+uqObf83f0fEeflJggf3xn8vsRB9/74HtxiT6ATr2Tb7wt4ViaBLadeVZcog/Av2IF1T/t+ZITAEve2R636AMIdOq89uflKexRZGKJPgAjFKS9oZ65z/yLjZ/P64FeHUrjw/GLPoDOeVWYgZ43IEpzxHDYjo+BRyJPrL+gSt4cJfTwD6M3MEIEZ8fRhwjUvXN9WNEHYHRUUf/Rz9C94a/Hgx7ysmbOjWFFH8DaT38gHbu1fVtE0QfQ1LqWeUsTSO8IgykM/rXyx+xuX8uBM2DB+qZ5vL/1UenY0UQfgIHgR6sekY4fTfQBdJk61y55XSp20DS4ZfnCQ0QfdB+bXNrSyD2rl0nFhu4jpLct38jmjkNFH8Av12y1ZI6yqS3In8KIPgBDwGf1fh7e0Cod/+MNOou2m+gH6aagATVtgqc/D9LWJd//xR8Hwos+AAEblhkE/PLGx83zdLwbDhV9AKEmQfWL1ox7gk+EEX0AfkHwX/WWjGNC723BXFMHnUHMrc2EnlmBuXbvv7c0E3olfpd3WeIVfnl0F6fdRwaQL4QwgNRb0Egyf0viTo1vr+6F2njbPuj515RkXVNiFshtwTZ8cTizJRuzLbEcSN+SxSnqSXQ2LUzcNa5mS8/ndxp64i5lu9asSH5HYmB0hqQcOrvWRq6ZlCZNDA7f8bEtPrdOo1bS1Tgeu/21n8nFBvSOGOOxMPDXyi+EdTSvR5jRn21Bv1ypi807Y5e6aIyjZEI0mnxVtPgjv0frG1O7+La8bWtK46/rkFuU2ObtIGBGd71c3dZC0JQTH9u9XTQHo39uNrVHd4yNxvLm2Pnpi+LIYY/E1vro740hYHuDBWFWF3sQ3r1Z3pXUtzN63/Q2geGTE2ciYEJHlL75BaJN/r0xdxz0PPEfuOgsqjsQwdQuRMcr/H4PrFAU5QlFUf4FLAf+oChKBvBhqjpnldEViRu1TOon7yIlTW7PH4WUpTwzMbcqp+bEY+/ZYuPdL5zYVrxj0OAUdSQ65UNzE74npzi1xwDCodkSPy5U3H9QCnoSHdUtd+zIObgXvvdpjhQO3/HRGd/3VimS/PzHc8yvYohcbEB15cZs4ygYJh0/I2cgUe0HAbtTzvCtsvT4mG2yMq05S+a6SvDYI/evT/YoS/Fj0ccV2TUzGZQ65Y7B9vFkoMU4Xtw/IxOHKnecsdLjwqNFnz4PyJQfp4dkxz4GOSxH/qhkeV7so9flufJHJTPj+MqU9pWP7yyJfq/q7v6vFA4Fok0fbaBkyR+DVUsP+kwfdFxXyXeDPbVmc3G980KIx4BjgA3Af4E7gE1CiE4hxI9T2D9LzBpezDePDv9gtWsKdvXAR/6YihxuPUV+EJHmhysSv6d4fLJ7ERePnfIYblu85TEU7p95f4p7FJ5+Tzwed1u1qJCK+/6Ywt5E5vivDcPhjv9Lrqhw4U/kLbStcOzXvxlXO1XTGD3rZMac0POn3BRVIefCxES8Y1AOtjgG2jRpwnE4j4+2H8Rx1F5TUTW5iYb6ncgF0PfhOPc6qdgAxSf+BrQI5YBUO3lH/RBHnnx+rsNVwNCpdxBJ/PUdcz2KIjdBLSuaTEHO6IjXXc4CZkyK/f5Fw645+fqoe8iw5x5yrcjTj7OH3iQd+1fDr4zZ5u8T5OP/cUz08UEBnpp6oVTsDJud20aMxRZB/JW6XNwxSt7PwWPT+PmYwWRFcIO+vF8ZTsnvFMDEAhfn943saNo/08YPRuRKxz9ppJ0BheHfG5cdzh5vpzhbXphNOdFJtLXisgEqmTny70/BcXYcxeH7rzqh9FyHdF6xoig4Li0Kr44UsF9YiKLJO3raTh2CUp7VHS7Pjf3sEShle/+d78Z+7gjLpShiEa+r59XATUAlsAKYBnwuhDghpb3bi1XXMn/IoL7djy+oU5DhQlGgMMtJQDcQAoK6iUCQ4+7lyd/mT+Hpi8FeBIoJwX1HBQTklEPbNug3A74VOW+gp6jtrMXQDTa0bKDIU0S2Kxs7duyaHb/h77aUzqpM+Qc4Fr716zE6O7GXlhGqrcFZWYkIhgg1N2HPy0PLysKWn9+rfQTwtfmp292O3akR6Axi6lDYJwubXcPvC9HR3EV+aSa5xdbsra0ihGDH8iVkF5chMFGAkB7E7nThcmfgyszCNHTszp6v3XhwPwO729GDOqIjhJrlINjiQ/XYoC2Eo08Owh/C2T8XLcWra2kS40vo6nnYj4+B7bvgnTmg69C19xhRQSa2b12CZmGC+kX8LSvg83ch6IeCku7/PelynPnJKT2jdzZgGEH0jjo0uwd7Xj9UzY4iaSxyMMLU6fI1EAq0otmyCHbVklcyKSnjV0jvoq5xBQ57Jg57Bh5XCaYZwOVK3rhjCpOg0YUv1IECOLUMPI6spMR+bfc8VjRuoTK7hLZAJ7X+Jr4/+GwGZCen5vEH1ZtoC/poCQXJUG04FTuTisrpn1VgObYhBC2BAK1+P816gOHZuWiqSobECZZI8bt0A10IuoI6DaEAo3KyLdXA25+gIdjtC+DzG+S7bWQ5NFRFITNJY1ZAFximACFQFAVNVdBU0JJU17bLZ2AaAodLwQgp6CGBKwNsSSqfZARMDL+JoipoDgVT767tl4zvrRACozWEGTQhINBybaiZySkTASACOji0L/p68L+j0VOunjcBU4AFQohZiqIMB6wtVfUQLZ1BHvp4M2+uqgEhcDs0qlu7yHDamdo/nw217eRnOLnvkrG9K/xWvwYv711hC+0+9Pq+nLWdH8IvS+Eu+YR2q7yy+RWeXPskjV2NhMwQuqljYJBjz8Gv+wmKIDMqZnDfzPuwKckZmGXwzv+cpscfJ7BlC0Z9Pex/5l9RUJxOSu64g7yL5FYVk0VLbSevPrAcX2vkhGTNAWdcO75XhZ8QgtmPP8Kqj95DCEFuSRlCCFprq/7XSFHILS7l/J/dTX5Zzxea30dgSysdn+4hsKMVoqViuDTKfjwZLaN3vvstLS2sW7cOt9vN6NGjcTjSO49fQg7r8THwyvuwaeehF5q86H98HONH37T0uQs88Qto3u8Z0LrX/OuJ2wkMnYTz7O9LxwYwQj4aPv0lgfrVYAJK92K1o2A4xSf+HzaPNYHQuOcTti5/gKCve0zVHDkUlB+LHmiisM+JqBbFpbeziuXr/kynrwZVtSEAVdEoLZrKMRPvthx//q6XeWfrw+hmAE2xIRAMyJvAlWN/b7mG7plz76DJ3FsDsv1/P/90+Xq+UX4i1w+RLxBvmCbnzXuKJv3ANFgVOKajH7cMm06xS97xVDdN/rRhNR/WVhESJooAE0G23ckvR09kfIG1Y6o+3eA/23bz+p56fIbAo6loikK+0863BlZyXIm1Wm87vSFuWlBHS+jAzRkVuHRAJtcOt5aesGZ3iI826AR1KMpWyPeojKrQGFScHFHWVKezZqFOyC8wTQgFITMXxh/jIMeipg+2mDTODhJsEqCA3tW9V2LPhcKZdjz9rc87zcYQoSfrwSegUMN0qmhD3diPTU6tb8VpI/jpdsTaOpR8D7ZThqA6e2a+HO+O32IhxBRFUVYARwkhAoqirBVCpPYA+V5kd/xafUFOvG8OTZ3xOfzMv+0EylNsoxqW1j3wQIJvpWKDX/S8IcUvP/8lL256MXZDoMBVwCeXfpLaDkWg9eWXqfl5bBdKgPzvXk3JLbekuEfh8bX5eeK2+XG3P/umcfQdYX0lVIanb7+Z2q2b4m7/rfsfIb+8MoU9Ck/Hp3toe3t7QveU/98xqElapY2Xuro6HnvsMYLB7udTRUUF3/nOd3q8H4cbX8Idv8N2fAzM/gwWxzbkct72XanXDvzjp9AewximpD/OK+J7Fh+MMA12/nsWmBHGcEWj75UfodrkThjsWP13dq+LnBZQUHE8I4/9vVRsgJb2rbz9yWURr7sc+Vx42jvS8d/c9Bc+3fVU2GtOzcO9sz6Wjn3snJvRiW7AcX7xNG4b8TWp+NNnRy8zYlNUXjz6Ukokxd+ln31EVVdk86G/Tz6GUblyu666aXLZvBXU+CPPLS/oU8KPRsj5N9T4QnxtTvTF/UkFTv40VW5H/aN1QT5cF96g5IyxNmYMtbYjWrNTZ9GHkVdcjzvbQZ6kwAy1m+z8e3TPrKLT7OSMkRdRZlOIwJ/Dmyapg104r7R+ksH/n2Wwcz+jPgUcV09BLYn9ebc6RsY7w9ijKEou8CrwgaIorwFhlhAPL15fWR236AO4+43U26iG5S9TEr9H9Lz9vF/38/Km+I+ZNvmbqPH2gksq0Pjww3G3bXnyPynsSXQ+eSZ+IQUw+8kNKepJdPyd3oREH8DcZ/+dot5Ep+OTMDvmKbjHKosXL/5C9AFUVVWxY8eOHu9HGsscvuNjHKIPILB+i1z8WKIPoG6HXGygc/tHkUUfgDBoWxVe+MRCCEHVxqejtmmqmoOvY5dUfIAlq6PnjvuDzbR75T8qn+1+PuK1gOFje0tipW32J5boA3ilfoFU7Cpfe8w2ujB5fvcaqfh7fJ1RRR/AL9fKu8EubGqLKvoAXttTT6cuN0/787rWmG2WNskbBn+yIbIr5acbrc8t1y+J7ni6Lsb1aDTNjX1vy3z5+ADBt5sjXjO3+BHhangkgAgZB4o+AAH64vhKpVklLkkshDh/7/+9W1GUj4Ec4N2U9aqXSNLRXQl6Nw8ulfR2jt9hT4Jvz5fp3fxS/e0Pk65+qd6zNMARMj4qh2ueazzfh9TukKf+G5m6V1AOlwebJLK9/3L/1nzpf4GY3U/1OGc1fG+9/z30ugk/MYUQc4QQrwshrFVI7AHOGVdOQZy5Owpw11k9cjLnUG6SKCSqJCc5ORFcNhcXDYu/2Hyhu5DSjNIU9ijKa19/Q9xt866Kz60yFcy8LDEX2VlXDk9RT6LjysikbEhifT32a7Fd4VJB1qy+id9zfJ8U9CQ6U6dOPSC3qrKykn79rNm7p+ldDrvx8agxcTVzDpcsKZQdx5GnUvlyRRkDTui26YuEopEz9nKp2IqiUDk8uutpQcVM3FmJP0/2MWVsdFNXlzOf7Ez5+Mf1jXyM1Kll0D9vrHRsG7EXAy4oPloqdoUnO2Ybu6JyaZ/IrqjR42dQ6Y6eD3/36IlSsQGOKsihIoYnxPl9SsiwyR03vCkOx84pBYmVrNqfWcMj/22PH2Z9bjl8SvQYIyfJH8MsmGGPKZDyp1v7HRynRz4CrA5xWXL1BFDsGvQ/KFdQAdvknkmNiSvHr7ex4urZ6gvy8CdbeGNlDQjIcGrsavGR5bRx1IAC1te2U5Dh5I+XjKV/gXwisWXWvQ0vfD2+trYsuKNntoTD8fqW1/n32n/T0NVAyAihCx1TmOQ4cujSuwiZIY6rPI4/HP8HNMk6Ocmgc+FCmh57HP/WrRg1NYeau7jdlN55B7nnnx85SA/Q2tDJq39aTmdL5LmizQlnXjeeymG950AqhOCTJ//JivffQghBflkFQgiaq/Y7Jqko5JWVc/5PfkFeWXJc32Twb91r7rK9BaJNwd0aZbdOQcvo+YUUgNbWVtatW4fH42HUqFHY7b3Tj8OJL1uOX28Ta3wMvP4hrI+c86refJWlz13g3/dCY4TjisOPwnmmXP7gPoxQFw0f3U6gbgVir7mLgsBeNIriE36NzW3N5KKpai5bl91PwFcDCGzOPAoqZpBXMpXCypmWnUNb27cxb9mdeL3VaKqGQEFRVCpKpjFt/J2WzV0W7HmVtzf/Bd0Moio2QDAofxKXj/mNZXOXs+beRaMZ/ljmtypP5ppBZ0rHNkyTCz57hoZQ1wE/V4EZhf25edjRFEnW8YPuPLw/b1zDB7V7CO4d+00hyHM4uWfMJMbmWcuV79INntlRzSu7avEZJm5NxaYoFLocXDWwgmOLrZm77PaGuGlhPU3BA4/cqsDlAzO5epi1z/3aqhCz1+81d8lSyM/oNncZUJScOVtLg8HqBSGC+8xdApCVB+OPcZKdb22XPtRm0jA7SLBRgAq6DxQD7HlQOMuOp691kxSjMUjwyQboNKFYQ3GqaEM92KfHXrSIl+C8HYg1dSgFHuwnD0HJjS9X2eoYecQLPwDTFGxpaKcraDK8NIsWn45pdpdwaPIGcdo1+uZ5cPeQo05EVrwMr377f/9WckG0w/5n7XOHww8X9nTPDsAUJttat5HjyEFVVeq8daiailN1srN9J0Nzh+LTffTL6Ydd6/2JrOHtxL9zB6GmJmzZOfg2rMeek4Nn7FiM9nZcQ4agSq7MJa2PusGmJXV4W3043Hba6zsJhUycLjuBgE7fofmUDswlszfMh/bDNA02LfwcTbNhd7nQgzr5leV0NNWj2ZwIwyS3rIysvN4tkSFMQbDKS7ArQKjai4nA3TeHwO52jNYAWoaGrSiLzFFFqLavtpnK4UZa+CVGXOUcVqyD9z475Oe2W7+dnHIO816HNfO7V6iMABg6HHsmzrGzLMcG0LtaEMIk0LQZFA2bpwBXvnz9voNpb1qHoroQ6NhsHgzdR2bOIJQkLFyG9C5CIS/ezhqCoQ6ysirw+RopLZooXSNwf3zBduq921FVjRxXKSEjQK67GJuanLH38a3vsbp5O816G0VaDg1GB8cXjeLbg8+wHFs3Td7YvY62gI8u06A1ECDf7eTcylGUxrErGAtDCNqDAap8PoqcDta1tdLHk8XgnOQ4M+7p7GJLm5f+WR7qfEH8ZohCt5Ph2VlJKenQHgjxcbWXYpcNh11lU0uAUfkOxiZpkyKoC0DgC3bX71MVBYcteecNhSnwec3u3SybgsOVnFIL+wi2GaCBI1PD8As0V/JimwETsyGIqQhQFGz5dlRXajYyhBAQ0FFc8X1n08IvBq+vqOKm51YQz2951pgyHrpcfvvfEncn+CAqHAs3zE1NX6Lw303/5Ref/yLu9t8Z/R1+OOmHqetQFMzOTnb/4EZ882O7Zhb95CcUfvtbPdCrQ3n/8TVsXlQfV1uHW+M7f5yBqvW8WHn37w+ydvb7cbV1ZWXz7fsfwZ2VvNWxeOlYUEPbq/GbVXiOLiP/3MSKvqdJHWnhlxjRxkcjFEL/079ixpB29dyyCl57MGob9cIfYe8vl0Zh6n5qXruKUOuOQy8qGhWXvoo9o0gqNkDj7o9ZP/+nEa8Pmngr5UMulo4/f9ndbN8T2bVz1JBvM37ENdLxH1p4Nbs6Voe9durAazlxoPyYNrtuObdviG7Q9bPBF3NuxTFS8e9a8xEf1m+LeN2ByicnfEcqNsC8hlruXr0Uv3moSY0CvDbjFPKdcsclQ4bJabMXE4wyf752SB8uHyBX0kg3BV/7pJqGQGSDnT9PLWR8gdxCsGEKXlkWYumOA01eFAWOHqRx1ji7ZYG2Y4POyvkh9p982+ww9SQHReXWBFSo3WT3vwKY+/xtFECAvUCh9CwHzmJr8yP/k3WILYea5yiDnDgvL0ZJojg2tjUTenMDtAdQKrNxXDAaJTv657KnXD2/lAR1k5tfWBmX6AN4c3UNu5o7YzdMNr+VWLlsXJX8fsQgZIb45YJfJnTPY2seoy3QFrthCmh67LG4RB9Awx/+gBmQd8mSxdCNuEUfQLDL4NPnE3PXTAZ6KBS36APwd7Tz4WN/S2GPwiMMQdtriTkU+j6vwfRHdjlLk+bLSjyiD8DUJT//MUQfgPny/XKxgeYFD4QXfQDCoPaN70nHBtjwefQyE1uX3YcRiu4OGYn6puVRRR/A2s2PY5pyLoqr6z6JKPoA3tv2CPWd8o6hsUQfwG+2xFfa6WCCph5V9AEEMXl4k9zpJr+h88vVy8KKPujWItcsll84/9mKjVFFH8Ajm3ejm3IbK2/v9kYVfQA/WRSHo24Elu00DhF9AELA/C0Ga6tiO7pGw9AFqw4SfQB6CJZ8HMSUfF/2Ufta8H+iD754nVCToP49a+nVxg5/WNEHILYGMBZ3WIp/QDzDJPTaemjvfj2xp53Qh5IOywlwRAu/unZ/wl+8Tzc2pKg3UfD3fD0+GZq6mjBE4hOENY1ylsxW8a9bH39jIQhuiz4QpYKWmq7YjQ6ielNr8jsSA29T4oNMouUfkoHpDR4y2MRDsMab/M6kSfMlwWyIbF/emwQaopejMLqsjdciZlkkQZdXLp++tjE+07ZAsFUq/rrGOTHb1Hg3S8VONTs741sM/qRxh1T86q4ufGb0uUpDwC8VG2B9W3zjRVNQToQsbY69CG1lmbq6Nbqwi3U9Fl2dgki6OOiHQOLTngNjNEce5AP11kSluSX658KoTqJvlzcIB5WcE3Wpn4sc0cKvMs9NhiOxLeWzx8ttzVuibFLPv6YEJZ4SnFpiRyMUFKaWTk1Rj6KTMT0BxzFNwzViROo6E4HCPomf1R9+dM87peYUlyR8z+DJR6WgJ9FRsx0g4bjl7NfzR1LTpEk57vie11ppYQo7IX8sytNvRtTr9rwh0rEBVJsn6nVFseHJkcsl7Fd+YhytFNwuuff+6MroR1AVFAbkjpeKnWqGZMVnrPLNfuOl4vf1ZFBoj25sMzRLPs/vhJLY/VeBEpfcUdJTyqM7kgLkWkjhHByjePrgEmvSICNbQYtgm5CRDa7oX7uYuCsjP1M8/az1XRsf/b3XBifRZyHbiVJw4JuhDrBm2hMPR7TwUxSF5753NJ44xJ+mwM9OG06OuxfMSK6Znfg9p/8p+f2IgaIo/POUf5Jhi/1QAnCoDn5/3O97zeAl7/LLyf/Ot2PWjFEcDvo88kgP9epQjr9saNxti/tnMfHU/qnrTAQUVeWU7/8w7vZlQ4dz3OU9nzOpKApF14xJaK6Zd8lQlN4r4pkmTcpw3hhHSZU+ZdL5POp1sY9xatf8QSo2QO6E7+DpfwLhvtCKK4+ys6w9t8ef/ARKhHIRiupg9My/SLtu5mT1Z8Kom9C0SE59CsdPjV7gPRp9c0YyPYL4c6hurhz7e7Kd8oL+7aPuidnm5cnRj8pG46dDo+cG9nNnc2ZFYiWE9mFTVf4wcRr9POHnKhmaxiOT5XITAW4ZNZCyKKJOA/44Ub700jElbqYXRY6vAv88Vn4BeFSFxhljbeS4/7dOqiiQ7YbzJ9oZaNHZU1EUjj7Vgf2gXyE7H4462Wk5f7D0bCeOov/FUFygZkDGUJXi06w52aqFdtSZWWGvacdmYRsX3/w3HhRFwX7xaNSBeZDlRJtQju2EQUmLH/F1U2nuoijKDqADMABdCDFZUZR84HmgP7ADuEQI0RItjlVXzzRp0qRJ8+Xgq2TukowxMj0+pkmTJs1XB6tjZE942M8SQuyfIPRT4CMhxG8VRfnp3n/flqoXb/IG+Nqjn7OjyYddUwmEDAwBDk2lJNtJUDfpDOoUZjr5+ZkjOHlk7xQc54GjoHVD/O3vaIJeKEGgGzpnvnIm1Z3VX/xMUzQ0RSNkhhB7E6zs2Hn45IeZVj6tx/u4j7Z336P65h/B/nmeitL9vgkBug6KQsZxx1Fx331omclbyUmENx5awa418eXYHHPRIMaf1DtFvneuXsHbf7kPX1vUdRoA8iv6ctV9f02qdXO8CFPQ8PhqglviyyPJu2IEGaNTedQtTZqopHSMDPzuH9EbXHoazv59ZMMT+PP1oEfOOHLe8k/p2EKYNM77DZ1b3gUzdMA11ZVPwYzbyeh7rHR8gC5vFVuX/5mW6gNz5hyeMqac8SKqhRMrre3bWLjyNzS2HGzGZqMwbySzpt2Pwy5vzb9g9yu8sfkBQuaheUn5rkpuOfpZ7JK1/ExhMvPTHxMkfK5cturm/Rm/kYoNsLmtgW8ufTXi9RsHTOVrA8ZJxwe4f8Nq3qredYjJy6DMbH49ZjKVGfJjfm2Xn+sXraU+cODnUgG+NbCCbw2W/04B/HBBHcvD1PZ1KvDtoTlcOiArqePr2iqdD9fqmAJmjbAx3kItPEMXrFkYonaXgaF3T7dMEzQb9BumMWKiHdVCEXRhCOreDdK51US1Q+FMO1kjkjcfNjt1gk/UIxp1cCpop+WiNBmIdgNttAdtaO+W1bJKT+z4Td5/UFMUZSMwUwhRoyhKGfCJECLqfr6VFc2Rd72LLxi/Icnr1x/D2D65Uq8lzfIX4DUJO+27e94tc9YLs2jsit/o46kznmJckbWHtwyBrVvZduZZcbd3jhrFwJdfSmGPwvPp8xtZ/XFVQvdcesdkCit7NietvbGRf1x/VUL3ZOQVcO0jsZ3hkk3931cS3B6+6HAkKn59DEovlMhIcyhfwR0/S2NktPEx8NiL0Ngasx/S5Rz+eTu0xXYllhV/9R/+FN/OT6K2Kb/gGRx5cnl4erCDRW9egBEK/7zQ7FlMv+BDqdheXw1vzL4Y8yDBuj9uZyEXnPqWVPwl1W/ywrp7o7bx2HK5e+Z7UvFnzb2NLjO6hcggTylPT4lcDiMa02fHWJAAXjr6UsrdcmPdz1cuZk5DbcTrTlXjvZmnYZOstzfr/QVEswa6fdRATq8olop966I6FjdFNxG5YmAW3x2WKxX/YLY3GDw658DXu3K6nRHlcmLqs7cDNNZENoipGKQyeaZc/iPAnuf8+HcfqF1Kz7eTOTg54q/r17shEFkbOb5WiDbSYqKiBQ73cg4CeF9RlKWKouzzXS4RQtTs/f+1QOKuEXFS09aVkOgDeOjj1FupHoKM6OslEhF9AK9teS1FPYlO/Z8SsxAPrF1LqDbyIJEq1sxJTPQBfPB4dKe7VLDglecSvqezpXfcahMVfQAtb/e8o2uaNKR6jIxD9AEEtss5V8Yj+qzg2z0vZpvW5Y9Lx2+unhdR9AEYIXnr9t3Vs6OKPoCuQCNdkq7en+56NmYbn94qFRuIKfoAtvrkxswVrfHdd9fqj6TiA3zeFP2zGTANPq2vidomEgsbW6OKPoDHtuyWig2wJIboA3hzT/JKj3268dDf5tNNciVe9JCIKvoAqraamIbcppMwxSGiD6B1SXJKMpm1waiiD0Bf9uV2AU/1WcFjhRBViqIUAx8oinLAWUYhhFAUJew7vHcQ/B5A3759pV48w5n4r1ecJb8KIY3qgjBHNY4E8pypdygKh728LOF7VE/Pr+BodhU9Rr2eg8mULNpqhewC+SLJPY6mQIKDir1C/rhVmjQWkBojkzE+HkBeeDOD3kbRHIgYde60DHldbHPmSt8bC6cjvtg2WyTzl+hk2OVdKXubYkd8Y1ilR/53dKoawQh1/L7oh0tuLC12xj7+m+uQPyKsKaDHGMKy7Mk75pnlPjRWpuRUWNVAVbuPdkbCZgdFcttJUZXuLauD4sfpORg7vjt2x5QMa+Y3vU1Kd/yEEFV7/7ceeAWYCtTtPb7C3v8NuywjhHhUCDFZCDG5qEhu0pntsjOxb27c7TMcGj8+Tc5FyhK3JJDb18ucNTD+45MOxcHXR3w9hb2JTPHNtyTUvuDaa9Gye97S/+wfJH4M9vTvjk5BT6Iz9ZwLsSc4SI48blaKehOd7FMSz4HMmthLub1pvtLIjpFxj4+nx5f/5syVnGBPOzN2m/zEF+H2kTf1xugNNCd5E+Tdg/NKjyKvNHLZn7ySBEoCHUTfihPJyYru0Ne37ETskjPW84b/OGabkYXHS8UGmJ47MmabG/qfLRW7PE5Bd/tI+f5fOzi6q+bQrBxG5+ZLxR6QlcGAjOiC/c4xg6ViA/xgRG7MNjeNkOt7OE4eZcex3z6JTYUzx8kJV1VVGDYh+qbLqKNslvIT8489KL4G+ccmxz1eybGhDjhI9e7f1QwV24wvd/mnlOX4KYqSAahCiI69//8D4JfAiUDTfonr+UKIn0SLZdW17O3V1byweDdjK3PY1tDJ9sZOxlTkMLl/PvUdfna3dDGoKJOrpvfH1lt5PqYJv4xzd6x0Clwrl3eQDBZXL+aWObcQMkMcW34snUYnFRkVBPUg7+1+D2EKrhx5Jd8b971eK+UAYJome265lc6PP0Zxu3H064fqsOPo2w+hqXQtWoyWl0fZL+/BNVj+IW0Vf2eQp36xgIB378q2Qtgi5GVDsjn/5km9Ypiyj89ffp7tK5fSuHsHRiCAZndgGDpmKASqRnH/ARihECd+5zr6jBjVa/0M1nfS/PR69GZ/d2a5gHAeBY7huRRfNabH+5cmMl+VHL9kjZGxxsdASws8GiF/2a7hvPnbFn4LCNXvwfzP3eEvnvJtnGOmW4vfUU3z4r9idLUSbN4GRhB7wTA8FRPJHX8VimS5hf1pa1jBrnX/oa1+Kag2HK48Bo3/IQUV8pb/0G1OU1X3GZu2vUxT20Ycjiw8rmI01c7IwVdQWmSthm9A9/HelkfZ0DifoNmFbgQwhIHHnsUFw29nWJG1GroLG9dx09pHw157fuLP6JdlLVPnp8vf5dOWQ49EDvMU8vhR51ke66p9nTy/cxtr2pppDwbpMHTKXR6uHDiUmSXyCxL7eL+6nie27KElqCMwUVAYl5fNPeOH4tKs7QpVd4b4yZIGfLpgQIbK5g4dTYVTyz18bWAuuc7k7jrppmDhVh3ThGmDbdgtmK8AtLcY7NlqgAKmDgG/icutMmCEDU+W9Xl2oMmgZZGBI1chd7INNYk7oAD6Rh/6/HbUvk7sx+UimkKIVh11oAvF0bt+AIezq2cJ8MreL64NeEYI8a6iKIuBFxRF+Q6wE7gkhX0AQDdMMpwaG6rb0FSFyf3zGVqahdcfQlVUjhtSxIkjSnpP9EH33jgOIPbZbmbGXulLJSMKR3B0+dFsb9tOrjOXiXkTWVSziF3tu/CoHhwOB7muXEJmqFeFn6qqFF93HY02DfeIEbjGjsX7yScomZmEtm7DMWE8gTVraX/zLVw/vKnX+unKcHDeTROY89xGAgEd3W/g6wxiBEW3BjTA5gaXx45pCjSLD2QrVI4YybpPP6Ko30D8HR2AwNB1XJ4M/D4vfm8HA8ZP7lXRByBCJoYGuLTuokqtevdTyKGBIiBoQqad7FnWnNfSpLFAj4yRzrw8ImZrHX+UldAAmO5IJwHs0MdagXUAVCdCDyFCPhS7C81TgJZZgj2nn/x5sf0wjSBN1fPIyhtO6cCzaG1Ygb9jF76OXRRgTfgpikpOZn+K8sYQ0n0UFYwnEGphxKCvk5slZ0izP06bh9LMgVR3rCfDMZg+2aNw2zMYX3oKzhjF6eNhdM5AHGiHOHtm4aTYnWs5/rcHTmblslraReiAtU5FEUlZ4FSA3b4ONEXh2OJSunSDCfkFDM9JzjHZ0blZDMj0MMZmQ1XArkCO04FfNy0LvyK3jVPLPcyv7WBFi4lLhYFZdjLsGh5bcuaqTV4Tfwgq8lRsqsIxQ5I3X8vIUnF7TPxdgsJyFafLRm6hkrSFa2eBRunpGt7NIRpmB3EWK2SPtKM6rccXQmDWhVCK7ah9neirvOhLOlAHe3AOT01KkFnbAQ4NNT/1KUcpdfVMFrI7fkHdZMqvP6CtK1YaLngcGq9dfwxDSnoh16GrA35Xmdg9jly4fWdKuhON97a/x62f3hpXWwWFx059jCmlU1Lcq/DsvuEHeD+Mc2dUVRmxbm1qOxSBV/60lOpN8Tu0nnfzeCqGJu+YR7w8ccv3ad4Tf8L6DU88jzNCAd1UUv+PVQS3xv9+amVuym464jeYvjR8VXb8kkVUV8/tu+CF2K6O0q6e7zwB6z6L3mjYFJxnXSMVv3nJo7SvjGzeotgzqLz4BTR3gVT89sa1rPwo8o6notg55qI5KKrcJP7z5b9k2+7wrp19y05gxhT5cgh+3ccvPz0NPYwJi4LKt8bdx/Ai+d3W53Z8zAM7o5uz3T7ka5wjWbLp2sWvsaojugHL+zOuJPPgKuBx8tu1K3izJvJ4dXm/wXx/yAip2AB/WLuV16saIl6/aVg/Luont6u4oTXAtZ/Xhzv48wUPTytiVJ5cfijAf5cGWby9W9BX5il85zgnriTtmjXVGcx789BNjMwchemnO3FnJEecbf+bH/Mgj5vS8+xkDpHf0zLbdAJ/qg576mofjp9XoCVpx1UEdILPrkTs6TaZUseW4jgn+ufycHf17FX++vGWuEQfgC9o8IvXe2fiz+8k6rIFW5PejXj42dyfxd1WIPjNQvmBzQqG1xu/6AMwTarvuit1HYpAS21nQqIP4K2HV6eoN5Hx+zoTEn0AL/3qjhT1JjJmwEhI9AEYNV2EWo5Mc6U0X3HiEH0ARldsB8ewxBJ9ABsXy8UG2lc+EfW6CHXSuvI/0vHXz49eHlGIEFuW/lEqdl3T8oiiD2BXzWxpR0+ANzc9EFb0AQhMXt7wf9KxgZiiD+D/Nifu9gzgN/SYog/gmwtfloqvm2ZU0Qfw9M4t7PbJuTOGTDOq6AP42+ZdUrEBfru6OaroA/jlivhq/4ZjZ6PxhegD2NMiWLA1vrlyPCz/NPzJNW+bYMvq6E638dK2XD9E9AHUv2ctfujlxqiiDyD0QmLu9tEwlld/IfoAzFW1mDtj10q2whEt/DbWJmbFXNXSlaKexCI5NrQ9QUgk9qWq6ZSzS7aK3pj4F9O/uucFlbc58QmXnmCJkmTglXg/2xrqUtCT6Ji+OI5Kh8Fo7q3vfpo0hwFtiZdA6Rlin0jSO+THGD0Ye47gbd0oFbvTF7tfXf7o4iEaDb7oJ358UcpU9DbtofgW2hqDPqn4sdw891Hnl3vu+/TYY3DQlD9N1xyH03dbKDE38P1p8YUphxDmZ7JEe1u7vMl5nUBD+N/fqkG+2RpbAIum5IhXANF26Bww3M+SyREt/K6bFd1R62AumpTgcctkMeKC3nldCUYXJOYoeebAOFzfUoCzf39wOBK6p+x3v0tNZ6K95pAcEj3yXjm85495FvZNfFf66IsuS0FPomPLcx/owBUnzgG5Se9LmjS9TlZ8R621UtlyLamdQqiu3JhtMoecLh2/oDK28/CgCTdLxS4vno4tSp6dqjrIyxkqFRtgZr8ro14fmm8tf9NN7PGz0CaXGlPsiq98zjWD5E6zeWw2XDEKsxc5XYyVdPXMcdhxx/CE6B/D9TMaJ5TFzvM6rkS+rNPQUg3Xful8CjC2MnlmMZUDI8eqiHItEfImh89HdPe39kyyTYvt2Gk/MdfSa+yPNvKgZ69TQx2U2jneES38xlbm8stzRuEIY4ahKt0fdlWBbJeN62cN4oYTesnZ8dInSPhPccPKlHQlFo+f9jiDcuIT1BcOvpCfTIlq2JpSBr7xOmpubvc/FAWckXMFci6/HPdQ+UFYFptd45KfT0WL82x9XpmHc24cn9pOReDy3/457sTsQZOPZsKp8Zf+SCbFN08CW/zqr/DGcd21gdKkOcJwXhfH4sul8sLJ/qNHYre56W/S8Ssufgk1Uv6eYiN36o/I6D9TOv7waXeTWzKN/42/+09KFSpHXEV2oVz5HJczl1OO+TsFuYcaXTkd+Zw581kUC+Y0I4qO4bSB30c5aO5gV12MLzmFK8ZaS7P4YEb0+zVU3jzmXun4/512adTr/ZzZXNZvvHT8F445kWzbobleNkVhRlEJf5k0HYdk7ibACzMmkGMPn0s2IjuDvx8l7xZ908hcTiyNLOyOL3Hz07Hy4sDjULhmppNxfTSGl6l8Y7qDgcXJE35jp9upHKx+4b2k2SC3SGHi8XYqBibHU9JRoFJ8ug1lXzgVMoYplJ2b2IL/wdinZ6NO2k94H/S2KJM82MYkr+6v2icX+9fGog4pQB1VjOMbE1AyrP0OsTiizV3SpEmTJs2Xi7S5S2Kkx8c0adKk+epwOJdzOCzYVNvO1x5dQLPv0DO5CuC0qWiqwlEDCvjDxWMpyJRzkLLM3QnaC9+wHAqt20EnSo23hhs/vpFNzZswiX7GfEb5DP584p+xqz1f0kFva2P7eeej18TIs1AU3OPHU/7b3+DoJ2GykwTm/3czy9+PzzilqG8WF/9scq/U8lvzyYfMfvwRQoHYh+jP/uFPGXp0fMWjU0HdoysJbYsjx0VTyP/GCDzD5VwB06Q53An87h/RG5wwFeeUcVKxTT1E6M/fj9rGdsODaE45i3JhBNn9/AWYXQflGCsaqt1D9uivkztBvg5hU+1i1s25Iew1zZ7NqOP+RE6h/M5NU+t65iy6jS7/ofnO+TkjOGXGP9AsjI9Lq9/m7c1/oSN0oNFHjqOY70x8gNLMxNJd9scb7OKkz6ObuX024z40yV2zer+Xi+c/RyhCHufZJUP42aiZUrEBXti5lb9sXhc2+rT8Ym4ZMYYyt7x1/nc+W8GmzvBjoVtTee34Sbhtcu+NEIJfLm9kdl34+McUO/nlhCJskidVQobgw7U6W+oN8jMUTAG1bSYChWwXHDPEzhiLRz99HSbrl+o015uEggJjb+pcdp7C+GMd5BTI73abIUHj7BDeTd25lp7+KkZQYHZB9mgbOeOtSRvRZRL6sBVjhx/a9P9VWctRcV1XjuK2flhS+HX0j7dh7mlDrczBNmsgiqtnJNkRfdQT4LyHPwsr+qA7bdyvm3QGDWZvrOfap5b2bOf28bRELtRDE5Lfjzi46t2r2NC8IaboA5hbPZffL/p9D/TqULZfeFFs0QcgBF3Ll7Pzm1ch4kwITyZVG1viFn0ADbs6eO8fa1LYo/C0NdTx3t8eiEv0AbzxwG/xtSfmrpksWt/bEZ/oAzAEzf9ah9kLhjlp0qSawAP/it1o9iLp+KEHr4/ZRn/oRun4Va9ceajoAxAGZrCD1mWP4t2WgHvzQUQSfQBGqJ3Vs6/BNOSMFkIhLx/Muzas6ANoblvP3MW3S8UG2Nj4Oc+vu+cQ0QfQFqzn4SXfk44NxBR9AMfPla8pfPnClyKKPoA36jbTGpQzX2kPBnkwgugDWNBcz0+WL5SKDfDvrXsiij6ALsPk0rnLpeM/v70jougD+Kw+wO/XyLt6vrMqxKebdKpbBWuqTNZVmzR3QkunYGeT4NkFQXY2WRsTF3wQZM9WA1+HIBQA0+j+b2ujYN7bAXRd/rRh48ch2lcZmP5uMxfvBpOubYJAjaDhgxAd6605lAZfacJY7IUG/cDS2m0m/keSY1gYemsDxtIqRJ0XY2kVobc2JCVuPBzRwq+hw48vGP9kfvGOFnzB5Fnaxs3myJbPhxPV3mqqO6sTuufdHe+mqDfR0ffsSax9bS2BLVtS1JvIrJidWIkEgF1r5R/4sqz6MPG/446Vy1LQk9j4ltQmfE/Xenlb9TRpDlsC8bnP6c2tcvFFahfL9LbYtWq9m9+Wih3ojO06LIRBR9M6qfh1TcsxYlgM1jbIi+61DZ9Gve7XvbT4E38WJoIexwJwONpDATqN2J/NP2/+XCr+K1U7YrbZ7vNS5QtTDyAOXtgZex7UEpKfS765J3aZiQX18vaV66qj/90EsCFGm2h0tpt0tEQWdnoQmuvk4+/b6Yv4+lvkYwshMDdGWXBoMUhGipy58cAFLXNT8kpExOKIFn55nsQSJAszHLgkt+Ytocm7M/Uk+a58HGpi72n/rP6p6UwMFFdijlqK3Y69TK7YqhVKB8R2kDqYjNzUJv6Go3zI8ITvKezTO0dntcLEv0+O8uQla6dJ82VDzZFzZ0w1ii32c9yRL2fKZnPFd7zblVkhFT87s2/MNm6XrJsqFGXEiq+Qac+Tjp9KMmz2uMyXZxUOkIo/MbcwZhuPqpEfxfAtGv0yYo8xVmaSg7Nij/ElbvlXKMqK/e4XxtEmEk6Pgi3GCebMbPn49oLo99rz5WMrioJSEOXIpY2kpNooBZ6o/04lR7Tws2kqP5gV36DgtKn88ZJxqL3h7nenxKpckZzTmBVcNhd3TLsDNc6PjU2x8asZv0pxr8JT9usEXldVKbnzTrSsnp/8TDi5L+7M+M91Kwqcfu3YFPYoPIMmH0XliPg/c8UDBlPcv+dzUAEKrxyZUEkH18h87EU999BNk6anUL7/9bjaqZrkJPLEy2O3GTdTLjZQdGJ0Z0lbTl9yx31TKram2cgqiJ7bWDLwHJyeYqn42Zn9GDPsu1FaqMyY/Gup2ABHVZzP0PxpEa+fPPC72DV5z4Jr+sZ2e/3ZoIukYmuKyo2DI/cdwIbCcSVywm9MXj593ZFLmdiAW0eOxa3J5VQ9OCX2WHjbKPnx78aReVGLaThU+LkFV88zx9nJy+geJO0a2A6a0o2uUBnfV15Y2mwK446xRxR/IyZpeLLk5UfxiQ7U/bS34uALNeOqVMmdbC1Xzn5OPmSE75/tguT4AdjPGAqZe//KmQ7sp/ecq/xXwtWzzRfkrdU1BEM6QnTXcch22+mT56E0x02jN8DI8mxc9l7Y7dufv86EhjjOhf+8Fuy9t0voC/lYWrsUExOP3UNzVzM59hyeWPsEmbZM+ub0ZVLpJI6pOKZXTEj2YYZCtP73FdTMDIzWVpzDhuGd8ymOvn1RMzyYbW04hw7FNWw4WmZ89a5SRe22VlbPqaJ6SxOuTDu5RRnU7eogu8BJe2OA4v5Z9B9dyPCjynu1ny011VRtWkfTnj2EggECnR3Y7A5Um532xnqEYXLKd68nu0huspRMvKvq6VxShxACZ78sjLYQzoHZEBIYrV2gqGQeVYYtu5cMndKEJe3qmRjxjI+Bh56CzjDHl646D2eJ/K4TdB+NCv7z59Bef+AFdw72a3+PasEyvzu+Sevq5xBmEFfBkG5jF0cWis2JU3K3b3/8nQ1sXvJbckum4M4swzCCCN1PQcVx2F0Jmq6FIRBso6r2c+qbVlBeNoOOjh143CX0rzjBUjmHfbT4a6nt2MqWxmUYhOibO4oRhdNx260vZBqmwWWLfsPOwP+OodmAoRn9eHzyjyzH9+sh/rJ5AR/XbcUpVHQNdNPk7lEncFRR7B3TWGxtb+fd2t0UOZxs97ZT4PJwbFEJ/TKzpEXf/ry2o4a5jS1cMaCcuQ0t+HWdLLuTq4f0kTZe2Z8lDV28tasDTRG06yYVHgczSj1MKHBZnluZQtDkFeR6us1dOroEDhsIFHLcyZm36SGB3ydQNQgFu/+dnatid1qPL0xBoNEEBZyFane+X0Bgz03OfpbQBaJVh0wVfU0nCLBPyEJJoFRUzNcwTESrHyXXhRKjLuT+pF09Y+AL6vzhvY3M3dyAoii4HSrZLjtjK3PoCho8s2gX1a1+Th5ZzHePk3fAskzNuvhEH8BvhsJdieeGJYv51fN5ct2T+EI+HKqDam81QSNIh97R3WAP/Gf9f7hw6IX87KjYCeKpQq+ro+O99/CtWQM+X/cPPR7w+yG4N2NXgYyTT6bPn+OvUZdsfB0B/vunZYi9KQHeJp3Gnd2TtI76bmOBjoYAIb/R68Iv4Otk7tP/wtfWCkB2cQlZhUXUb9tKyN/d5xf/707OvOEWSgf1fF3EfXhX1dP60iYIdi9s6Zu7jWb8iw/M6wlsaaXwu2PQeuOId5o0PUBg8crwog/gX6/CbdF2pWIT/PS/h4o+gK42Qv/5Nc5v3mUpflfVYjo3v4PuraIdQFGx5w0gf/J1luLuw+HKxuHMYffaf3YvBuWPxOkpwOEpJL/saEuxhRAsWf0nqurmYtMy6eyqobOrlmConcbmVUwZK1ccfh+6ofPfdb9lR9tKQkYQgWBB1UtkOHI5b/hPGFM801L8Z3Z+coDoA9CBdZ07ea9mCaeWWVufeadmE6/U7GdqsXcM/OW6T3j26EvIdsgXQRdC8Hr1Dt6q3o1hmmTb7KCqvFG9i1nFZdw4bDSqhTG/ORDkmV011PmDrG1uJ6iALqDAYSPfZeeSftZSR1Y2+fjF8ia8+6ezNeksbOji78eUkeWwNmbVtQn2tJgMKFQpzFJxWjjaGY7t60Ls3mpQ0kfF5zWp2SnQVBg4SmPwGLvl+ZbuFQSqTYwuCNYJhCmwZanYcoTl2MIQGGs7MXcHIU/DbAxBo06wVsc+Kxs1gVNa0VA0tUePeH7xukfyjp/XrzPp3vcJGPH9jgMLM5h968yEX8cyDZvhrxIP0Lt73jXx5k9u5oOdH8TdvtBVyMeXfpzCHoXH+/nn7P5WAjbfTicjVq5IWX8i4W3x8++fzY+7vc2hcs2DM1PXoSis/fQj3v3r/XG3P+7ybzHlnAtT2KPwNL+4Ed/SMBPRSChQ+ZsZqetQmoRI7/glRrTxMfDuXFgZ2y3OKSn+As/fB3vWx2il4rzlUan4TZ/fR8e6FyNezxr9dQqOukkqNoAe8rLg1dMRZjDs9ZKB5zB0ys+l4z//1kx0I7JRhMuRz4WnvSMd/7YPj0ZEMVg5qvw8Lhwpt/j6wxUPs6BtU9Q2l5XP5MYh50nF/+mK9/i0eVfUNm8ccxkFTrnTOGfNeY/WUPi/K0CGqvHeCWdIxW7o8nPB3BVR24zKyeARySLuz29r4+GN0Z2pX55ZRqFbToDM26zz1spucx0FuPQoO+P6JG8f6NM3/LTUR553Z+bCiRfKn1rz7TKofjFIuI++Z6BK+YXyp3iELvD/vRbqIpgPKeC4vhStuOe9Fr7ogsUx8ojO8fvzR5viFn0A2xo7Wbm7NXUdisRfp/T8a0rQ7G9OSPQBNPobqe1MrbNYOOruTTC3MBCg/aOPUtOZKLz+l5UJtdeDJu1NchbXVvnosUcSaj/v+f9gmj1fJiEh0QcgoH1O7+2gp0mTMuIQfQB6W2wXwbDEFH0QdnYWJx3r/xv9+prnMAJxlm4JQ83mlyOKPoC6bW8QCsgtsFbXL4wq+gD8wWZaO7ZLxf9g6z+jij6ARdWvScUGYoo+gGeqP5GOH0v0Afx2/Vyp2CtbmqKKPoBO0+DjusRcyvfx4+UbY7ZZ29ZJwJD77P9jU+zP9B/XtEjFNoXgo3X/EzUC+HBt8tzsuzpFVNEH4G2F9hb550LL53rEx4pvm0lXlfy8w9zUFVn0AQjQ32+Vjn84cEQLvw5/4h/mtq747K+Ty+G/6woQNKI/SCPhC/mS3JPYmF2JiyOjpTX5HYmBHkj8MxqU+FwnA9NI7HVNXUeYX47PttnZG9/7NGkOEwJyz/aUE7NchEDEURYgEnooluAVmFGEYTQCwda42oVCciUFvMHYE3+BSIr1fG/hlZxzePX4xiqvLjmn0eMTFobkex/PsNmpywknIeDg7gcT2CCJhRFnrASnEwdghqK/hrAwnIt4SsAFv7zfKTjChd8PTkws8TvbZeO4odYS3aU45289/5oSlGaUMjwvMVt/h+pgYG7PuzsWXvf9xG5QFHIvvCA1nYnCqd9L/ChIYUXvWK9PPP3chNqPOeEUNFvPpxHbKhMvzZB1cu+UnkiTJqUUxmfnbyuWdAh0pbYMiqtiatTr7j7HYvPIu+yVD72EaBbA2YUTcLrl5gQDKk+NGhtAVewU5cs5dJ81NPYR1/4546TznUrssY1tJmTL+yL0ccUex24deoxU7GOKSrDF+L1V4PQyOQOZO0fHnlsWOOx4JHPHT6mIfQzyxpG5UrE1VWHKgAP7dfSg5I3Tmdkqrhhpa3YH5BbK5+HlTIjcX0eBgruvvLTRhnsiOnruw3a8ddOn3uSIFn4VuR7euvFYhhRlYFfBpio4bQo5Lhujy7M4dVQxlXlu8jx2jh9ayCe3zuqdjk68DPocl9g9vZDfB/DUmU9xydBLyHJk4VSdOBUnSoTBrSKjgk8vjV5kNlXkXXwxZb/5P9Tc3NiNs7MZ9OEHvWLuUtIvm+OviM8ERbHB1X/qvVy04y6/iklnX8DBkxnNcdBZd0Vh+iVXcPJ3b+i5zu1H6Q0TcIyIs36VTaH4hxPQetvRN02aFOD8zkUxS5uoP/iGfPzrHwAlesEu5y3/lI5fcuoDZI+5Ag6uH6u5yRn/HYpP/D/p2ABOdxGTTnsWu7vkf6FtWbizB1I54krGzHzQUvzzT3odt3Ofw7GKXcuku8KbSlZGH84/5S3p2HbNwU1Tn8RjCzcJVRhfcirfn/x36fivTb+HfDWysB/kKuFvE34gHf/56V9jsCfyBPoPY05hUJa8qH/l2JMpP0iBKHRPevt7Mnh++onYVLkp8Jj8bH46ckDYWn0KMDEvmxdnTJCKDfDTsYWcWxlePanAbyflMyRHPo/trPF2Lp5i5+hBGpcf7WDm8BhF9xLkxItdlPRVcTghrxjc+2n8glKFky5xWppvZY+yUX6xg6xRKp7+KlmjVbLHaBQcZ6Pi604UC46qikvFdV0Z2pRMlAo7ykAnFGrgVqDUhuObRWiD5E2HDgeOaHOXNGnSpEnz5SJt7pIY6fExTZo0ab46pMs5xOAfn27j9+9tILTfuWOVA/NCx1bm8Mp1x6D1RvH2fdyd4NbxmCvgwr+mpi9RCJkhjn32WHx6fHl7dxx1B5cOvzTFvToUIQQ7r7qKroWL4mqffdZZVPzxDynuVXjmPLuBNXPiSzK3OVSuvv84tARqviSL6k0beP4Xt8Vl2OJwe/jG7x4kt6S0B3p2IL7VDTQ/HZ+pBYBW5qHspkkp7FHiVFdX8+abb1JfX8/gwYM555xz8HjSRebTJIZhGOh/fDx6I03DeWsCDsj7EWiqgX/dGb3RGdfiHCE3Rwl1VFP79vUY3powVxUKZ95D5qBTpGIDBLsaWT3nRnxtW8Ne7z/mOvqMlCsQv4/5y+5h+553ODSXX+HMmU+TK3lcMqB3cecnMyNetylO7jr+HVw2OVfMl3Z8yh93RjfXeWPqLyhyx3m64iCe2b6Ch7Yvjng9Q7XzwcyrpGIDbGxr5erFc8M6KNgVldtHjefk0grp+OfMXkxLlFy/O0cP4pRyuWPCnbrBmR9UR3R/uKjSxQ/GyKclNXlNHvs0SIvv0FcYUKhw8RQHeTGOO8Z8jTqDxR8FCRxkt2B3wIhJdgaMTI788O3e6/BpAArkH2sjf5q1HczAJ62Ys8MY7CigDnThOD8fJVu+/0II9E+2YyzaDYYABbSxpdhOHYpiS/3c7og+6rlwWxO/fnv9AaIPDjUDWrWnjXveWNtzHTuY/5PIL1r9VPL7EQc/mv2juEUfwK8W/grd7HkzkrbXX49b9AG0v/km3nnzUtij8DTXeOMWfdDt6vnB473zWX3x3p/H7dIZ7PLx/D09X8NRCJGQ6AMwanwY3sPH3MI0TV588UWqq6vRdZ0NGzbw/vvv93a30nwJiSn6AAxD3gAklugDeDsxN+D9afj4zgiiD0DQ+MldhDrknBkBNiz4RUTRB7Bj9cME/U3S8XdWfcT2PW8T3sBN8P5n10jH/r95Z0e9rosAf1siHz+W6AM4e9E90vGjiT6ATjPEezVbpONft3R+ROEUEia/XLOMOr+cQ/ajG3dEFX0A966J/LmKxZWf1ka1/Htpj59qn/y86t+fhRd9ANsbBS8tsWZ2ZhqCRR8cKvqgu5D7qs9DtDTIu3ruT81Le0UfgIDmuTqmBfMVs00PL/r2xje3+gm+Keeo+sVrrK3H+GwnhMxuJx9DYCyvwVgQ2+k2GRzRwm/Jzvj/OAu2yT/cLROn+9fhwOK66A/rcGxoTmwingy8cxO3gW5/590U9CQ6O9ck/rmTuccqAV8nejCQ0D3epoYU9SYyumSpi/a5h085B6/XS0vLgc+uXbt6ZkBI89UktEmupECqCTbGLhcRqJdfCOtoin1ve+Nq6fi7a6LXsA2FOqRjd+mx7631bpOOn0raQ/GNJc/sSqzc0T4ChkEgxiKlANa2yU3g36lpjN0IaAvKCajGQGxRtLYlsfF4H0IIGjqiC6OdjdZEmbddEGu60FyXHOEnwuhff42Fcg67Y7+v5k659/6L+3e1RnjtnvHuOKKF38S+8R9BmNJf0tUsGdh6x6VRhgnFiScsD8sfloKeRCfj6KMTvifr5JNS0JPo9B2ZePJ65Yie/6w6PRnYDjZxiUFmvnxiviy2ArmisJnT5Y/8JJvMzExyDzIlqqys7J3OpPlKoA0+PF1tHQWxxw5n0Ujp+Jn5I2K2yS6Qc90EqCiNbtpmt8m7orriuLfYc3j+XbPt8RmTXFQp97d1ahpOJfr0VgFGZudKxT+5tDCudtl2ueOA+Y7YaUcjcuUKiCuKQmGMj07fAmvSICNbwR6je3nFyZEfSpi32FUqb9amVsb+bKp9rBVvVyvDp3ZF+nmyOaKF39GDCrj1lGFoB32HDv5KjSzL4p5zRvVYvw7hjj2J3zPkrOT3Iw4ePOFBnFr8blI/nvxj7GpyHaPiIff883FNiF+kZp58MlkzZ6auQxEoqMhkxPSyuNtrdoXTviM/EbHCBT/7JUqcLmg2p4tL7rLmuCeDoijkfy2xhQa12IU95/Bx6VJVlYsuuoiSkhIURWHIkCGceuqpvd2tNF9CbPHk7mkKmiY5UbrirthtTrxSLjZQNOteNE/kXKbC4+7Cni2/aDN82t24syKLoz6jrsbhjm+SH44BlafQrzzyguKJ0x+Wjv3T6a9GvW7DznVT5F09v9/ntJhtXp4ax1HfCFzdb2LU6y5V4+yK2MI8Eg9OOjqioa0NhdtHjqfULZc3fd3w/mTHyLP/6cgB0s6VT84oi2rGe3a5k8oM+XnVlcc4yY4w5PXNV7hwsrU5m6YpTD3JgSPMa2g2GH2UnfwkCb+y8x0HKJm86RqqU96vQ821oc6IrIzV/k7sZ1tbfFfHlKBN6wOautdqVkEdW4p2dB9LceMl7eqZJk2aNGkOG9KunomRHh/TpEmT5qtD2tUzBmuq2rjvvY0s3tFMyDQZWJTJcUOKEMCW2g4W7Wwmy2Xn1+eN5oQRJTHjpYyHjofGFfG376U6frqp8+iqR/n3mn/jN/yIvf85GBs2ppRN4b6Z95Hl6J2jrP6NG9l+8cWw75y9qnb/1zBgvwUP5/Dh9P3XE9jiqfmXAlZ+vIt5z8dOYlc1OO37YxgwWt7Nywpt9XU8fvO1mKHYeQuVI0dxyV2/7ZXaiMIQ1D6wBKPBH1f7wuvH4urz5S7ImiZNJAL/fgVqo+QkXX0hzgL5FezA/d8HM8IzwebEeZM19+mu2pU0ffY7dG81aC4UBBhBnGUTKT7h16g2a7v1mxb9hrodb4IQuLL64nQXYAS9ZBeNo9+Y72Gzyx/H9Ada+PCzG2jzHvx8VygpnMzMqX/EZqH/a+vn8tL6X+PXOzCEwT4TmWxHEWcNvYnxpSdLxwaYPueHh5jh7SMDJx8d/zvp2KYQXPrZc1QFvWGvf6//JK4aGH1XMBoBw+Du1Uv5rLHui99BAY7KK+T40nJOK+uDXbKOX3d8k+8uWMX2zgPHGQW4uG8JPxg+QDo2wINrmnh5d3gjvUonPH1CcnaHFm/XWbRNJ9etUJajEDIVxvXVKM2Rf2+EEKxZGKKhyiAUBNMElxvsToW8YpXBo+043fJzA8MvaFsZwrvRRO8SiL2p/VljVIpPlK9v+EX8miDB15ugQe/+g5oCTFCyNRwXF6BWHj4nhGQ4onf85m9p5PLHFhLvr/jXyyZy5tj4j90ljY9+A3N/m/h9vSD+bpx9Ix/vjp6wvj/Zjmw++/pnKexReIJ7qth6UgI5e04nI1auSFl/IrF5WR3vP5qYOcF5N0+gYqichbYV7rs0sePFOcUlXP2Xx1LUm8hU/WI+IpBYcnf5r45B7QEb5TSxSe/4JUa08THw1iewZnPMGM7bviv12oEHrgMjhiOu3YXzxoek4ndVLaLu3RsjXlfdBfS9TL4I+uo5P6K1dn7E666MCiaf+RJKjHyxcOiGnxfePhERzn1iL057Lhed/l7CsQE2Ny3mH8tviNrm9MHXM6u/3FHbaXN+GLONS7HzyXFyZZDO/PQ/tOjRF+fuGjmT00qHSMW/eO6H1ISzldzL8UWl/HrcFKnYAKd8uJAuM/Lk8oyyQn42ZrBU7N+ubOKd6uju6dk2eONka+Lvg7VBZq8/dKy0qXDNTCeV+XJj4pzX/bQ2RH5vXB444UIX9jhyGQ9GGIJd/woQag4f3zNEofw8eWFmVgUI/L0uahvn9aWoJdby/KxgdYw8omc6Ty3cGbfoA7j/w02p60w0ZERfL9AWaEtI9AG0B9tZVrcsRT2KTNM//5HYDYEAHR8n9rslg0/+k7jj6dznY0/kks3C115M+J62+rq4yz8kC6MzlLDoA2h+PrZ7YJo0XzriEH0AgSWr5OLHEn0Aofh23sPRtvrpqNfNriYCjRul47fWfh71ur+zivZGOWfJPTWfRhV9AIFQKy1tcs/z1zf9KWabT3dGf/+s4hdyrpV+Q48p+gB+tyFxd26APb7OqKIPYE5DLfWS5Ryqff6oog/g3TidP8PeG0P0AbQnoUrWgq3hx0rdhEXb5V7ANEVU0Qfg90HtLrm5gW+HGVH0Afi2WNvM0hfEdssNze6dE3fJ4ogWfk5bYgnrbru8E9BXAZtqQ5VY+fTYe77wtOpJvGitzD1W0SR2mezOnv/aujxyx3WVqCnqyUc52MkpTtSM3lu9S5Om18no+Wd0PChxGIkpNitHu2I/L1RNbvdAi/M+LQGztP2xq7Hvs6mH53NNjTMFQJOcosZzhFNTFOmjnvHcZ2WU7qkRPpo/TYLT5y+IdwTWbHJjdTgXz6Rij+Pdt/d8CksyOaKF39UzBuBMYGL9szOGp7A3Ubj0ud553QTJsGfwtWFfS+ieysxKhuf3/PtacPV3Emqv5OeTcdTUFPUmMmdcPzbhe2Ze0fPv57iTYzu8HUz5sBFxu4AmC9VlQ81LfCKVf57ccaI0aQ5rZh0VVzPnCLkjaWTF4XiZLZ+TnDvh20SbStrzBuHI7S8dv3TQ+VGvZxWMJiuOkg/hqCiZjk2LLqizMweQndlXKv4lI2M7ap4++Dqp2ABuYovGEodcyoFD1RjsiX3vn8YmPu4AlLjcjMqOnrd9XkU/8hxyorvI5aDIGd358sqB8m6z3xwSe6G1r9v62HrSyPC/g9sB0wfJKSxFVSjrH71v2flQ2keu/+6+Kq7KyPfmTLS2gWM7Jiu6MlLAfnKupdfobY7oHD+A+nY/T36+g/fX1uIN6BwzpJBjBxfhDeh4u0I8v2QPpTlOfnfBWPoU9PyOzxesfAleiVOsOPLg9h0p7U405uyewwNLHqCmqwYVlY6DitBqaOS78jl/yPncMOGGXjH4ADC8nWy94AKMXbtAVVHz80FVEX4/wucDXQe7nZyLLqL0jp+jylqaW6SxqoP//mEpIX/0gqZZBU7Ov2UiWflyteqsYuo6//rJDbRU7cHmdGN3Ouhq33vkQVW7M7gBRVWZfvEVTLvgkl7pJ0DTK1voWlgTu2G2RuktU7E5j3ifqy8N6Ry/xIg1PgZWroN3I+dZy+b3fRH/lb/CtuXhLw6ehPPc71uKr3c20LTwLwQb16K6C1AEGF2NZA47h9xxV0rl3+1P3Y4P2bbijwjTIL/iWBzOfAJd9eSVTKWk/xkoqvy4YJghFq74HbuqP8IUOgoKpjCwaU5GDLqMMcO+ban/zb4qnl5zJ23+OkzDpMtoR1FU+ueO56yhN1KeZW1B66oFf2BDoCrsteNzR/G7cdY+O/evn8eLNYces1eAxyecy7C8YunYQgie37WVf2/fQofefSQ1S7Nxcd8BjM8rZGK+fJmOffH/tG4br1c1HGCAk6lp3DlmENOLrVn+f17XyZ3Lmgl3mPaCSg83jUlOndzdzQbzt+gUZSoU56h0BWFkuUaGhZIIALu36FTv0DF0CAUEmXkqmqaQX6JSMUBDkzydA915fp1bTbxbdHSfidEOwoDC4+xkDrM+lotOg8CHLYgdwW4LTMUEn0ApceK4IB81o3fnC1bHyCNe+AG0+oLsavaxp9lHboaDPLcdm6YypCSL+nY/TZ1B+hdk4Hb08lHPh06CxsWx2/2sDpy95yqkmzof7fyIdY3r8Ng9TCiewOfVn1PfVU+bv43zh5zP8X2Px6b2/mTat2wZjf/6F4avC2f/ftj79sNRXoYtLx/F4SC0exeeyZOxF8sPMMnA2+Jnydvb2bG6EWe2RshvoKoqdrtG2ZBcGna1M2xqGaOP65k6L5Foqt7Dwpefw+7x4MnOw+FyUTp4KKtmv097fQ2Dpx5DUZ++9Bs9rsd3+/ZH7wrR+sEOArvbUTw2NBR0QOxphww7jvIsMkYW4hlT1GsLE2nCkxZ+iRHP+BjR2fOyM3D2kd+Z+CL+/deBeVC+n+bAcdNfk/L96qpdQai9BjPYgS2zDFVVcRaNQHNbm1wDmEaQpqp5oCiomouO5rXkFk8itzj+OrDR6PTV0tlVS1vHLjzuEsBEmCalRZMsOXruo867nU+2P0V953YqsodRkjWQwflTKMnobzm2YRqcMvd2Ogkc8PNJngH8dcpNluNva2/mpmVvEDJ1BIIAgj6OHG4eOYMJ+daN9jpCIXZ4OwiYBl1GiC0dbQzIyObY4jJsSRiftnd08simnfhDQVw2B309Tsbk5TKtJA9HEuIvbujkha3tZNsFdk1jc0uQk/pk8vXByTF3a/Sa6IagMFOlwy9QFHDZFVxJOsrYXG8QCppkZmu4PAqBLoEnKznzgkBjkNblgoLjNURQwbfVJGOQii0zefN402ugb/GhuDXUAjtqge2wmC+khV8MfvXWOv45d3vYay67ij/UvVbj0FR+c8EYLpxUKd1PaQwD7k10ALPB3U0p6U40Xtn8CnfNj6NoL/Dk6U8yIUmDZ6LoLS1snjkLAoHYjYHMWTPp87e/pbZTYdBDBi//fgmNuzvjvue79x+Hw93zovrR675NR1N9XG0VTeOye/9I6aCeP0LZ9NImupZEd+Xan8JrxuAakJu6DqVJiLTwS4xo42Ow3Yv427MxY0i7ei54Bz57OXqjAWNxXhDZmTMahr+NPc+fh9DDm3B4+s+iaNa9KJKLjNVb/svWpeFLEiiqg6POfQe7Q76cw0fzb6A2ymLupFE/YvigxNIn9mEKk9/MPY+2YPhnXYGrklumPyud53fPuqd4pyH6vOupCT9mcLbcwsHJnzxBpxnZQMSGwvvHXYXLJve3fWzrRv61fVOYYlPd3D/+KKYUyi34Bk2T82YvoiPKIZ17xg7hhFK5XbmOkMG5H1YTzf7kwalFjCuQWzjwhwSPfBygrj1MKS4VThpl4/hh8kXc/T6Tj14OoIfxfsrOVzjqJIclAbjj0S70CP4qnkEK5RdYX1AJPFOPueEgA6IsBee3SlELrRW4t0ra1TMKi7Y3RxR9wBeiDyBomNz+ymra/XIuVZa4VyYHIgmWThLcu+DeuNveNNv6iqAsNXfcGbfoA/B+/Aldq1ensEfhWTu3OiHRB/DfPy5NUW8is3vtqrhFH4AwDN64/zcp7FGk1zUTEn0ATU+uS1Fv0qTpXeIRfQC6P/5n5QHEEn0A2yUdQ4GGOfdEFH0Avh0f07ntQ6nYwtTZuuyPUa4H2bTwHqnYALtqPokq+gCWrn2AUCh8HbtYzNn5VETRB9Dk38P7WxN0t96PWKIP4IrlcqUcfKFAVNEHoCP41fo5UvE3d7TxRBTRB3DHavlx9D/bqqKKPoDfrNmKHsP5MxL3rmiKKvoAblvSIBUbYM7GUFjRB92Onu+t1mn0xvgFo7Ds01BY0QfQ3ixYt0R+/hpsC0UUfQC+rYJgq3zfAYyqwKGiD6BDEHqv1VLsw4EjWvhtqU/sgRrQTapa5Ox9rdGzlveyCCEIRSrUG4aWQEsKexMd/8bELb59S3u+7ERLbWzb5oNpq0/8HqtUbUxcHHmbe35H2vQlPqAI/5fj+5cmTaowtu/p7S6EJdS6LY42O6Ri66HO7sSgKHS2ypfOaWyOR/AKOrsSW6jax5622M/kqo7EywX1BBs64it1sMUrN4bs6Iw99+s0dIKS5YY2tMderPWbJh0hOYGzrSP2PKvLgrapbokuSAXQEEEYxkNnjHu9FoSZb3vsfgXqrAk/URv5/Tfr4yhhc5hzRAu/GUMKsSeQQFqe62JoiZxtvSUKR/X8a0qgKAp5zvjPlo8tSNyxMlnknHNO4vecfXYKehKd/hIJ2sOPtp77kCijjj8p4XsqR4xOQU+io2U54veT3out5PC0sk+TxjJxlihyjhiU4o7IkTEotquju88xUrHtzhxs9ujjfcmAxMeRfQzqE3s8sdsyyckaIBV/asV5MdtMLk/tmJaJnCvmxPz4joeeUz5MKv6kvELsMUxzBmRk4pA07jmjPPYprXK3k7wYzp+ROK0ittFgpUd++j42hqOm0wYDiuTjl/aNfm9JX/k8vJxxsd/TjAHW8vy0YZEN9LRhX/75whEt/Prke3jsm1PoV+A5YC6oAG67yjGD8inOcuJxaEzpn8eT3z4KTe2FxM0b5id+z1kPJb8fcfDSOS9R4IotViozKnn45Id7oEfhKfrBDbhnzIirreJ0UvaH32MrsG4UkCj9xxRy7MXxW6l7cuwcf1nPl3PIKihk2kWXxd2+eMAgzr315ynsUWQKvzcm7rZqrpOS68enrjNp0vQizpu/HbvRwHLp+NoNcYxD35E/8p0/+VpcFdPCXlMcmRTOvAdXSfzf94OZcMp/sEUoSZBbMpV+o+N4/yKQkz2AqWNvw24LnyPodhVzyrGPSrt6DiucxnF9Lw97TUHh+H5XMKH0FKnYAK9OjZ3L/8Fxv5WOf3mf6H+3KbnlXNZvnFTsfKeT+ydOo8LtCbsOWOJ08eCk6VKxAWaVFnBueWRX0GKnnQenjJSOf/WwXEbnRBY4LgX+NUP+ezupv51Zw2247N1rQ3keyHRAhhMGF6t8e4bTksHLmGkOSvv973OtapCZq5CZC0PG2Rg2Qd6jQFEUcqcfJOz2dVWFkrPtqA5r83glU8N+cQHs/zIaaFMyvvSlHOArYO6SJk2aNGm+PKTNXRIjPT6mSZMmzVcHq2Nk7/vtp5gXl+zm3jfX4ddNclw2OoMGumEigJDRLXozHBqXTO7D9ScMpjBT7uiCZe4tAyOB3K3bdoM7O3X9icJJL55EnS92XsLgnMG8fO7LqBbrLMlS86tf0/rMM1/Ul4uIqlJ4440UXXtNz3TsIN79x2q2Lo0vUbtyeB7n/rB3nFIBPvjHQ6ye/T4ixntaMmgol979G+ySBXKtEGz2Uf/7OBP3VSi9bSq2nF763qdJk2ICv4th8HHCNJxT5HfNAvddHfW6dtPfsNmsueC1rX6WlqV/ByMAiorqzCZzyBnkjv82qkO+/q6hB9jw+R201C5EmAca3Kiai6FH3U1Rn1nS8YOhDj747Pu0tm+BvVYjdlsmFSXHMnroVdLHPPfxzOq7WFH33iE/d6oZ/GDqvyiWLA4P0BHq5OT50U9tLDj+Aen4DX4v586PbD5UbHfx6oxvSMfvCAW5ZdkCNnrbEUJ8UWvPrWr8edI0RuZYO+Hz1407eG5n7SE/V4BjCnO5e9xQnJr83OeWhXUsaQ6fT1bmVHjuBGsO9EFd8PKSINsaTHI9ChdOslOam5xSCIEuwdpFQRqqTYIBMA1AgcwchdwClUGjbeQWWp8XhtpNql8OEmrq/m5pmVB8ioOMgdZ+D2NrF8HXm6HdAJPur64CjHHhvqh3S38lgyP6qOfSnc38+KVVtPt1grpJgzeIL2gQNMQXog+gM2jwxPwdfOuJOGropYIP701M9AH8rnfquZ37yrlxiT6ALW1buOyt+I8HJpPWN96k9amnYos+ANOk8YEHCOzueYODHasa4xZ9AHs2tPDpc4kb1ySDec89yaoP340p+gDqtm7i5V/HV/Yj2cQt+gBMqP3dotR1Jk2aXiTw8DOxG81eIB8/hugDMP5srYC7b88iWhb9GQw/IEAYmP4W2lc/TcPHd1iKvfrj62iu/vQQ0QdgGn42zP8pXd7wBczj4c3ZX6O1fTPs5y8Z0r3sqHqX9+d9j2CoQzr2B1v/GVb0AQTMTv604OvSsYGYog9g2pwfSsePJvoA6kN+7t/wmXT87yyay7qONoz9RB9Al2lwzeLP0OOZG0Tgg5qGsKIPuv/S8xpb+dly+XH6/jXNEUUfQE1AcMNnNdLxAf41L8iqPSbeAOxpEfx1dhB/KDknAD9/z8/uLSZ+317RByDA2yrYs9Vg3lsBujqtvZYwBbufCBBqFN1vugCjA2peDhJqkf/bmp0GwScboMXo9l3c100BrPITfKvZUr8PB45o4ffY3NiOYPuzuqqNrQ1y1sqWmBfZUvpwY1t7Yu/puqbescpveOCBhO+p+XnP56TNeS5x17X186098GVZ9VH4SUYkqjasxZR0TZPF8Eo4bplgBtPOnmmOQDriKxUT3Lwjtf2wQOuKxyJe69rzOUagXTp2R3Mczpgb4yuJcTD+QCtdgcjulcFQO9X18qL7s90vRL1uorOrba10/FTiN+Jzu3yxWm7+EDAMqrsiL6YLYH6TnJsqwBNbYy8GLGmOUnMgBu9Uxf7erm6XL4mgG4LtjQeKI92EzRbdMAG8bSZtMcxYDR1qd1obcwO1AjPCcN+2Sv69MRZ2EK0OiLEysfJbhyNHtPDrX5hY4VWHplKQIVfs1BLKl+eYmZrgR8au9k6hS3tZ4s6X7tE970KZV5L4MaXeKN4O4MnJSai9ZrejSrqmyaI45d4bxXZEPwrTpImKUiRXaLonsGdHPtKmOrJRbZEd+GKh2mKPvZ6sflKx7TY3sSyGPS75Y2NZzth/s1xnqXT8VGJX43veOhW58cOuqqgx3vtKl/wR4TJ37Hmi28Ixz0x77HttFvxLVBUcYYbKHLd1c0OHSyGe7B5XhrXX0qJM7+158rGVouhzVsXTs3OaVHBEz3ZuOGEw2XFOkhXg1lOHkuvpBeH3k8R20brpnQ/fz49KbFfszml3pqgn0enz90dASeDLb7NR/ONbU9ehCJx2beK5NWffOD75HYnndX94W0Lv6anX3pTC3oRHtauoBa6E7nEMykHpDTffNGlSzSWxyyEA2HMlyxgVxpFyYLe2sJk/7WYULVwMhbyjbkTR5BcXB4z9QdTrNkcuZYMvkIqtaU5GDIx83HJA5RkUF8i5VgJcMfb/ol4flDuZ7DgcuCORo8a2rT8uV64UlaaoDPHELg31ynS546qqonBl/8hu2X09GQzMkvdI+PnoITGrBv1k5EDp+L+bFNkxdB93j5fPUVQVhbMOKoswtESlb4F1SeBwKoycHH3eXdpXpTRGSYlY2LNVMkceGsOep5A9Sn5x3DYmA6U48v22iw7fRbJ4+Uq4er68dDdbGzo5f0IFczc3IoQgw6GxbHcL7V0GF02sYFRlDmU58iuHSeHuOHdUznwIpsgnPVulNdDK1e9eTbO/mY5AB7rQKXGX0K63E9ADKEJhdPFoHpj1ALmu3F7rJ0DdH/9I57JlGIEg+q5d4PNhHzIER3k5zlEj6Vq8GM/4CRT/sOdFyv68+qfFVG3am++h0X22XAXVDujd/7/PiHzOuGYsqoWVRKsYus6CV56ndvMmOpob6WhuxO5w4MzMxggFCfq7KB88nFO/fxPuzF6oibmXzo3NtDy5tvt9zHFASAff3mMs+97TDI3Cb4zG1a93TJLShCft6pkYscZHIQTB3/8z/MW+pTi/bq3WW6B2Ozz96/AXT7sa56jw5RgSpW3diwSbt2PLKMaeU4m7bAKa2/okLNjVTP2ud+ls24mvbTOe3GHo/kYK+5xISf/4hHM02r272bT9RYK6D4SgX/mJZGaUWTZ2AdDNEP9d/3s2Ns0n11FKW7COTHsB5464lQG58oY9+5hds4zbNz0Z9tqLE39On6zY9eyisbSpih+ufJuDD/3lKg7envVNS7EBanw+Xt69Dbdmx61qLG5t4KLKARxTbH0nVAjB3zfv4pOaJtpCIeyqypjcbAZkubm0fzlZdmsnc0Km4M6l9axuCZJjA58OXgP6ZGg8PL0Et8364n+H32TNHpM++QqV+cndTOjqFDRWG6CY1FeZZOeqFJZraJpCdn7y5jD+Rp32FQaKBp7+Nss1/PZhbOnC2B1AZCmwOYDIs+E4KRf1MDgdlHb1jIOhJdnYVY2fvrQKE8Gk/vk0e4M0dwaYNayIXc0+7DaVkiwX6pdh5X/bnF4VfrnOXK4Zfw0PLXsIgcAwDVoCLQA4FAdBNcjmls2sbljNjD7x1dJLBcGaGnxLl4FpkjFqFF2aRnDLFkJbt2J2tGMGgwjDwDV5Uq/1ESDgC+JtC/3vB/tGQRO+8BwwYM+GZlrrO8kv6z1BFfB6aWuop72pgaC/C2F2211lF5VQvWEtiqpw9EVf71XRB4AvBA4VukxoOygRYF8aQ6dBcFdbWvilOaIJ+v2RL1rIQ/qCuij5TsFDTVMSJeSto3Hu/xFq3QY2D/asUgJ1Kwg2bSJ34tWomrVTOg53PtkFo/G17cDpKaGtbhkoJjlB+dzB/WloXsX2qg8x9AAeVz7tHTvoX3kK2Zn9pGv47SNo+PEGmgnonVQHN5PhyMFpc/PZrufIcxaT6y6xFN+rd0W+lqghXRhGZBfhUDW6DsoFD2KgGwY2zdokvi3oZ0FTPR2hIEMycxAC/r19EzZV5ahC6+6Mjf4AjYEgBuAzDeY3trCipY1pBbmMzrc2ruimSZVPx2t0Cz4b3VODOr/BtvYQoywKNSEETV5BWa6C2wEbawz6FaqW6vftj99nUrNLxzSgzxANVVXw+wTZFo5hHowwBKZXwd1HQ9G6DV+CzSaOJAhLbbAbs1lHbPEjimwoPoG+1It9SpblE0LCFJi7WlEcGrjtiCYfap8c6VSVRDmid/yEEFz/zDLeXh3efelgBhVl8Mr1x5Dt6uG8tOY98KDEkYm7kzBoS3DhqxeyqW1TXG3HF4znP2f9J8U9OpSm/zxF/a8jrEKHwT1xIv2feTqFPQrPrnWNvPHgqoTuGXdyJcdeODRFPYrMxs/n8uYDv4ur7ZgTT+WU70U/RpUqqu9bhNkQ/4RTybBRcefRKexRmkRI7/glRrTxMbBsNXwQ20DEedt3pV478LefgC+Gy50nB+f375OK377hVZo/i1IkXFGpuOhF7NkVUvEB1s77Mc1Vn4a9ptkymXbeu6iSx0lf/eB8Oruqw16z2TK44JQ3sNvkcs22NC/h0WXXR21zwbDbmNZH7qjqOZ/9gno9+hzjxPzx/HrMVVLxFzTs4ubV0Q3DXpv+dYpciXk17OO361bwZvXuiNfH5OTxtynHSsX2GwYnfxTdBf7kkgLuGjdEKv6api6uXxTZGAhgZrGLeybJ7biGDMHjc4PsOMjgxWWHbx3rtHzkc+knQfZsjWzeMmKyjaHjrM2z9Q7BnmcD6G2Hapi8o20UHCsfXxgC/x+q/ndKaH8c4Lq5QjrXT3SFCD65HNFwkEmM04bjsrGoFbFP/lkdI3t/zzKFLNzeHLfoA9ja0MkLiyM/KFKGjOjrJba2bo1b9AGsaFqBL2R9ZTBR6n8Xn0DZR9eyZQR37kxRbyLz3j8Sd11b+UHPl50A+OAff4277eoEHUCThdEVSkj0AYhOHVNPu3qmOQKJQ/QBBGV3/mKJPgCf/AJly4I/R28gTBrnRRGGMehs2xZR9AEYupfd6/8tFbu1fWtE0Qeg651s2Pq8VGzoruEXizc3x3j/ohBL9AF81LxCOv6PV78fs81Vi1+Rjh9N9AGsbmuhyifn4v7n9TtitvmgLoa1ZRR+vCS66AP4pD7KTn4MVu8xDhF9AP4QfLA2FOaO+PF1mFFFH8DG5TrBgLVNp9YleljRB9CyQEf3ysfXV3SGF30AQQh92Cod21hWfajoAwjo6J9sl46bCEe08Gv0Jn7MpFHGDv4rRIMv/ppz++gM9YL9rZH4RF5vkn9Qy6IHrdsn9xShgPxA01OYXXI2zuJL9HdIkybptPbO6ZFYiEh+7fth+uXraoX2pihEI+CLf/F4fzq76mO38cmX5gnGcdRSN61N4lOJEc0zfy8dodTOxxoDckeRd/tSOxYGUjwcef2R33uvRUEWzzTBNCAUtPY6erQ6gAKMLvn4oiX6PEK0yy8UC1/kz7To7Bn9cUQLv+OHFlGYGf/5f01ROGdceQp7FIFh1pLre5LJpZPREnAUtWGjyGMtAVwG19ixCbVXnE7c4+Qd1mQZOjXxHIyM3F5wngUGT4n/OKTLgmOaFez57lgO6mHRPL1TdiRNmpTiic/h1jGwb4o7IoerbGLMNtljrpCOn104Ds0ePR+5crhc/LLiqcR6GA0bdKlUbIBJZWfGbDMwb4J0/HiIVTIhGscVxi6T8cMh8kfw8x3Rx0mHqjImV84Z80cj+sdsk2nBfOWMythGg1aqCoyu1LBHuH9iP2u5g7mFCo4Yj52CEpWMLGvyI3tU5H46SxScRfLx7UdFfybYjpGf32ijSiBCjqA2tmfKrxzRwi/LZefl70/nyqP7kb/fxE6l+31XFPDYVUqznRw1IJ8Xrj2akeW9MGH9+lMkPFu9XW4V0io21cZbF7xFniO2FbNH8zDn0jk90KtD6f/sM7jGj4+rra28nEEfvI9iMZFchhO/OZKK4blxt3d4VK76rVxeglXOvPFWRh5/YsySDs7MLK579Kke6tWhlPxkckJFjkp+PjWFvUmTpvdw/iAOE7BL5Z0rnbdEcAvdD8fN/5COX3LagzgrwruCKjY3eUfdRNaQ06Xjq6qNiac+TVbhOJSDas6qNg8jj7sfT3Z/udiKxlmzXkDTDp3E222ZHD/lD+RlRy45EIvzR/yYCaVnRLiqMKLgWL478SHp+HOP/UPMNvOPv186/m/HnkKFM3L+3qiMQi7oM1I6/n+PPZkyV3gBVeJ08czRs1ATKfm0H4OyMvjRsMjCNdum8tYs+TTlW8cUMjE/snDN0OCtk+TzWvMzVK6d5WRyf40JfVWmDtAYXaFy0WQ7M4ZaWwRVFIVZF7jIK+aLaa3TDTkFkF+iMnS8jaNOtr547RmgUXaRA89gFUexgrNUwVWhknuUjfKLrJWQUbI07N8sgky1+3dQ6XZbz9GwX1yANiCxklH7o5Zn47hiPOqYEtTxpaiTK1BHFGE/ezi2aT2zAHdEm7ukSZMmTZovF2lzl8RIj49p0qRJ89UhXc4hCkIIbn9lNc8v3o0ZRd86NJX7LhnL2ePkV1AsE28Nv32c8Cs4ruddExfXLOb7H36fgBn7bLxbc/P8Wc8zINd6vSIZqu+4k7b//hfM2Afm3cceS/9/yq9MW+HJ2+fT0RxfzoDNoXDNg7NS3KPwfPyvR1n2zuvxNVYUvvvQ42QX9vwxX70tQO1vFsXdPv/y4XjG9Hw/06TpCQK/i/Fcy8/E+V25QtnBjlbEo7dGbWO/8a+okkXcTd1Py6KH6NwxGzPQAQfkrClkj/8W+ZO+JxUbIOCrZ9XH1+H3HmwEopJbMoXhR9+L3Zng2HwQG7a9wIp1f8UwD3zGZ3oqOPHoh8jMkE8veWjRt9nVHt4gzK66+Mn0l8hxyT3bPqpdzs83Rje2eW/aveQ45Ur3bOto5orFL0e87kTj4xO+LRUbYE1rMw9vWc/athaMgzY47IrCb8dNtVTS4TvzV7HJGznP8t/TxjAwW86x1RcyOP3DyMZAGvDczFKK3XK7c62dJo/NDdC4n7eNyw4uu0JJtsKZ4+wUWTiKaeiC5XODVG07dO7l8sDRpzot1/JrWxOi4V2dA1JFFXAUKJSd78CeKx9f+AyCrzRhbvIfGN8G2sRM7KfmotitH5gUXSFC729B7GpFKc/CfsoQlCxru5XxcEQf9fzX/B08uyi66AMIGiY3PrsCI1bDVPHoqYnfM/uO5PcjBoZp8L0PvheX6APoMrr4+ltyEwqrND/7LG0vvRSX6APomjePtvd63oly7vOb4hZ9AHpQ8O4/VqewR+HpbGuNX/QBCMHjP7wmdR2KQu2fottsH0zz0xtS1JM0aXqXmKIPoFnO2RCIKfoAQg9GLzkQjZYlf6Nj/UuYXc0HiT4AQfuKxwk2b5WOv+rj68OIPgCT1rqFbFp0r3RsgJb2LSxdc98hog/A66vio89vkI49d+dzEUUfQMj088BC+Xq/sUQfwKkL7pSOf2UU0QcQwOA36z6Riu3TdW5dsYhVrc2HiD6AkBD8eMVC2iXNYz6qbowq+gCuWiA/Tp8dRfRBdz2/b3wqn+7z6JzgAaIPuh09W32CjbUmT80PYuU04PolobCiD8Dvg8/eCeytASyH4TdpeOcg0QcgINgoqHrBmklK8LVmzI3+Q+PrYCzyEvogOWZYoXc2Ya6uRbT5Mdc3EHptXVLixuKIFn5vr47fMUsAC7b1vKsjANXxWW73NtvatqGLxFwTO/XOXnH1bH/rrYTvaXriX8nvSAw2LEjc1W37ithWz8lm1YfvJHyPkWJHtnAIU4BFV7I0ab5qBLft6u0uhMW/J/bY2LlTLo9cmAZ+b/Tfu6V2oVTsfeyqnh31utdXhT8g50r62e4XYrbpDMV2Le0NAoZOPEuy79RukYq/tq0Frx7d0dQEVrXKvfePbold9ksAuqS4iWeW5Zd0/tQNQYsver/qOwStMdpEo2Z3dNfLoB86WuXjd2yI/svrbcJSOQdzc/TFeHNLl3TsA+JsPfDzZ+5oRRipdxg/ooXfuMrchNqPrugdJ0JiuIodLlRkJn4UVlM0PDZPCnoTHRmHzqxje940pbBP4sVpc0tiO34lm4GTjkr8JsnEeSsoEdyy0qRJExm1sqy3uxAWe35s8xNn8Wip2IqqYXNEP8bpybGWplCYG71vdlsmjhh9iMSgvNiOpza1dxygY+HU4ssyGpgh57o5IDMLLY7xZ0CG3NxrZnFsczsAWwrHI9nJu01TcMU4IZrhhCy3fN9zYxzjVFXwZMnHd/eJEd8JmoVpp1IS/Q1SS5LzvVKKDzwKrBR6ULTUy7IjWvj96OShDCuJ74v99al9yHH30kPy5xIFuV0Fye9HDDx2Dz8Yn1he4T3T70HpBQFQdNNNOAYNiru9mpND4fXXpbBH4TnnpgkJG7qe/+NJqelMFEr6D6SgMjHHqXNuvj1FvYlOwbdGJdTePT6d35fmCOW6y+NqZnNIOvkdc2HsNuffKBcbyJ/6AxyFIyJedxSNxlMh78o7/OhfoSjhf3ebM4+hU6ylVFSUTqdPWficbEWxMWPy/6Eqcm7SF468HbsafRHwm2NjO3NGYnJWbNF968A4/v4RuHnI9Jht/j75HKnYhU4Xtwwfg0uJPMW9asAQKjxyOXjfH96fWN+YawdXSsUGuH9K7PndnWPlRDHApVPtRNIXWS64aLLDkmgdPc2BJ9LUW4GJx9ux2eXjOwtUskaH/94oNig5y25pEdhxXj5kRfheltqwnZorHXt/7GcMQynoVqhKjgv7WcOTEjcWXwlXz9q2Lmpau/DrJiqQl+FgV7OPilwX7X6DsZU5uB2Hgc/NGz+DpQ/Hbnd37xbbDRpBVtWvorazli2tW3BqTioyKzBMg51tOxlRMIJsdzZTS6eiqT1fImF/QnV1hBoaMNrbUTMyCFXX4Bw4AKO5mVBLC6GqarJPPQVX396tY1W9pZmNC2pBhWBIp6Xax/CppWTlu9i+qhFfR4AxMyoZMC7xun/JpLOtmU2LF1I5bCR6IED15vVkF5XSWl/TrV8VB3aHytgTTu0Vwb8PYQrallQT3NZGqDOImmHHaAmAL4BjWAGG38CR5ST3pH5ovVDGI01k0q6eiRHP+Bh48lWoaTj0wvVfx5mZ+KmDQ+I/dhe0HpSXNHwazjOvthwbwOhqBtWB4W9BoKK3bsdRPBq7O9dybCFMOtu2IUwT1WYHVDTNidNTkrRnWCDYgd/fhG504Q+243EVkpPdX1r07U9t+1ZW1X+Cio0sVwGKEGS7ChheFFtYxcOl837FTuPA9IJx7gH8fepNlmObQvDktqW8uXs9Hs1OlsOFzwzx7YGTmFEy0HL8gGHgNwxq/J1gCHZ2+ShwOBiTV4AzCc/9ra1eFjS2UZphxx8S2BSTxpDO1wdUSpeK2J9/b2pkZaOfHIeGW1MZk+/Epmqc3Mf6KTFTCBo6BKpiohsKJTkqvgC4HaAlaaeyy2siEDTV6+ghQX6hjaw8DTVJ8c2Aia/GQHMo2LNVzCDYc5WknPwRQiDaDAzdgDodtdSB6lRRMpM7XxBCQGcIMuxxP28Oe1dPRVE0YAlQJYQ4S1GUAcBzQAGwFPiGECJlyUBb67386q11rKlqp80fRDcE2S4bp44qxRTg9Ydo6QoxpDiLW04ZSq6nl3b9PvxVfKIPuh1Ae0n8mabJXfPu4r1d72GYBjbFhqqoCCHQhY659+S+S3Px1OlPMaxgWK/0EyCwbRs1d9xB1+YtEAiAroMQ3f8FlMwMFM1G50cfUfnQX7AXFvZOP30h3v37Wro6DsxJ+GzntgP+vXtNGzMuCTD2hN4TqZsXLmDxqy/ycWszwjBQVA1FVTD1/2UlZBYWUTpwCCUD4t9xTTbBqg68r2z7Ijl7/4yDYEMdAF1AqMpL6bfH9nj/0qSBnhkfA8+/G170Afz1Wbjtu1bCE3jgBjDC5MRsWEBg20qcP/iLpfidOz6hbdVT6N5abFmVaJnFBGqXY88dQPHMe9Dc8R27i8SGBffQuOs9uh8WGigadlcuBeXHMXDcdWh2uV0hAMMIsHHHS+zc8wGKotHctpnuP6eNwX3PYuq42yyJy66Ql492PMG6xnmEzAPzjk7qfzWnDLb2tz1rzp000nHIz1d2befnKx7n1+PlXTcBrl/yOis76rv/Yfoh1P1at6/9iH95chiUJX+yyRSCeQ21PLdzG01BPyUOF616iIBpcEmfgXytv7XxqbEryK0rNtAYPDQjb1Obl7vHD7f0t11c7+Pxrfv+pt2v8VZt96NgXn0X90ySdyQFUJVuB8/qVli4VUegM22gnUxXEtwqTUHtbhNvq4lQwG7XKB+g4XQlR/AJQ9C+LkTLAgPDB45CKD7ZgbM4OaJMhASB1xsRa7u6Jw9uBXWEB/tpeYke0Ir8GqaJubERs6q9u7C4qqB47GhDi1By5esExkPKd/wURbkZmAxk7x3YXgD+K4R4TlGUR4CVQoi/RYshu+O3ancr5/z1s7jbexwai39+EhnOHt79W/0SvPydxO/rBfE38/mZNPnjN8F5+vSnGVvc8xPrrjVr2XHRRfHfoCgMW7YM1Z3aL9zB+DtDPHbL3ITuGTOznOO+1jNHAvbnrQf/wIbP4jdSOO+2uxg0seeLo/t3tNH4yKq42ysejYq7krM6nsY6X6Udv1SPj4EX34FtsVMJnJLiL3D/9+JwTlZw3iJXKqd58V9pX/WfKKE1+lzxHppDbtdy0VsXE4hi8KLZszj6vPdQJE6umMLgnU++QWtHZNfRTE8l554U3d0yEl26l3vnnIEuIrtsjy6cyZXjfycVf8acWwgR3aRjWs4wHhj/fan4p875Nx1G9DWNp6ZeyMBMuSONv1qznHdrI3/2pxcU8/sJErnrgDekc/rH0eek/8/eecfHUV17/Dtlq3qXbNly773hSsf0EAg1CSVACgmEBEJIIS+EVJIQCIGEFiAJoQdCCb3axgYb3Hu3JVu9r1bbZub9IQwuuzOzd3YlY/b7Pu/zHpo7Z45nd+fec+ec3ynzqDx9jNhjbEFtFz9baS48U+GVefw4Zy3IVu6O8cTSAzecz5/hYvJAZ2vgD9+OsGf7gd8djw+OOcuLL8t56LTniTDduw997lSc6yZrsLPgz9ANQrfWQHec2Mgj4f1xZUreKEYeX4W+Nc5n7JJxXzIFuSLxW12nc2Raa/wkSaoETgce+Pi/JeB44OmPh/wD+GK6rv/bV5KTaQ9GNB5evDM9zpghEvT1AdWd1UkFfQA/X/LzNHljTv3vk5zsDIO6W3+XHmdM2LjEXLY5HmveSf6cVLBpSXIB6qLH/pkmT8xpeSK5370RNF/cZMiQDnplfrQR9AGEqwWl4W21y3Gg3rfuKQvTGu0rHxa2bxb0AWjRTuq2Pydku77xQ9OgDyAQrKE7yTl1H8v2PG8a9AGsbXpHyDZgGfQBvN++Sch2IBq2DPoAfrb2TSH7TeGQadAHsLi5gWDMjn7mofxp/Q7LMfXhGJ1RMfu/W2utNlorKuu5H+9sPNS/dzaYq6Fa0dWhHxL0AYS7YfdmsfuxP6G9etygD6BloTPfAfTtofhBH0DYIPahePubT65RH4gf9AFEdWJLrVVjnZBucZc7gB/CJ8q9RUCbYXzSE6AGiLtlIUnSNyRJ+lCSpA8bGxOkqVigaclPOLFekFL9rKLpyS+QRc5JBUYs+esakd5vP6ALfEf7jCSzA3Stjz57gVv6Wah1znDEcQd9OD8eQB89p60wbIj+G7rzxaQZ+iH9A+1hx/d9I0XQk2yt9FkkZoitx3Sbz3ND8N7ba0Zh34+D6a3pKF63CaftrM18T8W/y6z/n+DX5SAjFsdTsWazuslp7imetsBPkqQzgAbDMD4SOd8wjPsMw5hmGMa0khIx1b0bTkmuvsyjynxtrjP5ZiFO/mPvX1OAQXmDyEmy9cRNM3u/0TxA6Q+uT/qc8p/0vgrlqFn9kj5n5My+EXgZkmTa5uzzvpwmT8wp/NKI5E7wyH0qRJPh80evzY/l9uZOT5WzlLF0kT38TIsREnkTLxO27/aZ3x9Z8dFvmJhyZXnxdLL95vfV5ynB5xWrLZ/R/ywUyTwlb1j+dCHbYE9seqx/gJDtbJcHnw1hm1+MPV7IfqnXxzGl5i1KJucXkaWKqdleP9paeCbfpZAnqJZ77eh8yzGFDlQx9zFvxKHfn3kjBBV+PyY7T6Z84KGhhcsDA4c7r8Hz9pfxVMT/txfMcl6mJQ/xgjvBvXVJqDOcC+vIFTnIVfnxDyoS6jRxRVg7pK3GT5Kk3wIX01OV6gVygWeBk4FywzBikiTNAm42DONkM1tOVD1X7m7lFy+sZ0t9J91RDc0AryozZ1ghsqTQEYrSGYoyrDSHn542mrK83q3x+oR/XAg7kmiS3UfiLlEtylVvXMXSuqUYGEgf/w/wibAL9PTvu+eEe5jZf2af+AkQXLWK2p/+lMiu3aBph6YluVygKLgrKqi89x48faTsGeyI8K+fLSYWtt6umnRSJXOSDWxSyOKnHmXFKy8QCgTo2RqTelYI+z1HPFnZnHX9TxkwdnxfuUlwUzMtD623HKdU+Ki49nNRTvaZ4fNQ49eb82P4nkehvSvhcfm6y3C5xBd74dvMlTs91z8gbBugc9PztK95FC3YjJxdiuotINq8GSWnH6Un/BZXjrMehKve+g4djfvfPxnFlU1BxVEMnXw9bq+4eEw01sXazf+guvZtDMMgENxLj1qERP/Sozl6xm+QZfHFake4icfX3sz21uXoB6VmTis/k/PHOdt4Pfrd64gkeLs12tefh2bcIGxbNwwuWvwE1eFDxWMA7ph4CjOKxAJLgJiu8+Le3Tyxazvt0QiFqptOLUrUMDi9XyVXDR/rSHlzV6CLb76/lq44b2fG5fi5a+Z4W70EE/Hy7g5+ty7+Om90tsI985LfNI7H9kaN97fGMIBZQxWGlDoPnnTNoGa7Rmdrz3fH7ZGoHKampL4PQI8atK2I0LZMRw+Dmg+l8934K1Mk7hLWCT3RCNvCPcsct4Q81IvrC4XIWSm6RkxDW9uAUd2GIX0s7pLtRhlTilxsLijldI7slXYOkiQdC/zg4+L1p4D/7Fe8vtowDFM5S6ftHILhGO3BMLoBJble3KpCOKqhGwaSJOFRD5Md/63L4ZHjAB89moMA2cB+OcXFs+HqJALENKHpGptbNqMbOrqmU5VfRXukHbfqRtEVokSpyO77psB6JIIWDKL4/UQ7Ooh1duIpKCQWDBKqq0UKBsmZPRtZ7tuWluFQlMbdHXh8LmLRGKFgGFVVyS3y0dkWItgZpXxQPrmFvd+8/WBCXV20NzZQ1L+S7kA7LpeXtoZaFJebSHc3qsvVp4qen/hZ04Gm6xiaRrgzRFZpLqrXRSwQIRaJQUwja3jx4fHbz/AJn4fAb396Y34Mb9gIzx9Uo5ufheebqXkrH978EWz4qKczc/U28Phhwkw8009Kif19GFoEPRZBUlwfKwqnRogt3N2Oofek+kcibaiuLPzZqVlYA3R1NeD1FgAG0VgQWVJwubJT8uyJ6TFau/di6AYeNZv2UAN53mLyLN5m2uXZ7e/wn+qFxDAY4iqnKdrOpcNPYU4/5xt7hmGwqG4be9rbCRCm0puPy60ws2QQWS6PY/uaYdDQ3UU0piFJgKxQ4vHiUZSU3PvuaJSN7QHckoRuQEskyEB/DoPznb8VAmgLR6kNxvApEoZhsDcYZkiOl4rs9LygiGoGLiW186Ee+/iVgN7zeavu1K23tZCOIRugg6SBrhi4vKl5JhgxA2SItcdAMpC9CkigeFLXzsEwjJ7UUcNActm3+1kM/IbQI1ddCKwAvmoY5hXKooFfKKpx7B/eoa7jQKnpHI9CZ/jT3bEBBT5u/dIEZg/rGzl/oKdFQzJkVcANyYlYpIqvv/p13q9739bYnx71Uy4cdWGaPToULdDF7su/Rmj1GlvjPXPnMuQBMeU5J+i6zt+vX0ik236NzZV/mounD9qO7FjxIc/8/habgg5w8neuY9zRYqk6TuhYUE3HSzttj1cqsqi4dkr6HMqQFJ/zwC+l86OmacT++KClD8Kqnps/ghdMRUfhuC/jmeLsOaBHuqh//XrCdSv3+6tM7tjzKTjqWuGFZDjYyIf/Owddj1/fPXrOHyiuPFrINkBN/Xu8+8H1xC8cUpg+4QZGDDpb2P6DK65jY3Mi5XKJn859njyvmOz/v7a/zt3V/zMdc+/4q5lYaN3oPR53bFrMk3vWJTzuRuKd48X7QN6zZQOP7Noa95hfVrh18gwmF4it+XTD4PS3lhEw0YT45rBKvjpELGWvI6LxhTf3mpabPTKvjAHZqVkHtAR0Hl8aobrFoCxX4vzpbvoVON8M/+D1MHUHCbFIMkya62LgcPEALbhbY+9/Ivu6XBxo3wUDLvbgLhLz39AMoi+0oC1PkCVRoOD7vvPUeG1DA9FXNvf08AMoycJ9zljkEuv2MYe1quc+DMN4xzCMMz7+/7cbhjHDMIxhhmGcZzWpOeGWF9YdEvQBBwR9ANWt3Xz38RVEYn0k7HKzwMOnqzb1fthgR9sO20EfwK8/+HWfCGc033uP7aAPILxoEdG9va+W+e5jm5MK+gAevdn+/U8VWizGC7f/znbQB/Dq3X9Ko0eJSSboA9Bqu4gFel/YJ0MGSO/8aCfoA4h0d1sPiodV0Afw9qNitvejdcWDBwV9ADod6x4nuOMNYbtrF3w/YdAHsOG9HwrbBli49IckVovQ+HD174lE46c6WrGnfZNJ0AdgcOcHXxOyDVgGfQDfXHOXkO2YrpsGfQARDG7fZL8d1/7sCHQmDPoAgrrGz1d/RCyJ+Wx//r612jToA7h3a43w2ue6pQ2WGiNfX1wvZDse/10Rpbql54r1HQZPLnM+H+7ZHjsk6IMeAZYVC6N0d4kK3xjU/Td+0AdgRGHvf8Ufm9qyQOKgD6BVI/I/a9VVM4zuKNHnNnwa9AE0dhF9foMju3bp2/y2NLNku32Z5KZAhL1tgpOfY5xL0PYW79S8k/Q5raHW1DtiQXCV/T5u+wi8JzbJOGHv5rakzwl29L6aW1drC9FwnCbNhxl6SOzehNalQBkxQ4bPKMZKMVn+3iLSsDbhsXCj+GKpu3OXxQgDLSb+3LNS3jTQae/cKWR7TeNblmM6o2KtItJNY9hkYb0fC5usPp/4bOpssxzTEo3QJDinLay3t/APCKiLA+zqsp7HktwvNqWm9cAArb7DIOpQvbK+2iQwNqCjRVCxNQS6RVwXcxCX6Xutg159u7O1kNHYBXFeNBm1nb3youSIDvxOHltue2z/fB8DC/1p9MYEQVWvvuDUwacmNV5CotAn1oDVCdmzkheVyTnxxDR4Ys6Qycl/9nmlvS9AlFNUjDdbrElybyIL5vf7JvWNUmqGDIcD6oy+E2Kyg68ycaNtb8VUYbs5haMtRigoqvjzVlHMz5UllYLc4UK2p/ezUjyFEkHVzXRT5rU3l3yxwurzic/E/CLLMf28Pkq9YjXzZ1baS5/NcYnNR+PyrVM481Kg6rmPISUHhgIDCiXHtX6VQxPXrEkyFJSKhR+KT0KxyIZ0OZjO5UHWtaXyOGexglSeA3HWKnJVfq9oDhzRgd8NJ49ifL/cQ/5eWeBFlXu0KF2KxLSqAu67ZCqy3EciDz8yb/Ial6FnpN4PG5RnlXPe8PNsjZWRufvEu9PsUXyKrriCnJNOAps/ovxLL0UtEFdvE2XWF4eRW5LcwuLLN89KkzeJkWSZL/30l7h99h94F93SN21KCi5ObrHgGVeE4klNQXiGDIcTtmr3FAlFERMskC+9xXrQBT8Wsr0/eRMuxj9kfs+K8WMkVzYFM67BP3COsN2xR9+B6slPcFRi0kn2UmUTMX/ufUgJWi6oip95029FFQwsi/yVzOp/bsLjiuTimukPC9kG+POYb1mOeXHGz4Vsy5LEjSPMP7dC1cslQyYL2a/w+bl+1LiEx/t5vPxm4gxhVc/zBvWj0mcenP1yolhAD3DrtFJ8Fq79c579FxtWfHGym7H9ZXwuGFYqc+EM57WDpZUKQ8Yo+/9kgZ62Dked6MLtEV9v9zvPjZwg+FNyoP/ZDjZrJmehHpML/vj+SQPcuI/LF7YPILkV3OeNQyrNAkUCRUIaUoDrC2IbHUlf/7PQuNipqmeGDBkyZPhs8HkTd3FKZn7MkCFDhs8PTufII36buysU5bx7l7CxtvOTbjRel0S+z01nKIaqyMQ0naJsN3/76lTG9ktSXTNV3FzOpy0c7Izvmz5+mq5x06KbeG3Xa0RMiuIBJpVM4u8n/x230vsKlADBZcuov+22HpEXkyJutbKSoc/9FznLWk0pHax+u5qFT2yxNXbkzFJOvCzxTmY6iYZDPPPbm6nZcGC9jfRxKwxD15EkCV9ePmd+/8dUjhrTF24C0LW6gdZHreuWpAI3/W9MnEaWIcNnnfCtFmrF374QT464/Hy6+/h17VpAy5Lb0IJNgAT76uZUP6Un3oq/v3iTcoDdG/5N9dp70T8pHJIACbe3kLFH/4nsgpHCtiPRAB+tvZ3de99C16O43fkYhoZhxBhQcRxHTfyxo9SuHa2rufejb6MfpBPgV/O5esYDFDtM9Zz57vcSHpOBxcfcIWw7GIty0ZInaYwG4x4/qXgIv5hwgrD9qK7zlSVvsTeOcFGB6uLpeSfhEXzTDbC6tYOfrNhEe5w6vuHZPh6YNcFRn8AL3qymLsESa5Bf4R/HOGs3Ut2is3xXz2/JMECRYcZglbI854mAumawY0OMPTs0YlEDw5DQNXB7DPoPVhk8RkVRnWfYdayL0fZhDD1qoAdBj4G7RKLyAjey29m/Q9sSJPJ0M3R//HJMBrJlXGcVoQ7v+7ZaTjji3/hNuPlVOmwKPkgSbP7VqbiUXs6AfeYaWP3P5M/rg+DvkpcuYUXjCtvjy/3lvH7e62n0KD6BRe9RfaV9KWjJ52PUiuVp9Cg+Wz+q59X7zdXNDmbqqQOZeZaYhLYTHvzeN2itta98+p2Hn8Dr6/1gOrS7naa/2hf3kQo89L9xRho9ypAMmTd+yWE2P4b//iQ0Wc8Twu0cLIK+T+wLBn/de5ZR/8o1pmPKz3wAb6nYZtju9Q+xa809pmNmf+kdFFVsoffCWxfSEdiR8Hi/0jkcN1NM/bg7GuDn7yYOjCQkfnncO7gt6gwTYRb07cOPm7eO+b2Q/ePfeZCQbq5QctXg6Vw8eJKQ/dPeeYWOWGLhPLck8dYJYiUzOwJBLllsPscMyfLxjzkThex/c9FeNnaa35tKv8K/BYO/6hade97u6W29P24FrjnRQ3GOszXw8ncjVG9N7H/5QJmjTnLWp7F9dZTGV+Ov7WUfDLlaPDjTWqJE7kisnO/+TjlKWd+80IDPSDuHvqK+o9t20Ac9ux5/fTuxBHDaEAn6+gDDMJIK+gDqgnV0RDrS5FFi2p5+OqnxRnc3kerqNHmTmCX/3Z70OStf730/Ay3NSQV9AAsfeTg9zliQbDsHozVtHWUyZOhbbAR9AFqwrxStzWlf9bD1mPXJPev3p3brfyzH1Gz8t5Dtto7tpkEfQG2jeGue17ebv8k1MFhe+4qwfTsEEZP9b410WwZ9APfvFNvwD8ZipkEfQMQwaI+I+f/0but2Wtu7xH9TVkEfQE1QXNbzo52xQ4I+gIgGK3c7kwuNRQ3ToA+gbrdOKOjspVPbssTX0LshFhRvzxZ7xVyJPvZmm7Dtw4EjOvDzCSgq9cv/bL/CTSeSJKFIyadGuOXe3xlRBFKXZH/vq7p6fMl/R2VX7/9sVU/yu3M5xX2jViv7j/gM9gwZUoug+mC6kd3Wz3EloTiLNXbe5Ll9Yg3QXS7rbAc5gfCLHfK91tKFOe7eV9S2g0e2t45wC6w3AFSbQn1uweyuApdL6LzDBa+JIqjP7SwFU5ZBsfhay4r1GMvrWLzIlh2onko5Ft+7bPEU4cOBIzrwy/W5mDww3/b4HI/KedP6QP746wt6/5qCXDzm4qTGH1d5HF4HctiiFF7+NeQkgj/3iBGoRdYS0KnmpMuTr4M7+crer/HzZmUzet6xtscrbjczz74gfQ6ZkH92cmpq3iklafIkQ4Y+Zu4kW8MU0YWs20Yqt1v8+V941LUgm6wQJYX8CV8Wtj9k8nWmx2XFR/kQsXTALF8ZgyvN2x+NG3G5kG2Ao6u+jGwSGPnVPMaUzBO2r9pYHs7KEat/9KtuRmRbB6V/mXS6kH23rDAp39z+IH8WPsHo47yqCqx+MecMEO8pcOUw63YXp/YTf0kxa5hKXhzZ0NIciSlVzoIaWZEYPdX87gyfoOJyGGAWH+vqKceNg7e/5Cjwc51amDg6UsB1Ur6w7cOBI77GD+CpD6t5cNEOusJRAhGNk8eWked1sak+wLDSLDbXBRjXP48bThmVQq+TpLUW/mzz+v1mwTfSm8JhxqqGVdy14i5qAjW0hdoIxoKokkqWK4uOSAeSJFHqL+XG6TdyfNXxfeanFgjQ8dJLtD71NJH6epTcXPSODoxgECMcBkVB8vspufo7FH1ZfPHglFAwygt/XkHDrkDPHyQgzs9SccFXfjGLnMK+eyu9a/VyXrnnL4QCnfQkE0lUjh5LsK0VDANNi1E1fiLHXfrNXulHkwg9otH4z7VEt5qkGSsS+V8dRfboz04fzc8DmRq/5LCaH8O798Jj/0t4XLS+7xP7r/wT1iXYvBw1B8/pX3NkX4sEaVv5EOE9S8GTjx5pRwvU4a86hqJZ30d2uLEY7mpg80e/pbt9B5KkIrt8YOgUlB3F4EnXOH6O1Td+xMbtTxCKtFJRPINoLECgu5bxI66kMH+EI9uGYfDo2v9jXf27aMQw0FBwceygi5k/9BuOff/hyvtZ0B6/Bv2mYRdxRn9nwlj/rV7Pn7csIcyBaXleZJ6ecxGFHmdZOK/u3c3tm9YBBv08fnZ2B5CAbwwdxQWDnNXJR3Sdv2/ezYt7G+mKaUhADPDIEn+YPIrJRc6EAtc2B/nO0uZD/u4CfjW1kJmlzurnIzGDLfU6HpeBpoFuSAwvl22/LbWis02nfreGIYGuQTRs4M2SKOmnkFeYmndOWtCgbUUUSZKIdmlE6gzypqjkjnX+RtbQDSLPNaNvC4HbAI+KXOnBNT+/T7Ku9iej6mmD86YNYHRFDpvqAtS1dzNxYD5DirNp7Ayxty3EGRP6Mb5/ft86WVBhf+wpv0ufHzYYkDOAQm8hY4vGsrJ+JY3djczsPxPJkOiMdjK0YChF3iKOGXBMn/opu91E29pQBwwg99RTibW20PHiiygjRuAZMgS9oR7/lCm4B/Rtk1uv38X4YytZ9uJ2OlojqG4JSYFo16fRny9XZfxxA/o06AMYOG4S8y68mNrtW2jYto1wdxAtFqV44GBCXQGCra30GzkOLRZD7cN0GNmt4B9fQqArhhaOQiAGkgFuFfwKdERQSny48pwVmGfIcLjjGdiPhFWsMyc5ti8fex56osDv6LMd21fcfopmfIfuvbMI7l5A3qTLUL35ju3uw+UrpKBkKh5fKVo0CLIbSTIoHnhSSjavorEuCvNHo6o+PO48QKekaApZfgddpj9GkiSOHnAhXiWLxq7dqIqbkUWz8Lty0IwoquSszOK7I77IgmWHBn4KML9UrMfe/ozJK8GNhA4Uu7LQDY32WJgrhk5zHPQBjMwtYFZRCW3RCPmqhxyXSswwGJ3nvGevW5YZV5DL0qZWGnWNqA45qsy80iJG5tlrUG/G2EIfx5e6ebchwr5qNhcwsVBhWrHzdYBblSjJheomyPZCc0CjcYvO8DKZinznqYw5+TKRsEFTnY6BTm6BjKZLjvr3HYzWreMukVCzZHKyFfQQuItTY19b3YVU4UZ2SxhuCSmgI4/y9XnQlwqO+Dd+7cEo5927mM31AdNx5XlenvzGLAYW9X6dFx318Kdkd/5kuNm8ADUd3LLkFp7a/JStsTIyT3/haYYXiDcyFSWweAnVl9tPo1EKCxi+YAGS2rt7IdGIxgPffxcbde6f8LXfz8Gf2/sBS8PO7fz7J99H12w4K0lcdMvv6TeidxqS7o/eHWPvL5eAzdpupTKLiqunpNepDLbJvPFLDlNVz7Wb4X/vWtoQVvV89FaotWhFU1yJ59Kbhezvo/qJL6IF6j7575xxX6XoqKsd2QTobF7PyjcuJ26KBeDLGcTUUx8XCgB1PcZ/Xj2VSDRR1oHEjAk/ZPigc5K2vY8/Lr6QhmB8ARkJmSsm38GIIrG3cl9ffjtrOneZjvly/2P47jCx4P7c9x5jb9h8XfbavEvJdokFr9/5cBGr2hKvkSp9fh6fI94u4vS3ltERp5XDPm4aO4ST+4vVh+7sjHDponrTMTdPLOS4fmJv/TTd4KGFEbY1xp8k++fDt47zoipiQVQkbPDOsyG6u+IfHzRaZuJs8TWMoRvs/U+E7p2H+q9kQcU5HrzlYgGa1q0R+f0eSPTR+mW8P+iPlIJ2FKJkVD0t+Pt7OyyDPoC69hB/et2671daSDroA9ur2hRjN+gD0NG57h3zGop0see65K6rtbTS8Je70uRNYpY+vz2poA/g5fvWWg9KAy/fdZu9oA/AMHjjgb+m16EEtD67Jamfh1bTRbT58FQ1zJDBETaCPgBNUN3QMugDaKoRs/0xXTsXHBD0AXSu/TdGsg/OOKx/74ckCvoAujt30rxnoZDtFevvMgn6AAw+XPsnolHr9Uk8NjS+lzDo67Gu88S6W4RsA5ZBH8Cje+x9vw5GNwzLoA/gts3vCdmvDgZMgz6Amu4gm9vbhOwva2w1DfoAfrtuO7rgi5XvftBgOeYXq1qEbAOs26MlDPoA9rQ5U/fcvCqaMOgD2LlBp6NFfA3btU2PG/QBaF3Q9La5oqsZ0ccaEwd9AEGd2Pu9r1SfSo74wK+6JX5z0HjsTmJsBns0dTf1yXX1zs6kzwlv3JgGT8xpqk7ez/b6vvmedrUlN9G01ddZD0oD0cbkg7jIHrHFV4YMRwQdJqu0PibcFK/GzMCIhRzbjoat2110tdsIbuPQ0m69kazrUbrDYgv4PZ3W81Uw2iZkO92ENHtttnZ2tQnZ391l73m+vlPM/pIm6/M0euoAReiMWgeMTnL1Wrqsz7YzJhGBNutzuzrF7cfazc+1Om6G0Wod8Op1ghtlhwlHfOB3yrhy22NPHZdEnV0qcR2eksvxSLY1w4kDT0yTJ+b4pk9P+pyiK8QV1kSZfMqg5M+Z3zc1iUOnzkxq/MjZ4opyTsie0z/pc/zjMgIvGT6/KMXOa57SRe6YQ9WBJdWPbEdR1IKCitmWY8oHi6l6jh9xheWYnKyB5GYPFLJ/VH/rFMthhcnPg72BX7VX/33+gLFC9qcVliQSfDyAUyvE5tJvDbc+b4DPjVcRq5WbVWKdBlnhFU81HF1h7deYfuJ1fgOHm58rK1BcIR5++IfKCRU9AbJGiNtWZ1jXZ6ozkm8XdjhxxAd+J48t5/fnTqAk2/3J90RVJKoKfeT7XLgViZIcDz86dRRXzhvcN07+1LzJa1y+Jd741Qmvn/s6PsW6sFhC4pjKY/jFnF/0gleHMvC+e/GMs9n2QFUp+d61ZM2YkV6n4jBwdCHjj6+0Pb5ydD6TTxqUPodMOPmqaxl+1GywUe8y5ujjOeFr3+oFrw4le1oZvqn2ayuKLh+LlCIlswwZDids1e5NE1tcAyjfvdt60LdvF7YPoPoLKZp7E3zc80725NHvPPslB2aMmf1rcosmxD8oqYyc9Ss8giIs5SXTGDf88ji9+iRk2U1FyUxOnC1eXpDjKeQr436NIh0aREkojCyazSUTbhW2/8z0myzHLDla/LN9YMqZpsdPLBnMqRViqqceReGuqbNwmcxVvxg3BY9gYOZWVb4zPHHAXuxWuXdmgu+VDX4zrZRSkz12nwSPHZv8Buc+yvJkLpvrIs/XEwTsf5f8bvjyTBeVDpQ3+w1WGTdDRTn4qylBdp7E0Wd6HLVzcBfIVHzJhZrf81iQPaDmg7tMomC2SvEx4sJyrnl5yBMTrHElUE7ORxnY+y3KUskRL+6SIUOGDBk+O2TEXZIjMz9myJAhw+eHTDsHC/7w6ib+uWQngVDMNCe60O/i9gsnc8yIPmrmfHOSPV8u/A+M6v00yp3tO7n45YtpC7dZjh1bNJbHz3g8/U7FwYhGabjrLlr/+S+MbpOaL1lGLSuj/x//gH/q1N5zcD/uufpttJi9DZjigdlc8JPefzMJPT2j7rnqUoKtcWpSJAn2bSJJMidc/k0mzRdrvusUPaJRd9cK9AYbtX5uifJrp6IW9W2bjAwZ0kX41vvNB4wciueLYv1Wo5Ew+l++YzpGueZuVLe4gl/j4j/StfEZMPSerX09Ahi4i0ZS/oWHkGVniUsr3/wmnU0r4x4rG3IOI6bfKGw7GGrkg1W/o7Z+CcZ+ihEuNYup465n6EBnz8hFu5/g+c1/OuTvxf4BfG3ibZRkVQnbbuhq4QsfmovDLJ73J+H7H9JiXL70GXZ2x6+zPL54EL+acJKQbYC2SJivf7CA2vChtaB+ReFv0+YyNCdX2P5l761kW1fiOtM7p4521Mvv6iV1rGmLL1LikuDlk/rjUsS/+7VtOm9tiLKtQScUBVmGOcMUTp3grAUIQGerxjvPRQ4QrpMkkGQoq5SZOMeNJ04DebvEgjq1z0SINBoggbHvNkngKZPod64HxYH98KMN6BsTfLZD3Pgus19CZoW+t4PoG1sxGruQst2o8wajjBFTg7XLEZ3q+dB7O7j77a10WgR9AC3BKJc9tDQpMZiU8fS3kz/n8S+l3g8bnPvCubaCPoB1zev47pvfTa9DCWi8805a7r3PPOgD0HVitbXsuuRSonv39o5z+/HPmxbbDvoAmnYHWPri9jR6lJiHr/92/KAPPg36AAydN//+N7rae7/dCEDDfavtBX0AEYO6Oz5Kr0MZMvQRlkEfwKZtwvatgj4AzcaYRHRueYmuDU/3BH0Aeph9shaR5k3Uv/Z9YdsAu9Y+kDDoA6jf/gytdcuE7b/9/vfYW7/ogKAPenr7vb/yFqprxVQxAfZ0bIob9AE0Bau5a5l1jaEZVkEfwOyF4qrdP1j5SsKgD+Ctpp282yBQBvMxVy17L27QBxDUNK744F1iguIrT+zcYxr0AXz3ow1CtgF+vao5YdAHEDXgi2/uEbYfjho8sCDM2j063dGeX5Smw4LNGmtq7AnvmPH2s5FD1MoNo6eRe+0unQ9eT9hZ1BZ7Ho0QrjUwYvsFfQAGhOsMah4Vtx/5X0vioA9ge4TIC+KKqvtjBCNE/rUCY3c7dMcwGoNEn1mHtiO9a6cjOvD7z0fJyUgbBry9yVpGN+Ws/XfvX1OAxmAjYS25H9TivYvT5I05Ha++ltwJmkZgQYImxGmksyl5ZbpVb1WnwRNrWvYkd93FTz2WJk/MiSWr0Bk1iGXaOWT4HBPdIB78pZOOdU+YHg/XLndkv2azdUbKzrX3CtkOBGtp69hqOmZ37VtCtgHer3nG9Hh3rJPmoLNWGulkRXut5Zi/blsqZLszGqXarJ8AEAM2dVqrusbjoW32gq49QbF5ZVGd9QuIgINuJtsbdYIJhCkXbXYW+AUDOlYVZK2NBuFusTIzwzCItpqfG20x0MNi9rU11vdeW5saFWR9eytED9180Dc2psR+Io7owG9IibU6z8FUFTlXCkuez8bHkOdJPm2hwNs3anHuquRTXFwDel8tU6AvMHklfZOWKLuSK5iuGide3O4EyZ18wb6c7Ty9JUOGzyyVYgIm6cZdZC7uIbudqet5s/pZjskpHCNm212AopiLQOT47Qt7HUy/XPN7IyGR7T58FcNzFev03zE5YmrLPkWxVcdU7hWbSwf47Z1X7BGbV4q86V0TFmUnXnhU5DkTOnPbUBtV3eASnHIlSeIQvaSDx6gQR/PInv1cG+uHHHHF0wOuVRD/+SAVpneN99mIOAT5yWmjKcyy/+2aO6yYo4f3gaz7/zX3/jUFcCtuzh1+blLn/PnYP6fJG3NKf/AD5Dz7gWr2KaeQNdta2jvVnH3D5KTPOfOaSal3xM51v/cj22NzS8sYMXNuGr1JTMFFo5Ian31cJbInNQ/yDBkOK86Zb2uYKyf5TVIASmwELgPFAieAwmnfBpPgqfSE3wnbBphw3F9Nj0uym6GTvydkW1W9zBj/Q6QEy6z8nGGMHHJoqwq7zOh3Ftlq4o3VY6q+ikf1C9uvcFlv2l5UcZyw/ZvHWdeV/mT0sUK2VVnmh2MmmY45vaKSIo+YOuOfp4+2HDM6xy+sGvrLKdY1XtePFq8fLM2VOXaUesjGs9cFp010tgmqqhL9hiQOLSQZJs1xISviAWbxseZRXfEJLmGlbtdFReaRkQTur6QmTpD756FMP/AZKg3MQ5lsvSHlhCNe1dMwDN7f3kJTZzebGwKMKstlyY4mPKrM7qYgsiIxdWABJ44pF3pDmFJuLgYS53V/woXPw6hj0u5OIhq6Gnh6y9Msr1vOrvZdeFUvET1Csa+Yc0ecy3t732NU4SiuGH8FksgrrRRhxGIE166le/VqDE1Db+8gtHkzWns7rrIyck44ASPQSfa8ebj6pfeHZsXTty6jtT6A6pHRIjrhoIHLKyFJMjmFHgItYUbNrWDuOWLy1qlC1zTeeug+WvbWUDVxCtkFBXQ2NjL6mONZ9er/CIe6GD37GCpH22ylkSaMmE7bO7sJbWhBaw1CyOiRslJlcMsQNXAPK6DozKEombd9hxUZVc/ksDM/Jqz1mzEez3HJ9ec8mEi4G+Oua+IeU665C9XtXPo8sP1toq1byJ14KV1bX0YPd5I7/svIcmo2bHasvp/mPe+SVzoZt6+YzubVlFSeSNngUx3bjkQ7aWxZQ33jcjoCuygsHM3A8mPJzx2SAs9hS/OHvLH1AdojjQzOm8igwvGMLp5Hrtf54rQ20MTZH/3qkL8rSLw79w+oijN9wLAW4+/blvFEzTqiGPiR8CguLhk0lQuqnM8hwViMh7du4tXaaoo9Xqpycsh2ubh40HBKBN/27c9ta7fw4t5mPIDXpaBgkKWq/HziCIbmOltPGobBEzs6eGJrB11aT8sFRYLheSp/nFHmSNhlH50hg66wTnWLTo5HYlS/1Ok9dgc0NnwUo2yghMulEItpqKpCQansqJXDPrSwTnCHjqdUItxioId10CWyRygoHuf3Jra8E71bR3LJ6F4w1nYjDXbjmZXv2PbBGB1h9NZupGw3cpH1Zk1G1dMCXTf4x+LtvLu5iZim43PJeF0q3VGdWDRGDFhV3cYxI9OromNJzVpsBX0Az1wBPzGvHUgnDd0NaJrGnq49NIWa0NHxyl4auhu4d/W99Mvqx3PbnkNC4ooJzgrMnaB1dNDwhz8S3rwZtawMJTcXV3k5WnsbXYsW0bVwIa5+FXhGj+7TwE/XDRSXTCRoEAl+mrgf7TYAjeZgT875qtdrGDm1nJIqcSUyJxiGQc2GtVSOGUt3oIMPn/8PyBKq6uLDl/4Luk5hvwG01tQw4aRTGTX76D7xE6B7czOh5Y1ooWhPMYcCRICIDkEdVIhubye4romco/o26M+QIZ2Et5jU7y1dAw4DP2PxiwmPaa8/gnr6lY7sAyj+IlqX30fHhv+g5lbhKRhMYMPT5Iw6B+mQZmHJoWlRutq3EQpUEw7uweUpwZtVhuJOzUZwsLuBdVv/RSzaRWH+KILBerbufo7hVWeTlzPIke22UAMr6l4mbASRZZUdHatY2/wOaxre4ZIJv8OtOgtu7t/xSty/axi8sOd9zh7oLKvj1dotPFKz9pP/DmIQ1CI8W7OOM/qPIEt1tin3au1uFjbX0aZFaQ5G2RTspFh1U+nL4vyqoY5s67rOkqZ2YvRMMV3Rnrk7R4vSGklQQJcEtcEYT+8I0LJ/LZ8BG9ti7O4MMzTf2WfbEtDZ1aIzoEBm+mBnv6F4+LIVxsyQ2bYmSmtjFJcHBgyTUVNwKcMw6N5l0L4yRqTZwNBA8kLWQBlvqYKSgsx1XdfRFnb0/Idk9GwaRw1iVWHUfuIqxfGQcj0ouam1aXq9I/mNn64bDP/pS2g2/4m/O2ccF84Qlz8WZvO78OgXkj/vZrHCZCfcuvRWHtnwiO3x5f5yXj/v9TR6FJ/uLVvYeab9e1p01VWUXtv7CqSapnPPd95J6pw5Fwxj0nGJm8emA8MweOZ3N7NzpX0FzKoJkzn3p79Mo1fxaXpkPaG19tOnXZXZlF2dfMpthvSQeeOXHGbzY3jJR7DAWgDFVqP3ePbvvRECFr81tw/PNX8Rsg/Q8uG9dKx6KO4x2VtA5XlPIQsGabFIF0ueTZxyWNjvaMbO+4OQbYBNO5/hw9WJm6jPmPAjhg86W8j2luZl3L/iGkioWS7xf0e/TLZbrM7+pAU/otMwFx+bkTeCOycJqJID31r2HKs7zcX0/jPrQip8YnWcX1n8FruCiUU4Krw+npor3hJr3mvvmx4/r7KU744Re6u7qC7IT1eY/65+ODaf0weK3ZtV1TGeXBpF7+mGwDlTXUwbnNr3QM11Goteihzy9Swsk5h3hrMsgJpHQ4T2JF7YF8xSKZorHmF2318H1YmDd+XEXNxH5wvbd4rTOfKIrvF7ePEO20EfwM3Pr0+fM2aIBH19QEOwgUc3PprUOXXBOtY2rbUemGJqr78+qfHN995LX2yCrH0nedW1xU/1/tve6nVrkgr6AHatXoGuOZAeE8CI6kkFfQDRmgB6yLmEdYYMhx02gj6AmFXbm0RYBX0AEWeKuR2r/5nwmB5qpXPT88K2t680r0Fv2buASEhcWn352jtMj69Yf5ew7Z5WDmZzlsGzG8WDVqugD2Bp+2Zh+1ZBH8Btm94Tsr2xvc006AOoDXXzYbOYeuJfNuy0HPNUjbhC/K1rrH9Xf1zXJmz/tbUx9I+/Ogbw6lqb2WZJsOGjaNyvZ0u9QUu9+LogtFc3DfoAWt+PoYUEVUN1wzToA9De7hCyfbhwRAd+jZ3JtR6ICvZ0+bzQFe1CN5K/R03BpjR4Y47WmaSkv65DLwcpAF0dyaeECHwEjglbSGMnQtN6N6AyBH/DeiTz28/w+UULHMbtTCweeHpYPPMlErbux6Vr4vdG180X1FqS7ZH2J2LDr65IavqN9RVtEbG+ym0Re/e1KUGfPytqu8XOs4ud6cjJjNUdPTAoCkVJ+cZ3NJLYXtRBJqxmp02DcVB/v2Swc2M/48uFIzrw+8bRyeVwnzWhj2p9hp/eN9dNksF5g5laNjWpc1yyi2MHHpseh0wouS65xrJZs2cjqb1f8jr5pORTNgdPLEqDJ+YMmjiF3JLk6mCzCwpxuXsvbx1A9qgohcldU/IqqLkZgZcMRyB59lIgPSWHr+y/p3xK4oOSQvYI8YyZIRPji9J8cm1/ha2WDwntV55ienzwgNOEbc8ZcL7lmDOGXyts3w7ZsvjzPUexfuZ+c9gMIdtHFZfisRD+UYH55f2F7P9kwjDLMcNzxGvwvlRl/bs9sVw8XfKog9I6pw9RUi7EN2RM/FRLtxeK+4mHHv6BMoqF/olvsISaI/bvkVQJLG6tNMK5YFVfckQHfgVZbp7/zhy8qvUX4KyJFfzpwj6q8/nKoyT9UfRBfR/A3SfczfenfJ+KrIqEY2RkZEmmKqeKl895uRe9+5T8M8+g5Cc/gf2DOVVFysqC/SWWFZmcM05nwP339b6TgC/bzTlJtHSoHFPAaVdNTKNH8XG5PVz0yz8y80sXMnT6LFRP4glfcXsYMHYCV/zlgV708FPKr5uGe5A9ARy11EfFT8QWFxkyHO54vnWR9aBLxWrMADzXW//G7Ywxo+L0u/EPPpGeaiRAUpC8BXjKp9DvrIdx5Yot3gH8uVWMPfpOJPnAhZyseCnsN4+ppz7mwHOYOflnjBxyPorsQZJUXGouXnchOVkDmDjqKo6aaL9FzsEcXfVlzh75Q3LcRUgcGOSosptLJvyeyjzrtgOJeP+YO0yPu5F5Y17i+kUr/jfvYopMevn938hjmF4o1udQkiSemHM8I3PizwOD/dk8NucEZFlsCZytqvxqQuIXC+Pzsvj7TPE+tt8YVcB5AxJHN7OKXPxscomw/fnjVM6b7mL6YIVzpro4Y2LqxV2qRqpMO95FVg7ICqgu6DdY5rhzvCgOWjlIisSAy7z4h0mHLJtlLxTOUak4y9mGs+eGSiiKs3Gggjw9C89F4vf+cOCIFnfJkCFDhgyfLTLiLsmRmR8zZMiQ4fNDpp2DBU9/VMP/PbeWYMS6fuuXZ43h4lmDe8GrONycZDPOqVfBmc6a14pwz8p7uHvV3bbGDsgZwL0n3cuAnAFp9upQ9EiEPd+/jsBbb4HZ5oYsoxYXU3rDDeSdeUbvObgfO9Y08tJf15jX6e/HFbfPw+tL/Q6dFYse+ydLn3vKVi1AQUV/Lv3j3Sh9kD4bawtR9/tltvPwc784hNyZ4m8NMmQ4nEnYw28fXheeay8Ts71zHfzndvNBZ38PzxCxnmxauJO6V68j2rjmk7/J3gL6n/MIii81Ke+r3/kO7fWHBs7ZhWOYdOLfkSTxxCjd0Hht4ZU0tx0qHFeQO4pTj3lI2L5uaPx64RfojMSvoS/PGsZlk/5AoU8sVXVl81a+tdZcfOaVWb8iX1BRdUXrXr6z4n8Jj0/KK+OvU8XTeO/ZtI5HqrcnPH5KWX9uGm+SRmzBVxauYHd34lrCh44az7C8LCHbXTGd017fk/C4S4Jnju9Hrtt5H8sPtsd4d2Psk7q/LI/E8aNVplSlZu7esz3GmvejREKgqDB8osoIh28YOzfGqH8xvnhM9kiZ0lPcyA56BWrbQkT+1wxNB8UNMri+VIQ6XuxzPRhD04m9sQ1tXT1Sjgf1xGEog8VUeJPhiE713FDbwQ+eWmUr6AP42XPr6Qr3gbrfzQKNVj/6W+r9sCAYDdoO+gCqO6v53tvfS59DJjTddTeBN980D/oAdJ1YQwN7b7yR8I4dvePcfoS6orycRNAH8K+fLE6fQwlordvLB/990nYBeGvtHl6+67Y0exWfuruXJ1V83fHfxIuDDBk+y1gGfdCj7CCKVdAH8OwdwuZbPvjzAUEf9Ch51r92g7DN/anf+UrcoA8g0LKePZuSU7E+mOVr7ogb9AG0dmzkg1W/Fbb9xNpfJgz6AOq6tvLvNT8Vtm8V9AGcsuQmYftmQR/AyvZ6Xq8z6UFpQiAWNQ36AF6p38OeYJIicB/zQnWdadAHcMUHa0yPm3Hpgr2mx6MGfPcDcdXQfexq1vjv8iitQYNQtOdR0BwweHpZlPoO5womXR06H70TJdzdsxSLRWHDhzFqdzoT0ksU9AEENuk0LxB/phndOpHHGg8N+gB0iD7djJFMuwATtA+q0ZbVQDCKUR8g+vQajF6IQY7owG/pjuQVrZZsS04KPjWkXko3HSzem3zAsbl1MxHNeTPTZAksWpTcCbpOsA/SpRp3dVrGpgcT6e599dHN7yd5P4GajevS4IkNOpO/P4Z++Ke8Z8iQLmJN4i0L0kn3ng/i/j3SvCkl9ut3vGB+fGf8BuZ22dOwxNx+k712G/HY0Gz9TK7uWC+kxJ1ugjF7a57n924Usv9+Y709+3t2C9n/r41WDU7ueqMN5cpdAecBwo7G+F4aJseSoblej7u+aaoTX8OEG3XLjfLuanHf9b0RMFEkxQC9WlyN94Br7Wo78A9hDaOuMyW2zTiiA78JlUmmTwJTq/JT78gRQrKKntCT7um2od6VavxTk/fVN04sHckJRZXJp8mort7/2Q6eND3pc0oHJaeqmzK8yd8fSU6tolmGDJ8llKL8vnYhLu6S+M9kV15qygeKK481PV5YMceR/ZKi8eb280cJ2x6UZy0eUpY1GNlBqmq68Kv2Uv2OLRkkZH9qkT3xjRPKxNJgjy9Lr7J2nst6Pir1Ok/zrCxI/N0wO2aX/OL4NhL93Q4uG7feUy5uXy53WRbBSRWpKbWRKnIO/IMqI5WIpU4nw+H3REghkwcW8ONTR2F3TfetowdTkNW78vOAmEJnee8rERZ4C/jCEPs593muPG4/1kYqUBooufa7eCfaU7+UfD7KfvJjvKPFFdBE8ee6Oe7i5Cb/C3/R+5996aDBjDn6eNvjfbl5nHFtatKxkqX0m5OSGp81L7FCbYYMn2Xk6y6zNU5Yyn3eedZjZp4lZhsonn09cs6B9beS4qH0pNSkkVcMOxd/7pC4xzxZ/aga/3VH9o+a8CP8CWrs/N4yZk7+mbDtSyb+DrecuGVAjquYr4z/tbD9Hw+xbhfxxNSfCNu/ecxxpscrvTl8acBYIdsFbg/HlZSbjpmSX8iI3Hwh+18Z0p9cxXz5/PvJw4VsA9w/27x1kgT8ZWZy7ZXiMaxM4cQxKm4VZKnHrtcFp01QqSx0Hh7kFsiMn+VC2RdISTB4jEzlUPGgVZZlio5LHJl5KyWKjxEPzKQsBdfZRZDgp6WekofscR50A6izq5DHlIIkQY4H11mjkfzp12/4XKh66rpBJKrRFoqS5VaRDJ2uqE53VKPI76IlGGFgUXbK+5gkzd6NcN+x9HzjDk5TVQEFRp4PF1nn3qebTc2bIAa6pJPjzaEsq4ywFqajuwNZlsn35eNV+77XiR4OY2gaejiM5HIhaRq6riO7XMgeDwYgKQqSoKxzqjAMg2AgRCgQQdd0opEYwfYwmg65hX4MIDvXS26RRQObNKNrGqFgFy63m2BHB4qq4vZ6CbS24svNIRoK483Owe3t+88+1hWhu6EDXAquLDdGMIa72E+oIUCsW0N2y+QMOnz7l31eyah6Joed+TG8YTM8/+6BfywvwnPpOSnxIbz+A1j6Jmg6SCpkZcOwEXimzk+JfUOLEgu2InuyUNypEVbYHy0WIRYLEIuGkGQVtycfVU1dpkpMCxPTImixEJKs4Fb9qCmaH4ORLqJaN27VSyQWRtc1sry5uJXU2P+wcSPPb1pMl9ZFBAMDg8tHn8aUUvHAZn9qgx1sb28Cw0CWoMiXzaCcItyKc3ERwzDY0dmOKkm4ZQW3otARiTIgOxslBXN+RNPY1h5AAYo8LtpiUbyqm/5Z4j389qc1FGNLcyc+VaE1GiNbVRhe4CfHk9rgQP84DjCMnhhETvFa2DAMdN1AkiTkFGbXxLpiKD6lp+ZO6tnAkhy0itgfwzBABz2sYygGaKD60yNWZ2g6yJLtGMTpHHnEB3717SGu+McyNtV3YugGitQzN+3LjlaAHJ/C6H55/PKscQwrzTEzlz7+PAta4xeBx6WP+viFY2EueekS1n/sq0tyETV68vVlZPT9Mtvn9ZvHX0/6a5/4CVB7yy20/ecZiEZ6csL3fddVtef/VxTknByKr7ySoq9d1md+rn67moVPbLE19qQrxjBiuvlOZjoJtrex4NF/ULt5I4HWHmEBWXUT6e5CdblQ3F4KysqY/61rKerf+2qu+2h+fAPdKxMLH+xDynNTcf005BSoo2VIDZnALzms5kcrgRf5ustwucQXkuG/XQfBjgTGVTzfv0fYNkBwz1Jal/2NaPNmoKc2SMmpJHvICWSP+IKjPn6GHmPbqr9St/UpDP3AWnR//kjGHXMHHq/45lA40sHqjffS3LaejkA10ViPmIgkKVT1n8+cKT8Xtg2g6TEeWfNTNjd/gGFoyKi4XV4UVCZXnMxpw692ZH/mu99LeMyPi7eO+YOwbd0wOP7tvxOJU7DVz5PN47MuQHUQnMV0nYd3bOKfO7YeUG8nAePzCvnDpOlkucSD+6ZQhKs+WE1dHDGOY4rz+NUUZxlEL1Z3cvvaNuJV8pW5ZZ48wZkSdUtA59nlEWrbDWTA74GJA1SOG52aoHLL6ig71seIRUFxgRbt6ec3corK4FHOrxFt1encqBFp1ejabGDEABVyRiiUzFeRVfHvjtGtE3m9FX1tsKfeT++xrZxbhHtMajae9F2taDtakcuykUeVJPXiKRP4mRAIx5h486vYFeCRJXj52qMZWd7Lwd97d8HrAupbfRD8Tf/XdEJ6yPb4QbmDeOFs8wL6dLDrkksJLl1qe3z+RRdS8XNnk7AI21fX8/JfkxNBOeOa8VSN7f0Got2BTh64+goi3UHrwZLElXc+QF5pWfodO4j6e1cS3ZFEgbQElb+dlz6HMiRFJvBLDrP5MXzv49Bm/Vvw3CiW0hi++1oIdVmMkvBcb0NdNA6Bra/Q9O7NiS2rPirOehB3vlgbpuWvXkJXm5lQjMLsc95AcSWfaRGLhfjvG18kHEksnFOUP4ZTjn4oadv7+NWCM+iINCY8PqLwKK6ccqeQbbOgbx9uFBYcI5Z2O/st8++EW1J457jLhWwDXL98CR+0JN7880kyrx1/mlCmV1MowjkLlptqjMwqzuP3gsHfw1vaeWhrgs2Uj/FK8OopYpur9R06d74eJp6m2ahymUvnOit5WvZmmL07EwusDJ+gMGa6eNAdbtSp+XcYI4FGkJoDg74l9tbViOiE/rwXOuP77768FGWQs7fpsRV7if3v0+eOMq0/rlNG2D7f6Rx5RNf4/eO9nbaDPgDdgAcW9oG0u0jQ1wdsa9uWVNAHsLNjZ5+oigWXLUtqfPt/nkmTJ+a8dv+GpM9546Hkz0kFmxYvtBf0ARgG7z35SHodSkBSQR+AAeFd5pNshgyfSWwEfQCRPXVi9i2DPkiqV81BtK140NxyrJvAxueEbIe7Gy2CPgCNuu3PC9nfU7/INOgDErZ6sENbqN406APY0mJ/81OECGLqjIGYtdJ3xNBoCIm1W2gKh0yDPoBuQ2dJs1hLhFdrmyy/1UuaxDfmn9huPR+FHLyz+WBbLG7QB7Cpztl6zdAN06APYPt6Z8rkHatiCYM+gFgnhBvErqFt7k4Y9AFE/mOdSWR5jQ+qD/zv5XsxbLadSwVHdODnUpPfyVFTlB98JOKSxF7PS3wG7mkfqTqKZLKkMkc+qesqyaVD9kXzdlFSVReQIcNnEvXwTHWWZBt+2RkTz7ZNtUtJFnuOSVJ676k9/w/P55pdr0QVSWWbV3AJ2lfSrAeRbrkJU12aFFzbyn/H/z47H5tgdGOp8J2K9dfBNvYp6/QSR3Tgd/HMQbiSWNApMnzj6D6QoD/bfFfzcGFg3kBy1OTSYMcUjukT0Zzs4+0rUAIUXHppmjwx5/Sr7SmP7s8p3zKXCE8XI2fNw5eTa2usJMnMueDiNHsUH8+YJGtyFHBX9lFtb4YM6aTCXkq4u0wwdTzbxm9NEa/nyZ92lelx2ZNLzigxgRq3t4jc4kmmYyTZQ9ngM4Ts9y+bg99nnupeXjxTyDZAnqeEIp95qt+4UnPlTDPszNo5kljKW5YN4Zws2UWxR0zMrNDj4fhS81YN2arKdJttHw7m5H7Flovnk8vFWz5cNty6FVmOg33VmUPVhMHfhEpnYYEkSwwYbm5j+CRnm8J5k1Vkk6+eqwA8xWIbL/IIHxQmPtd9frGQ3f1R51Qd8N/KjEokV+9tvh3RNX4AnaEo1zy2nA93tqLrOi5FRtd1Oj9u0Jjtlsj3u5laVcRPTx9NaW4fqRE+/2NYnoQQSh+Ju+i6znVvX8c7e97BMAyyXdkEo0E0NNyym7D+aWPLr476KjcedWOf+AnQ9Pe/03Tf/Rjd3T1/iEZ6doe9XiRdB5cLtbCQ0u99j9xTTu4zP2s2tPDcn1daD1TgnOsnUzGkIO0+JSLSHeSD/z7Fnk0baK+rxcDA488i0NyE2+fH5fdTWNGfE6+8iuyC9PY6MqPtjR0E3qyxzDJTBmRR/q3JmTd+hxGZGr/ksBR3+cfTUJc45VC0vu8T+4/9DvZujX8wuxDPN3/vzH7zJlo/uo9Q7QqIBQEJd+kEsgYdS/awk1F84uIrhmGwd8uT7Fr7AFp0//Q6iYKKOYya9UtUgfq+fcS0EBu2PkpT61raO3fQHW5G1zVUxcWooV9l4qgrhW3v8//5zbezqv51ND2GgorfXYCEzqwB5zJ7wLmO7J/87k9oJ356/yBXCY/PdlamcuaCf9IcO7QZ9uSccu6adoajTWPDMHhhzy7+vHEt4Y8nAglQkTimtIKfjp2EK8kslv3pjMb40UcbWN1xaLrzZYPKuWLEIGHbAMsaurh5ZQuBOBmA4/Nc3DXbmchbZ8jg5dVhdjUbuBTwuyWmDlKZOig1mTo122JsXRMlEgK3FyJhUGSJsUeplA90fo1Yl0HXZo1op0bHWh09BJIX8sYrFM11OfvuRHWi73WgfRiAsA4RwCuhXFqMu19qFFv1+gD6jhakshyUwcmt6TLiLjbQdINNde2s2t1GXUc3w4pz2dTQwdXHD2djXSf98n19F/Dtzz/Ohx2vWo/7eVv6cwEs0HSNBTUL2Nq6lRJfCX7VT1esi45IB9tbtzO3ci7HVx2PIpiGkyqC69cT3roV2ePFkCVkjxfZpaIFu3EVF6Hk5eEZNKhPfQRobQiwYfFeVJdMuFujtS5IXomXfsMK6GzpJtKtM/KoMgrK0t/c0wwtFqOjsQFPVjbbV35EZ1MDw2fMoqulhZa6PRT2H0hWbi7FA6qsjaWZUEOAzoV7UEq8uIr9aC0hJK9KZG8nekMQ/4wKsseUIDlQ/8qQejKBX3LYaufwyLOwJ05tytfOxlPqfAc7/ND/QcveA/9Y0A/P5bc4tg0Qaa9GiwQwtCjoUWRXFp6i4fZSQS3QYhFa65fS0bQew4jicRdQVDkPt78YRXW+yIvFQmh6GFlSiEQCBMNN5OcOwaWmpjVPbec26gLb6J87ku5YF4FwKx7Fw7Ci1PyETn33x7TSfcDfBkklPH50arQJVrXu5e367bSEQ/hlF8V+L2f3H0uR1/lcpxkG/9q+GV3XGJFTQEsshEdWmFlcRp7bec/mTW0dPLFzL4oEZR4v+R4X+V43J9p8027FGzUdvFbdCZKErGk0xySuGpPPlBQ3+Y5pBoGwgUuRyPKkbm3Z2hyjq02noETB5ZHo7oLsPFAseiDawdANtG4I12loegw1S8XfL3XlJXprDCOsIxWpENQxDANJlpBylJRlsRndUQxZQopokO3OtHPYHyeB3/vbm/nK/e9biryMKMvmmW/PIdvTB3VJhgG/yE/uHDUfbtqVDm8seWPnG3z/3e/bGnvTUTdxwagL0uzRoURq9rDt9NMhfOhu4sHIBQUMee6/uEqdN0RNlmhE48EbFhAL2/sdqh6Zy347B08vNPk8mC3L3uelO39PLGJdmK+6PZz/899SMcy+UlUqqfm/RT0yzDYouGAkWZN7/7PPEJ9M4Jccpqqe7e1wz5OWNoRVPVcvgtcfNh805WQ8x9lo9B6HaPtuap+/Aj0ST6RGoviYm8keJp6tsWPlX6jZlFiEqmr8txg45mvC9jdse5TVG+8jpnUfcmxY1TkcNVE8I6Y7GuBXC08nmlBwTeKa6Q8yIG+MkP2rPrqTFQFzsbuv9z+ZK4adKmR/T7CD899/ImFSxmBfHv+eZd1EPhH3b1nPP3ZtS3h8WkExd0ydJWRb13WOf2OpqbTNvTPGMCbfXmnEwezsjHDponrTMY8eXUb/LOe9JpfvivHs8iixj/8xI8okvjLLg1tAI2MfXR06bz0TRk9wg8bOUBk2XnwN07Vdo/aFSM+buP2RYdC33ag+8Q0hPaIR/ksdtCdwPl/B85US5DLxe29oOtHnN6Cvb/gkK0nK9+I6ZyxyP+vvTEbV0wTDMPjmvz6ypey5uT7A/QsSPyTSSrJBH0CsLdVe2MIwDG5YeIPt8b/+4Nf0xeZCzfXX2wr6APTWVvb+wP6/KZUsfGKL7aAPIBbWefuRjWn0KMF1IxFevus2W0Ffz/gwL9z+uzR7FZ/OhTW2gz6A1ic2ofeiolaGDL2GjaAPINwuqGprFfQBLLeRxZKAxgW/TBD0ARg0LRSfX2KRgGnQB7BrzT0EWjcL2e8I7GL5uj/HDfoAtu56hobmFUK2Af695icmQR+AwYMrvids3yroA7h/j/hn+4PVr5hm4u/obmdla62wfbOgD+DD1ia2d4p973+2arOlnuk1y8TVt69+31pt9IZl5oqudugKGzzz0adBH8DmeoPFW+N1D7TPsrciCYM+gHXLYmgxsd+toRk0vBwn6APQYc8T9tYoiYi92Jo46ANo04i+YK7Wa4W2shZ9XcMBpShGW4joi72ztjuiA79AOEZ7t4nm60Gs3ZuRdLcipIWI6fYfCgYGIS25FhCpILI1Qc1JovE7d6bHEQvqt7clfU7j7iTbFaSAQEsz0VD8BUwigm0tafLG4robk7+u1tr739EMGQ4bVvRNixgrom07zAfoEYxYcs+lfYQCNbbGBdvFNoTbOqzPszMmEXVd1oFZMNb7c4Vdam20aljQuFPIdlizt5G3tEUseFrfbt3GJOJgw7vTRlBU3+28TVZTQEeLY6au3dlmfVeHxfkGhIKCGzZdBppJVymn70T0OuuYQW9wFlwaDfG/P0ajnfY4zjmiA78cr4shJVm2x58wqvebTQOQK9Z8ti/wqT5yXPYVED2KB18K6iSSJfvYY5ManzVbLOXDKSNnVSR9zvDpvZ+WmFdWTk5xcnULxVV9873OPaYyuRNcEmpJauptMmT4LOI59qi+diEuvkpz1UvZV4gsKL7izx+GpXalpJJXOlXIfmnRZBTFvI6svGSGkG2AscVHW44p8Q8Utp9upuRbz30XVYkpWHtsirac2i/JueJjzuxvPQcXusXLhqqyrP2fVOg8zbNfvky8bNER5c5Cg+IK8/MVFfw5YqmkrlwZd3Hic32DnNXfKWOs16vKMGdrWnlofEEqeYi4UFVS1++Vq/Qh/77yKKqKzCcGRZa4ZGYVF80wl0ZOG9etTP6cU/+Scjfs8sQZT+CR7RVGP3XGU2n2Jj79fvVL3KNG2RqbNXcuFb/+dZo9is+U+VX0H5lve3z/UfkcdWbvtxyRJIlzf/pLSgcNsdV8sGTQEL70k9QIOySLb0QhrmHWctj7KLt6snXvngwZPoPYqt3LFhc2U757t+UY+YrfCtsvnvNjvBXTiBegKVmllJ/2N2Hbsqwy9ujbIUG/PdVbwrijb8PjF9to83oKOO6o2ykpnIjPW4JLzWHfv0NV/Myb9jtys8UDs7NH/5ABuWMTHs9yFXLNDPFWUQ+O/57lmFdnic+bvx1/EiUmQftFA8ZR4hEXMXlw+lzT498dPoY8l5jAy+XDB1DlT3yuS5J4Yu5kIdsAD8ypwG0yJWXL8JtpzjeAXYrE1+Z56J8vocrgd8Mp4xSmVDnTuph2vIvcgjj/AAm8fph1in0hk3iUf9GNf9Ch6xBXAfT7ojOhRtex+cjjfZ8+clyASs9/u0Ae78d1prMATRlRjHrKCKQiP/hckOVCHluG6wujHdm1yxEv7pIhQ4YMGT47ZMRdkiMzP2bIkCHD5wenc2QfSFj2Lu9sauCaR5fTGf4059ulQJ7XRWt3DE3vCXzH9cvhP1fNwdOLTRQP4Gb7bygAuG4r5KZGMjgZWkOtXPX6VaxrWWc5dnzheO484U6K/c7lwkVoffFF6m78EcTL91dV5NxcJMBdVUXF736Lp6pvWhC8/vB6Nr9fZznOn+di/uVj6T+yd9IB4hEOdrHg3w+x7aOlhAKdaNFD8+E92Tkc/eVLmXDCKX3gIUSbg9TfuaKn/44N8q8YTfbwvvmOZsiQbsK33m8+YO4UPHPE0hkBwreZ96JzX3e/8O6+oWu0Lb+f9jWPwCG15TIFs24gb8zZQrb3sW3Fnezd/O9D/i678jjqjGdQ3c6k83fvfZsV6+8mEKze768SVf1PYe7Umx3Zfn7j7SyqeRL49Fkno+JSPIwpnsf5Y3+GIost82JajLmLfmA65v1j7hCyDRDRNX629k0WNsVXJ//7lDMZnS/eq649EubKDxZQGz6wflsChmXncve02fhVcWXJ6z5cz7KW+LoQMvDGiTNw2ciOScSX3qimKUG52ewSD7918MZP0w3e2RhlyVaNiNZzT3QD3AoMKJKYN8LF0FLna2HDMNiyOsrmlRq6Bv4cmH2qB3+2s2TDSJPGnqcjaPuXsEqQN02h5FjnKbChpxox1sSpHZZBOSUP98wk1+sHYXRFiC3ehb69FVwKyvgylKn9ey3z6IhO9axuCXLZQ8sOCPoAoho0dUU/CfoA1u7t5KTb3+1tF3u496Tkz/nTsNT7YYPzXzjfVtAHsKZlDV96/kt9ourZtXgxdT+4IX7QBxCLobe0oLW00L1iBTu+eDaGTcXKVLLijd22gj6AYHuU/96+koZdfSdC9MzvfsHqN16hq7UlbtAHEA508vp9d7FpyaJe9q6H+j9+ZDvoA2j7+wYM/fDPfMiQIVksgz6ARcvF7VsEfQCRP4k3iG9Z+hfaVz0cJ+gD0Gldciuh+tXi9us+jBv0AejRdpa+cJawbYDq2ndY+OGPDgr6AAx27XmZD1aJKx+/uf1BFtU8zv5BH4BOjLDWxYr6V3hwpb22S/GwCvoAZr37PWH7V330fMKgD+CK5S8I2wb48ntvHxL0QY+Q4pZAB19e/Law7T+t354w6IOeT+TEN5YK279y4d6EQR/A4sYwd65rFrb/8uoob6zX6Ir0rIcjGsR0CEZhU53BAwsi7GxyrnS9eWWMDR9qaLGermVdHfDWf8LoDuZbPWKw++GDgj4AA9qXaXSsty/oGI/wqy3xgz4AHbSX2oltFxOUgp5gOPLoKrQPajAauzD2dhB7dQuxt3qvq8ARHfj9faG16tX+7G4R/zAdUSv+gOhNtrVtoy5oL0jZR0u4hU2tm9Lkkcl1H30sqfFGdzdd77+fJm8S8+H/diZ9zuZl5v190kWgpZm9m9bbHv/R/55NozfxCdV0YqoRnoCulX1zTzNkOBwILxFvK5BOAptftBzTtkK8jm3rsl+ZHtdiAbSoiYSgBdurXzI9vqPmFWHb71Vb189va/1I2L4dRJfvmqGzobPJctxbdWKL4eZwiHbNPABoioQJxMSChBdqrNst6CC86b0lYB10vVAt/r38cJe1/RW7nQd+OzceumGjxaClXlyRNLhDN/3iNS9w1opCX2qtNht7s13YvlEfwKg/9Bra6uTW1k44ogO/qiL7ip4AGX0Hc/I8Yq+3CzwFKfbEGle/5NUy1bLeV3X1ZiefauLPdZ7KIILb70dW7acNZRcUpdGb+Ki5Yqk7rtLknhUZMhxRVIqn1KUT2ZtvOUbNTv5Zvw9vVn9rHxTx563PY/4MdKniz50sd77lGJdNEbbeRkZCtVJUBQZm5QvZ99ucpzyyWDqjV7G3dBZNcbZzlt9BoVaOja9Fjsf5gtibQLvH6xe3rVj8ZNQsh357bZxfIH7zJb877gcsZffeuu6IDvy+PHMguV77H9Dlcwalzxkzrj48d1sPpthXzEUjL0rqnDOGnEFZVu8HVEVXXgku+0GAf+ZReEeOTKNH8Tnre5OSGp9d4GHs3H7pccYCt9fH3AsvtTVWcbk59lLxFC9R1FwvakmSUssSeCrttyjJkOEzw7RxtoZ5BggGTwU2nkXZ4vWzxbNvMB8gyRTMuFrY/ph5t5oeL+p/ApJgjRzAmOEX43Yl3jCdPeVmYdsXjrU+99Rh4vcmW7JWR5yVKzZnSpLE5UPM60p9ssqwHLHNQ5+icmq5eVB/er8BwjV4t0+1Vgwflyse1P9gjPUm+y+niGs8nD7RbRpcluRIzBzmXAJk3FGHBjPFFRLZeeKhh69SwWVS3lh+jjO/XV+2uK8SuE8Tf5kh5XpQZh+kJ6FIqCf0nlr7Ea/qaRgGDy/eyatra+nojuJxKZw4powhxX4Wb2th7Z52cn0qN502luHlfbz4syvwUjweru6b+imArW1bufWDW9ndsRuv4qXQV0hTdxOdoU5aoi0oKMzpP4erJl3F2OLEctPpxohGaXzgAVr/9Qi6puGfMhnZ6yVaswf/3Ln4hg8jsns3vkmTyJ5p3i8qnWgxnf/dvYo9m1vR92VXSKC6QddBQqKwXzZTThnI0Imlfd56oKOxgS3LlhAJh9izcT1dbW0Yuk5OYSGK6mLAuAlMOulUFAeF807pWllPx1u70VpCoAFZMgQ+Ti/xyD01gBL4ZpRSdHbvB/wZEpNR9UwOq/kx3NoK9z0d/6ACnh8426AJb1sN/70z/sHTv45nlLMegVq4nfa1TxPc8SaSy0cs3AWxTvyDT6R45vccycIDGIbOukU3EmhZjydrIIHWjaguP2Pn/p7cFMxfmhahpn4hu/e+Q0vbRiRJoSBnGEdN/hFulzPhmEgsxAub76CucythPUiRfyAV2UPR9CizKr9Evs/ZpuvjO97mjt3PxT328OTrGZXrrAVWTbCdf+1YyZsN2+k2Yhj0vAz5etUULhsqLji0j00dbfxy7XKaQ2FkyaDcl0WF18/Fg4czMi/fke1ILMa3P1jH9q5u9k8YVYBbJ47gqDJnImzNIY2vvLOXbgNygH0lbSOyFe6cVY5PdfbepitssGJXjM6QTkGWRH07lOdLlGTLVBXLKClaZ0QjBjs2RGlvMhg0WqGkX2o0Jbu2x2hdFkXTwAiBt0yi7DSP4+cBgBbViDzeCI0xwOhZQ3gllBF+XPMLUnINvTmIUduJocooVflIPvvrpcNW1VOSJC+wAPB8fJ2nDcP4uSRJg4HHgSLgI+BiwzDSpqohSRLnTq0kx63y2NLdBCJRFm1pZOFmg031AfK9KoZhsKu1q+8DP7uUi/eHScnl/eV0x7pxq276Z/enK9KFpmuMLRmLJEnUBevI9+T3yZu+/dHDETyjR+MZPgy9K4hn0GDUkhKy5syle8VyWteswVVeTs4JJ/apn4oqc+LXxvCf339IoD2MovbkwUuA8nFKSUdzN3U72hk6sfebt+9PU/Uu3vnnA2QVFjFg9FiycvNQFJWswkIatm+jsLIS1eVGcqBmlgq8wwvpWtOI1hjqqQcI6D1PIffHfuW4ULJd+Edn1DyTobu7mlColry8Schy36QcHyn01hzpyssjYSWTz1kjYqBHtSER5YMcm1c8eeQMm4+hh4l17EXTalDcfmTVA5+ECuIYhk7/YedRu+1ZQsG9ZOcPx+MvQtfEa6gO8F9xM6DiWFTFh99XihYLk+UvwTDE65w+sS2rDCuciiq7aejaTiQWZG3DuxT6KnApzj/bQVmJU4DdOFd9jGgxFjfvImTE8KLgU1RUWaXQY9572S6hWAyvIRExdHRdpzncTXskQpdgbd/+uFWVKUU51HSH8BoGoY/jg4E+N6PynQX0AD5F4tzB2Ty5PcD+Oib1IY3WUAyfw9TALI/E3BHp35x1uSWGjHGxY0OUtkaD/GIDl1mTQpu4C2Vyx7tQs8HbX6ZtaYy6F8MUH+/CleXsu6m4FNzHFhBbHkDviEKODE0aWkBD7dKQsp2HTlK2GyPLjVKalVTQlwrS9sZP6gmJswzDCEiS5AIWAdcC1wHPGIbxuCRJ9wCrDMMw7cLq5I3f4q1NXPLgB8RsPGMHF/l5+4bjhK7jiNp1cO/s5M+7WbzAVJTXd77Ode9eZ3v8r+b8irOGOVNGEyG4fDm7Lr8CQoeqesUj75yz6feb36TZq/isfbeGdx/bbHv85X+c6/ihL8LLd9/O+gVv2hqruj1c/uf7yCns/Tq/rhX1tD5h/36qFVmUXzsljR4dGWzffgc7dt4FGHg8FUyZ/G/8/tS3QPm8vPFL1RxpNj+Gd9bAEy9b+mKr0Xs8+3dfByELleHBE/Gcc42QfYCWpXfTseZf8Q9KMpUXvYjqE3u7Euray4o3riQWiq+QmFUwkinz/ylkex/doWZeXnAp3aHGg45IzJv+OwZWHCtkty1Uz5+WfJmQlliM4qKxtzC54mQh++e89wv2xlpNx8zIHc6dk78jZP+mNW/wVuOOhMd9ksKrx1yKKliH990PF7O8LbHy5eicPO4/6mgh2zHd4Pg3PjAVt7lh9CC+MECsdvaDxm5++KG5+M25A/1cM7b359dkadwbY/HLBwbaM09yUTZQPHhqXhil9f3EIi7FJ6jkTxELpgzDIPxwA8aOcMIx6hcKcE0Tf1Gk72oj8uRqCGugSLjOGIUy3v53xekcmbZteaOHfU8k18f/awDHA/vyTv4BfDFdPgD86n8bbAV9ADuag7yzyVqtKeWIBH19xI0Lb0xq/C1LbiGqO99dS5aGP/zRdtAH0P7Ms2htbelzyIRkgj6At/+1MU2eJEaLxWwHfQCxSJi3H743jR4lpvWZrUmNj9V2EW23/135PBIK1bJj593sk1MLh2vZueuvfevUZ5xemSNtBH0AMdFWNlZBH8COVWK2AT0WpmNt/HYLABg6Te/8Qth+9fp/JAz6ALpaN9FW70wZc+P2x+MEfQAGy1b/Qdjuq1vvNQ36AJ5e/2th+1ZBH8DSji1CtrtiEdOgD6Db0Hh450oh+yEtZhr0AWzoFN84/9f2GktF09s27BS2f9ta63v/9O7UvJFON6veOzRAW/me+Jow2qHT+oG5cmfT2+LKnvq2kGnQBxD7n/XnY0b0rW09QR+AZhB9fSuG7jwDwC5pzceSJEmRJGkl0AC8DmwD2gzD2Pep1ABxK3AlSfqGJEkfSpL0YWNjvIemPeo6klvQbW/sEr7W54FY3H5KiYnoEcIx8x9ROojVJy/PH2t19mPuLTqbez9IiUWS/ww7m8X7DDkimvwDVOuDe/pZIhJp5OB+YeFwpgWGU0TnyFTNj/vQ2w9uinV4YESDYJESGesS/x5Guq3vXbBjp7B9gGAo8WZyLCa+3mgN1VqOiaavisYRHVF788nebrGetV0xZ5L+Vuzssg66nCzjAwJz2OFKJHRoiCywnPgELYB1HxEHt8/osNHGwmGnC6PjoBsQjEKs9/RW0hr4GYahGYYxCagEZgDWUkifnnufYRjTDMOYVlIirl509mRrueb9OX9apfC1hMntPTUfp0wuTa6+cGbZTLLdzvPdkyX3zDOTGi/n5eEZPDhN3phTUJ5cPcO00welxxETPP4s3P7k/Jx8anKfQapwD85N7gQJvEPy0+LLkUJOzjj8/mEH/K287At95M2Rg+gcaXt+zLX3m3WXHJ4pY4qvADXHXDk0b9JlwvZLqqzSIGXKBp8hbB9gcOUpCY9VlIqLis2u/JLlmCH5fasHkIgKXw7mupI9fLlqgpD9Io/XUsDCSZXZFUMHWo4Zki1eYzmnzPrcHNdno/9Y/yGHpur2HyIeenjKJVwF5v92l3jIgDLSZxkZSVXOSm2U8QfqX8gji5Hczmtm7dIrCgyGYbQBbwOzgHxJkvb9JiuBPem89o9PHcX1J43ArZh/UbLcCk9/axbZ3j5QIrxuefLnfD+59MBU8Y9T/8HQPHuB6qyKWdxxwh3pdSgBJd+9hrKf/AQp56A8bLcLybNfExtJwj18OENe+l/vOrgfF/3fUfhz7H3vpp0+iKGT+0bg5co7/07W/jV7SvwHlcvn59hLv86Yucf2jmMHUXLFeFyDbObfuyRKv3t4Lo4OJyRJZsrkf1JZeSnFxScydsztVFSc09duHTGka470XPUV60GnzhE1j/u6+1MyxoyKsx7GUz4FpIOeN5JM7oRLyRmWOLCyorTqZEbN+hWq+9AaQZe3mIkn3o+iOuuF1690FvOm/Y4sXzk94YaEInsYXHka86b9VtjuhPITOWfUjeS44wftA3LH8c2p4unYi+b+0XLM+8fcIWz/v3O/gvfgz/RjZOAXY45nWLb4hsSTc04kW4kf/rkkiRfniYu6Dcz28f0RiRVNy71uHpolFrQC/HRiEaf2T7xp45Ph+ROSe6nRV0yY7WLwaAVFBUWFQaMUJs0VD5wkWaL/BR5yxiqoueApk8geI/d8aSRwl8PAS6xbkSS0n6Xg/mYZFCXYOqhy4bnEmXCheuwQ1JOGIQ8rQplbheus0Y7sJUs6xV1KgKhhGG2SJPmA14BbgUuB/+xXuL7aMAzTp5MTcZcMGTJkyPDZ4XMk7pKSOTIzP2bIkCHD54fDtp0DUAH8Q5IkhZ5Y/EnDMF6UJGk98LgkSb8CVgB/T5cDhmFw9t3vsbLGuohXluD28ydy1uQ+SPUE+z389nHeP2Fs76tlhmIhbvvoNl7Y8gJdmnl9giqp/PGYP3JC1Qm95N2BND/6KA23/NJ6oNtN+c9+RsF556bfqTg8+ov3aa21V6hd1N/PhT/ru56DAG31dTz/x1/TuDtxcf6gSVP54g0/Q1HT+YiJjx7TqP/TR2gtNgoJJCj59kQ8A5JMD00DbW1tvPbaazQ0NDB8+HCOP/54XK6+64WYIe30yhwZvtXijZtLwnPdlWK2g+3wt+vNB33lZjzlYvOqYejsff4Kok0bPv2j7MZbMYWCaVfhKXbWgzMSambLst/QsvfQvrguXzGTT/wHHr+zli+rN97Pxu2PoWlhdOPT2rMJI77O+FFi930fy/e+zOPrbz7k727ZxzVHPUxZ1iBh2+vbdnL5qjtMx7w99/f4FLG3N43hLs5679GEx8dkF/PAjLOFbAPs6urksvffJRrn5caQrBzumzEXb4I3gnb488YdPLO7Pm45WbFb5eHZE8lziz2/Y7rBia8mFpBRgFfmV1pmsiUiFDV4ZU2UHY06/QtlxlfKvLgySkc3FGZLfGWmm9JcZwmB7S0a770UYf9yTrcHZpzopqjcWVpj04IIbUu1uLV+7jKJ/ud5UHwO27xEdCKvtKJ/eOA6V57ow/MlB7mkhwFHdAP3G59exRMf1iR1zvNXz2FCZX7S13LELZWgCxTX90E7h99+8Fse3Zj4YR2PNZeuSZM3idFDITZNSi6Fb8jrr+EZ4KwhbbIseHwTa95JLpNr1KxyTrh0TJo8MscwDP5+7ddpr6+zHDvl9C9y3CXOFjYiNNy/msi2JH4bElT+dl76HLLJPffcQ13dp/d15syZnHKKeBrbZ5XPyxu/VGHazsEq6PsY4XYOt9n7fXuuf0DIfuPC39C1+fm4x2RvAZUXPIusiqd1rX7r27Q3JlbtdHmLmHnWS8L2q2vfZsGyHyU8fu4pb+Bxi8nCd4ab+eXC0xIed8s+fnX8O0K2AWa++z1b40TTPee+db+lBsc3h0zl0kFirXaOe/PFuEHfPsbm5nPvDLHn/pt1Tdy82lw9usrv5ZG5k4Tsn/3mHloi5nenxC3x9AliGypPLI2wcvenCiUSB8ZQfjf89EwvsmCjcsMw+N8/Q2hxNHZkGU692Iuqitnu2sZN+N8AAQAASURBVBmj9ilzVVB3qcTAS8WfCwCRF1vQlsZXzVWPy8V1XL4j+044bNs5HA68tj55ta+3NzpXSEsakaCvj1hQsyDpc5bWLk2DJ+Z0vGm/9cA+Ov8nPsGLsnlp8t/R7Sv74Dv6MR2N9baCPoDNSxam2Zv4RHYlqQRnQKy1b1U9Ozo6Dgj6ADZv7ps63gyfP8LPJ/+87A2CO99OeEwPtRJpXC9sW4uFTIM+gGioGS0m/mzYUfOK6fF1W/4hbHtj82LT4xG9m85wHykr28CO8OIzNeKti8yCPoBNDto5vLTHeg7eFRT/3lgFfQCNEfGXNhtrD5SlPNhSMAINHeL2A+1G3KAPQNehtUFcdrNjtbWkZqTB+QstbVPiLCxtXbdj+33JER34DS7OSvqcEWW9r0D5WWJofvIKpGMKe//tlD/Jt30A3okT0+CJOQUVySllAuQWi6uFOSUrvxDVbU/soHjgoPQ6kwAlJ/nUI5FzUklWVhb+g1RTnagZZ8iQFDMm9bUHcVFzTTIwJAU1z1pdMRGy4sHjrzAdI8luZEVc3KUw31y0YWDFccK2+2WPsBgh43clWUJymDEiJ31qswU257F4jMy1XlvmKOLLazuJkE6KKMos0jgVCfL94qmSvizzc7PzxO+Nt8L6XCX5ZdUhyKWJ1wRSSe+XsKSSIzrw+9tXpuJKIgf6hJElnDy2PI0eJeD/RPrH9c3i/4bpN1CZbT+94NRBp5Lt6f1g2t2/H+4x9gNO/5w5ZM/q/dq5078zkaSyKSQ46/t9p0Kput2c+p3rkCTzR4fL4+Wkr1/dS14dSNGlY5PS6s46uj+S2rePQkVROOuss/D5en7XJSUlzJ8/v099ynAE8O0LbQ3zlAsusMcfaz2mXLxdUdlJfwQ5ziJL9lA48/uoDurvJElixFE/Q1ETL+JHzPg/JMF0N4DRQy6iIC9+HWJu1mCKC8cK2+6fO5Ih+VMTHj9r5PdR4t07m0zNtv7cfjz0fGH71w6dYXpcQeLX48SVN785NHFnFEWS+M0E8WzyK4ZWUuE13yz8+USrwDwxdx5lven3t1niG4NfmOyi4OPgLMcLU6rkT6ZMWeo57nXQLkJ1SYyZHj98HTFJtQwMzcifpuIqNDlfhrIznG/kuk4tgJw418mWcX3hUBXgzxJHdI3fPpZsa2JXUwCfW2FDXSeSAceOKqG6JYQiG7R0RTl7ygAKs/p2158/jIOuautxP20EV9/5ahgGewN7CWth3tj5Bg1dDXRGOplUNgkkGJg9kJquGk6uOpl8X36f+QkQbmig+a9/xTV4CEpeLoTDuPr3x+gOgaoCBr7x43EVOyvgd8qOVQ3sWNNIVp6HUDBCw84OsvJ9SBJ4vCqKW2HQ+GKqxvatn/uIRaM07NpGZ3MTbo+PnKJiIt0hajatZcCYCVQMHd7XLhJY10hgdQOKWyVrUinR2gChXR3osRhaW5Ss8SXkzumP4jl8du9isRiBQID8/Py+dqXPyNT4JYed+TF8x4MQjpMideocPBOcZ2SE//QdMA4SU5I8eK6727FtgOCepURad+MpGowrdwCyOwfZlZrNT12P0d1ZTWPNe7TsXUDpoDPw+fIp6Dcb2UHgtD+Brr3EtBBeTyE7ql+if/k8crNTU0/eFWljac3zVOaOpqZjI1nufCZXnIxLUHRlfzRN4/RF/0cbBwpcjHL15+HZNzi2rxsGv9+wgFAsSo7bzYb2JrIVN18ePJEZRc7vT1TX+e/HImTt0QjTC4uJAlMLix0F9PvYFQiyvaOLzZ0BFjW04pNkLhkxgNklhcL1cfvzt7VNvFvfTSDS89+lXphVnsXXRzsPPHTDoD1okOuTUGSJcMygscOgLE9K6oWJGVrMoL46hqSALEsUlsq43KnZZA23aERadRSXhJILWsBAkmS8FTKSnBr/DcNAb42h7QmDbKAWe5DL+jhOwPkcecQHfoFQlHP+uojNDT35uhLgViTC2qf/bhkYWOjl4a/NYFCJWKG1Y974IyyyoUC5jz4QdtnHUxuf4oG1D9AabsWv+in1l1LfVU9npBPN6FlclPnL+O3Rv2VqWeIdyXQTqamh/dn/EmtvI3f+fIxolLb//peuhYvQ29uRsrJQi4oo/vZV5J/V+wqp+2it6+Klv62mrbHbtPChsL+P0789idyivkv13LHqIz545kmCbW14c3ORJIm80lK0WIw9GzcQDXUzYNxE5n/9O/jz8vvMz1BNO00ProOgeT2Ae0guRZePQ1F7r3lqBnMygV9yWM2P4adfgW2JNxRFhV0+sf/EbVCzIf5ByY3nOvFecgCxYDNNi/9AqHYFxLrBMMDlJWf4GRRM+6YjcReAXeseombjv9FjB9bay2ou0057DI9PfLNN12Os3/oIbZ3bGDHoXPy+UnZUv0wo3Er/8rlUlMxwFIAEo+28tu3vfFj7Aroeo8BTQdQI4Xflc+7oH1OZ56w/2OkLf0qzHl+9e07OGG6b8g1H9n+x9i1ea9h2SI1Zgezm70edQ7nP2Xrsd+tW8r/a6gPsu4BZxeXcMmEqqiwehOzoCHDF+2s5WGZEAc6vKuPbIwcL2wZY2xzk2qXNHFwqJwM/HJvHqQOdKVEHQgbvb4uybo9OlgdmDFYIRCQGF8tU5KcmOOvq0Gmo0fH6DbasiRFog8phMhNmOeuNaRgG7atidKyJoYXA+Dgw9pZLlJzoxuUglXQfsY1dRN9ohxiga9BhQLaC68oS1Py+Df4ygZ8J7d1RJv7itaTO6RNVzw0vwxP2UnIOoA+Cv6vfvJp3a961Pf7ayddy5YTeV3bsWrKE3V//BsQSVBgfRO4Xv0j/34k30xWlYXcHT/0mue/2hf83g6J+vZ8++/Y/7mf5S8/ZGivJMpf+4W6KKntXJRUguLaRlkeSEAWQJSp/Mzd9DmVIikzglxymqp6PPg/V1gJSwqqed38PQvGV7w6wL6jqGenYw96nziWubjuAJ5+BFzyD7BIr6lnx2mUEWhMErR8z84uv4fIkXytnGAbPvXk2XcHa/f56oH7i8KpzmDHxxqRtA7SG6vjjexcQNRKLiFw8/lbGlx0rZN+Oqmelp4inZ/5MyP4XFj5CU9RcJOOZWRcKB3/nLHydhnDie+OVZN444XQh25vbA1zxwVrTMYOzvPxzziQh+wvrg9y03FyY57yqLK4eI/bmr6FD5+43w0Ti7ItKwDlTXUwb7Oxtd0ONxvuvRzDibGb7c+Ck88U3sGseDxGqThy79L/QjW+A+GZu+MVm9KWJ25W5rylHKem74C+j6mnC394xl9uNx43/WZ0GTywQCfr6AN3Qkwr6AP628m9ourUKU6ppvv9+20EfQMdzz6FHImn0KD6vP7gu6XMWPLYpDZ6YEw4GWfHKC7bHG7rOilfiy7Cnm5Znk/zd6wbBtX2nlJohQ9qwEfQBRPYkry4M2Ar6nND24d9IGPQBhNvo2vGWkO1YJGAZ9AGsX/RDIft1TcsOCvrg4H/Lll3P0h0SU958v+YZ06AP4LnNfxSybZcaQdVQwzAsgz6An60V+2y7YzHToA8gZOi812BPofpgfrTSeg7e0RUipImtfX6z0vq+PrXLvI+yGYu3xuIGfdDzDX1zg/21UyI2r4rFDfoAgp093wERou26adAH0PKeuP9GRDcN+gCiz7YI2z8cOKIDv2Ak+Q8/FO39IOWzgp7oV2xCzIih2xJuTi1JB3GG0aMz3MvoseQffjEbUs+pRtc1DD05X6Ph3g+kAdCSvz96qPfvaYYMhw199Vu1wNDCKRkTD92wN9fHYoll3c3QYnb8MtB1855kiYjZOE/TnS/g+5KQoP8xm2uVQKKeAxZEbM4xmmBwI7AsSM6+xVc/pjl3QLewoSe5ntiHnY9WZF316ck2fIh+ttcLR3Tgd/VxyQtM/PxMcZUtYVJQJN0bqLKadGuGC0ddiEt2pcmjxBR+9askI5fpnzkT2eusVkSEeRfGV3wzY/Z5w9LgiTm+7BxGzkouHXLS/MTNhdNJ/snJ11ZkTytLgycZMvQx2faeae4hginZUnqFkfInX2E+QHaTNVhM+dHtybNs5wAwZvbvhOz3K5uF22Veh1VZfgxZfjEl8Rn9zsRqCXfC4MuFbNslSxJLd5MkCZ8N4ZybxhwjZD/H5SZLMbcvAydXiDVA/78J1mvLQpeLLFXs9/Ht0dapxXNLxNcrM4aopsLXc4Y7/10PGZvYhssNimC7C3eBjKvIfG1XcJT4mlPyysijze+t+8yMqmfacSLusqWugy/c/R7dFhG6T4U/XziF+eOsJ4K08NuhEG6yP76PxF0Mw+AXS37B/7b/j7AWRpEUfIqPbq2bmPHp7plbdnPDtBu4YNQFKVHPEiG4fDktj/wbvaOD7JNOwugO0v78C4Q3bux5uydJSFlZ5H/xLMp+8hMkB4XeTti6vJ63/7GRSDzVvf1weSVO+cYEBo5JX28jM3RNY+WrL7LshWcJB7tQ3W4Ulwtfdg66ptFauxfD0MkrLecL1/2Ykipnxe1O6Fiyh47nt5tmiQFI2Srl105ByXFWbJ4hdWRq/JLDUtzl1vtNz5eu+Qpuv3jjq/BtX8fshyZa3/eJ/cYNNLx7C1r7Lj7djpdxl02i9PhbHLV00LUYG5b8hJY9Czl0q19mzLw/UdRvlrD9cKSDj9bcRkdXDcOqziQvZyibdzxFONJOZfkxDK06E8XBxmhjcDdPrruFXe1rAQNF8iBL4FZ8nDbsO0zv/wVh22Be5+dH5a1jxFNJDcPg/CVPsifUccgxCfjDhPnMLq4Sth/TdS5//122Bw9NR670+vnb9DkUeMSDp+d31/GHjTvjHhuXm8VdR41DcbD2eWRrG/dv6Yx77KRyLzdNdtbnta5d5431EXY0GnhUGFcpAzKDi2VG90uN2FlTrUZ9tY6qGmzfoBGNQF6hxLwz3cgO1lt6zKDp7SiBzRp6hE9+umoelJ7kwl/lLHA1dIPo221oHwRAN0Cj539VUC8sxjUiBY0CHZARd7GBpmlIkoSmaaiq+klusfZx/rWqqp8c63PefhtcLujuhmAQiot72g50d0NDA8yZA/3797WXPTK3H6dGGoaBJEmf3FdJkpAkydEPO1Xs75Ou65/4uc+3WCx2eHzufPp9BNB1HUVRiEQiuFwuDMNAUZQ+C6L3R9M0ZFn+5J7KsoxhGJ/c133fh75m3+9+3z3c99/Q871QVfWw+I5mOJBM4JccdubHaDSKvn49dHWBokBeHmRn46kUe+NxMOFgEHbvhuzsfReE0lI8WdaNru2w7/my/3Mllc+Yfc+GfdfQNA2XK7WZKvv7v++5mUq7+2zum5dTZb+xsZGWlhZcLheqqtLd3U1VVRXeFGXI6LpO7ON6/H0+p3JO3vfZRqNRPB4P0Wg0pZ/tvnl73/pC0zQ8ntRsJEajUTRNwzCMT+YwWZZT/t1MF7quf3Jf9v2+FCW1Ctrx1iOpYp89TdPQdR1VVdO2tklm3eR0jjw8VrxpQtM0Jv/ydTpC9nL5ZQk23XIyLlcf3JabbaqGrf/4/w6YB1e8mDZ3EhGIBJj/9Hw6o/F3ovanf1Z/Xjz7RVSLlIt0YOg61V//Bl3vvWdrvG/qVAb9+5E0exWf5a/uZMmz222NLa7M5rwfT0MWTJNwwpq3XuP1++/CsFELOWTKdE6+6nv4c5NXw3NK4KN62p7abG+wDCXfmoRnYB+1ccmQIY1Eo1H0Pz2c8HgYIMuH5+qvCtkPb1kNz99pbv+Uy/GMnS1k3zAMGl6/ge7qRYcck33F9D/7nyg+8bSrvVueZtvyPyQ8XjroDEYeJaZauY9AcC+vv3cVwe46JGQkWUXXIyiyh5mTb2JQ//lCdg3D4DeLvkB7uCHucbfs58dznyXLnS9k/2crH+b19pXxD36siXLPuKuZVCRWelDb3cF5S55IWFI1KqeYB6efLWQbYFN7K19ftiih/dMqKvnJ2MnC9i9etJKdwcQCMlcPG8AFQ8Q26WuDES5811xw6b6ZJYwsEA++390Y5Z1NMaJaz9pXlmD2MJX545wHlY21MZa8Ek1YjzdsvMLYGc5UMVuWRGlZdGiNpuyD/hd48JSIr5FCf9mL0Xio7RhAhYr36xVIaop6HW5tJvbKZoyOMPLoElynj0Jyp7e91BG93X3xg8tsB33Q80Z37u/fSZ9Difjd0OTPqV6Yej9scPVbV9sK+gD2dO3hliW3pNmj+DQ/+JDtoA+g+6OP6FzQ+/dU03TbQR9AU02A5a/tSqNH8elsaeK1e++0FfQBbF++jAWPPJRmrw7F0A37QR+ADs0Pm8tyZ8jwWcUs6PuELmt1xYSYBH2f8MqDwuY7N/43btAHoHc30fDmj4Vtx6IBti03T1Vs2Pki4aCg4unHvLv0RoLdPZGSgY6u9wjpaHqYJct/Iaxu+K/VP0oY9AFE9CD3Lv+OkG0gcdC3H99ae5ew/W989IKpjsbGziZeqU3iWX4Q1yxfYmr/pdoamkLmyp+JeGDLbtOgD+CurdXogp/txQusv3Pfel9ciXp7o8Yra2OEoj1aaFENwjF4e2OMdXucCxwufT1x0AewdY1Gd5e4QEqsy4gb9AHo3VD7jLhYVeSN1rhB3yfUxoguPDQ9WQQjHCP6zDqMthDoBvq6BmKLdqbEthlHdOC3dk/ydXCNnWIKYY4IJVHb18dsbEmiPxrwYYN4iq4TuhbFXyyY0fFi779BbdmbvCTzrrW9LyVcvy351ii1W5L7rqSCWHPyCnx68LOtfJchg1Psbuj0Nt17lpgej7RsEbYdbN+OZREw0N64UvgaAO2diTf2dCNGILhXyG5PXZ85TcFqIdu9QUvE+ln9Rr39TdGDCdpopbCwUaydw/tNbbbGtUTEFFujNuJFJ7/Y3c2Jz65ucf4siNn4Zzc6CDDD9eY+xgLiJWz6JuvNAH2H2IbBwRiNXRzcV8PYk5qg0owjOvCbNDA/6XMq8npf2ZHsfr1/TUHGFY1LavysCvHCeCdkH3dc0ufknSOeViJKcf/kG7EPmSguZiBKxfCRYKoDdij9RyWnAJsK1CJ/sm4iZ3026iUyZEgXfSVsZYV/4DzT4+5i8WdMVt4w7Dws8kqnCF8DoCA3sQKkLLvIyRJLBxxSYO1XadYgIdu9QYnHuv7ztIoRwvatVD0Bji0VE/ObV1pga1yRW2xucduYw5wkAw4qTvx7rypy/ixw2cjiLHPQYN1bbu6jmiOehimPsW4srwxPTZwglWaB58DvqTQg/eUxh+fTPkX842szKEpiUafKsOhHx6fRowT8wLqJ7CGMPCf1ftjgzuPvpNBrr6ZicO5gbpp5U5o9ik/hJReTfeIJsG9BY1E06583j+yZM3vBswORZImjL7Q/uZUPyWXSiQPT6FF8svILOO2aHyDbKMyWXS5GzJzL0V9Nr5R4PCRZouCiUfZPUKH4iuQ2MzJk+Kyg/sDGb7DAvOWAKRf+yHrMWd8VNp8z4kz8Q+LXwCnZFZQe/2th24rLz4gZP8NsGVQx/AI8PmfqicfM+D05WT3PbElSUZSeRaOq+Jk7Vdz/L4+7hSJfYnEen5LDN6f8Vdj++aXmQTfAPyb/QNj+/dPOQjEJvCfllXN82RBh+/dMn4NqMu9/qX8VBYIiLJcOHcDIHHNlxx+NGiwsBPLkMdYtPh6aWypkG2BQscKZk1zkeHviDq8Lsjwwf6yaEkXPo+a7kU3MjJys4PGJhx+KX6LouPiBvZIN/c4Trx90H5eP1M8kbhjoQp3t4Jm5H5JbxXXuWKSSLHArKJMqUOeKK9navu7nQdUzQ4YMGTJ8NsioeiZHZn7MkCFDhs8PGVVPC7Y1Bnjsg928s6meHU1BNANcMhgGxPaLeSvzffzvu3PJ8ztTGhLmV4Mg1mp/fB/18YtqUf6w7A88t+05umM9ogDGfnUSEhIGBjIyR1ceze3H3Y5qo1FrOghXV1P/698QWr0aVAXvxElEt28nsnMnaFrP20Cvl5z58ym/8YeoBfbSN1KNFtN58e5V1Gz49PNXXDKgox2UKz9kcjGnfnNC7zp4EDtXr2DBvx8k0NyMYYDb78PQNLoDATz+LKrGT2TSyadTMSz55vSpwNB0Gv+5jsimNuvBikTpjdNx52b6+GU4MrHq4ydf81Vcfuv0poT2b7vS9LjTPn4AXTveoW3Vg8Q6ajB0DdlXSOG0b5M99CRHdmORLtYuuJbOlvVg7F9ro1A84HhGzrwZuY/mLzsEIi28ueMhtrUuB0PCQCcQaSbbXcgZI77HyKKjHNk36+MnA4uPuUPYdkzX+drSZ9gWPHTdowJ3Tz2T8Xlize0BVrc0890VS4gd9HJjZmEJPxo7iWIHPfwAnttdyx83Hiq0JgGn9ivmx+PE1E738fcNLfxz56EaABJwwaAsrhp9eDcR370lxvZ1MWIxg2BHz5rb5YaqkSpDx6t4feLpmFrIoGNVjOBujXC9gR4CDJA8UDRPJX+ys/INLRQj+q8mjKZoT96tAZJPRpmbi2ti8uU5Ca+zvQV9cxNSkR9lUgWSK71qnvs4ot/47Wjq4vQ7FxKM2CsiVWWJrb85LenrOOaN38Ki3yV/Xh8Ef1/+35dZ07TG9vjh+cN55qxn0uhRfKL1DWybPx8jbE+sR+1XwbBXX0Xqg/44j/zfYtob7BcLj5hZxkmXjU2jR4mpXr+GJ39hraQnyTLn/vRXDBzX+0Fq7W0fojUmp1RY+TvrtKYMvUPmjV9ymM2P4XsfhzZrFWbPjV8XurZV0NeDjOf6+4TsA7SvfZzWD+6Ie6xozo/IGfVFYduLnzkRzUSlOrtwDJNP6n11YjtEtRC/X3w+7eHECpCXT7qDUcVidfZmQd8+PCi8e8xtQvZPfvdhOg/e2TyIJ2deQKU/+bS6tkiYMxa8lvB4lqLyn3knkq2KzfeLG1q4caW54uiMolxumypWg/p+fYAbl5u/CDi3Kotrxhyewd/2dVHWvJ9YNM2XJXH8uR5UgZYIhmFQ888w4YbEsUvRcQoF08Rf4nT/uhrC8e2rx+XhOs55HZ62po7oc5+WecnDi3BfYG+95HSOPKJr/J5ZXmM76AOI6QZr9rSlz6FEiAR9fUB7uD2poA9gS9uWT94M9iYdL71kO+gDiO2tpeuDpWn0KD6hQDSpoA9g8/vO5MWd8P7Tj9saZ+g6q998Jc3eHIoeiiUd9AGEdrSl3pkMGfoaG0EfQLQhnUrBzlQCOzc8nfBY2+p/Cdvtat9uGvQBBFrWE4vYu4e9zabmD0yDPoC3d/4jrT6EEVNm7IyGLYM+gPu2LROy/+fN5oqnXVqMhQ1iip4Ad2zcYTlmabO4OuPPV1pnfz23O3lF8N5i21rz70V3l0FDtdhzIbRXNw36ANo+EFcM1RqjCYM+gNgHqVHdjH2054D/1rc0Y7SnRi3UiiM68PMJNEHM8WQU/hLhksXujSr1fqqM7DcvvE7VOU6RBXa8pD781bp89tNj3N4+UMiVxdJHZN/hm86VIUPa8R6+857sSvxcNjtmhaLaez5JgvNeunEr1v571N6f0+zgMlP+2I9ct1gKfp5i/bbHr4o/8702RM6ctPf2KtZnq4JzXW9gQ1AVwZetyC7rf7eTJadkJanqTs0C7JAm7ZLUozDZCxzRgd8F0wYwoNB+7UKh38WgYmuJ4ZRz+du9f00B/C4/Zw45M6lz5lfNx6X0/sSZe/rpqKX2Va98M2bgnzI5jR7Fx+1VqRpflNQ5c893VjvghGMuvsKW9LsnK5upp/d+ewzZreAdm2T6iwTu8tTl7WfIcNgw0Z7CrSs3R8y+z0YaXq4zVcz8yVeSaBldOP1qYbverH74c81VI0sHnW47QOxthhVOZ1DexITHZUnh1KFXpdWHwd4yofO8isqILOvn9NeHiGWzXT3SvBRigM/P7GIx3wF+OTFxi459XFgl1ioC4K8zrX377uh8YfvpZtxR5mu+onKJkv5i4YenVCZ7pHngXXKS+JpTzlOhKHHk6DohX9j2/qhzBx0Q6CkzKpGyekdj5Iiu8QPojmi8ubGe1TVtvLS6lo5QlKoiH6qksKm+Ex3wKRJnTq7klrP6UNZ954fw8Ak2B0twc1s6vTHl3ep3eXjtw+zo2EGWmkVjdyNhLYxP8ZHtySYcC+NX/Vw39TpOHnJyn/mph8O0PfkknQsWIns95Jx8MqE1a+h86y20QBey14OrooKiSy4hZ/78Pu1ltfGDWhY8sZlot4bbJ1NcmY0Wg46mbro7elJiZBXO/O5kKkf0jQjNProDHSx5+jHa6mrRdZ2c4mIMHZp2bSe/vB+DJkxm6PSZ+LIFF5MpILCijrYXt0NQO7BHs4uezDOj5/+6qnIou2pSn/iYIT6ZGr/ksJofw8tWwluJU+ZE6/s+sf/8PbAlwfVHz8Jz2hWO7ANEO/fSueE/hBrWY8S6cRUMoXDqN1GzxRfv+6je+G/2bn2aaDiAEetCkhTcWWUMmXQtxf0P79pf3dBY37iQzc1LcSkeFBT2BrZQ5KvkpCFXku1xNlec8e7PaCJ+qut5pXO5fvS5juz/e8cq/r7rI6K6jrbfg3pibhm3Tz4Nr51XRwkIx2J8+8NFbAp86n+eovCN4WM4vd9AVIfzfXMowsXvraRT60lZ3Get0KXy0/HDmFac78h+UzDMlxc0HJB1KANlHolbppQwIv/wFiTr6tDZuiaGy21Qt1snFITCCqga7qJ8gILk4I2lYRh079YJN+h074kRbujRZnIXQsl8N54C5yIpkYXt6Ju6kfq5oS2GlK+izshBLk7diwyjM4y2vQW5yI9cab9uMKPqaYHPrRCLabQGI4wtzyLX52HakCI21XZw6rgyVEVmY10Hp4wV74mSEgYl8Rleuz59ftjgmAHHEIlFeHTDoxxdeTRel5cCTwE7Onawt3MvcyvnEoqFmD84fv+l3kL2eCi46CKUomKMSJjs2bNxV1SQd9YXUQoLMILdqKWlKNl98Jb3IHIKvYyd2w+3RyG3yIfLp9BaFyS7wENrfRdttUH6Dcvv86Cvrb6WjsYGjr/sm7Q3NrB77UqGz5hN7dbN5Jf3w5+TTdWEyX0a9AH4RhcTqgsQWtMCsoYr14tamYPeHkHN96KFYyguhdxjB/SpnxkypBvP9EmEEwV+px3r2L7rjG8QvT1+4Cef+GXH9gH0SADZX0r2yOGo/mK0rnpkd2re0pcPPp1QZw2hUBNZuUOQkAmHGlHdqenVlU5kSWFc6bGMKTmapuBufGoOLd21ZLnzHQd9AA9Nv54zl90c99j3RjjP6Di/ahwlviwagp28Ur8VCYNSTzaXDpniKOgD8KgqPxs7mXu2bKAjEiVsxOjvzwLDQBbsr7c/RV43Px8/jHs270I3dBq6oxR5Vc4Y0I/xBc7nv2K/h++OyWdBbRcNoRhu2cCrqEwq9jA8z/mbIU03aA4YRGIGzQGdPL+EKkuU5cm4bKSaWpGVKzN8goquQ3mVTmuDjtcvUVAiOwr6ACRJwpUvEWkDb5WMb5CM4ukpnXHnp2gDP0/G8IGhaSijfMjZSspzJKUcD+rEnjfDRlcEI6oh54srLNu+7pH8xm97Y4AT//Quus1/ot+tsOynJ5Ll6eV4OByE3yabFuCCm5vS4o4ZTd1NnPDkCeg2CvYlJO6ffz9HVTiTlBale80adl5wIegmvvp8VNx0E/lfOqf3HNuPWETj4R+/R7grsQLWwVz08xkUVvR+auLTv/4Zu1avAHpUOw2T+zpy9jzOuPbG3nLtADre3E3H64fKbCfCd1Q5RWdbp+5k6B0yb/ySw1TVs60D7n3C0oawqudjv4W928wH9RuJ56IbhOzr0SB7n72YWOeeuMfzZ3yX/PHiweWWD39P3bb/JDzu8hRy1FkvCTfi7g0aunbx0MrraO6uOeDvA3LH8PUpf8Gris0Vpy74Ca1G0HTMeWXzuH7Ul4TsL22u4furXibR8ixHdvHfuV/BJ1gMdtF7b1HdnVgA5c4pM5lSKJaGrBkGJ73+AWbyNNeNGsTZA8XaUTR2RznvnbqE9wbgj1OLmF4qVsO5u1nnX4vDBOLo37kV+OpsN8PLxN+axaIGS9+M0Lgn/hph0EiFiXPFg9faZ8N0bU2w/lBg4Nc8uAvEojS9K0b41r0Jj8vDvXguTu2Louhb29DerwbdQB5cgOu88YfWAO5HRtXThG//+yPbQR9AMKJx8/Pr0udQIpIO+gDTR076uGXxLbaCPujp73f9u9en2aPE1Fz7PfOgD6C7m7pf/QotEOgVnw7mvWe2JhX0Abx416o0eZOYXWtWfhL0AaZBH8CmxQtp2GGxIEwDhmYkFfQBdH9Qhx5O7jPIkOEzgY2gDyDaJai8bBX0AezdJGYb6Fj3RMKgD6Bt2d3CtrVYt2nQBxANt9Cw8yXha/QGL235yyFBH0B1x3re2/2ksF2roA/gqfqFwvZvWvemaWDTqUe5a+sHQrZ3BjpNgz6Am1Z/JGQb4JFtNZYrsD9v3Cls/8YPm0zvDcBNK5uF7T+/MhI36AOIaPDMhxGcvBTauTGWMOgD2LlJo61JTNUz3KAnDvoANKh7PiJkGyDymPkLFX1LCG136tQ39dpOtMW72Res6Dta0ZYnfualgiM68Nvblvxktm5v3zRG/6ywtW1rUuO7In0nORxrbLQ1zujuJlYnLu3shMbdyUuFB9vFH2qi1G1JfvHWVLM7DZ6Yo4fEArhYq/3WHxkyHHHU9l2LGDMiLRbzjaFh6GK/+Ui3vYyZtnoxfYHeoilYnfBYY7D3n8F26YpZz2M7uqzbGsRjTZt1e5JATHzz/MMW63WieEMBqAtZnx12cIGmTot2CN2gOejCEmi3DhoD7eLtHKyI2bh+Ioxm6+eJXp26NZjRfOgGS7y/pZIjOvCbPyb51+yXzRmUekes8IqlA/QFXxqRXFrH8IK+S6Hzz7LXuNY9eDDuoUPT7E18Jh6ffI3ZwGRVK1PA2ONOIimBakli8OTez9ZTslzgSfKxJoOr7PCUPc+QoTdwDRvU1y7EJXvYKabHZU8ekixWmuHNrgTJOp2tcsylQvZ7izElRyc8NtbkWF8zIrvYcswZ/eyp0h7MSeX9LceMzBFvwv2t4VWWYwrd4iIgx5dbz0cD/OKpmGP6mZ87vFRCdVDnV1Flbl+SocTCh0Rkj5YtlyJZI8RDG2WyheaDZGNMEsiDC8B14L2QRzpTQra8Zlqt9zF/PH8S0wbZ/3GfP62S86cNTKNHCfiRQCrMRU+l3g8bXD7uco7uZz2ZSEgMyxvGY6c/1gtexWfAn+/AO3FiT38UAK8XyeNB8vlQiotxDRxI7umnM+C+e/ushmP4tDLGH9ffdkxVUOHj1G9NSK9TccguKOT0a28gK78Al9dLv5FjcPt8IEnIB/VD8vizOOfHv+gzgZey703pUe+0gypR8p1Jh3UNT4YMotiq3RsuPuep1/7NetAVvxG27x84j/xp34ZDeulJKFnlVJz1kLBtSZKYPP+fSFLih0XlmMvJyh0kfI3e4OSh3+SEwZdTnj2UXHcxHsVPnqeUc0bdyPiy44Xt3j/+WssxC+b+Xtj+XVNOZ3h24lZGFw4Yx2kVYhvHXlXlRyMTz5MDfH7unjZHyDbA2IIcTq1I7HuhW+Xh2eOF7f9gfCGjchNvaOSr8NA88RcGZ01xMWeYQq7306WHBHgUmFgpc8FRzhRDywYoTD7aRV6RhOsgU74smHOqG49PbM5VPDLlZ7uQErjoGyxRepJ4/aB7fgEMSXB+loTrgmJkB0H3wUhZbtxfmYg8rBCpMhfXF0ajDEuuxVfS1zySxV0yZMiQIcNni4y4S3Jk5scMGTJk+PyQaedgwQ+fXsV/PqpBs4hvczwqL107jwGFfZTydXOSaQffXgqlI9Pjiwm1gVrO+u9ZdGv26ifvO/E+ZvW3l3KZDhruvJPmBx+C0H7FuJIEsgyyjCTLqKWllP34R+QcL7476pTd65t5/7ntNFV3YiRIYffnujn2yyMZPCm9aQB2efb3t7BjxYcYuo7q8TBm3nEoLhfN1bsYPGkaU04/C1lO3c6YXQzDoOnRDYTX2Ch+V6Dshum48g/PJs0ZMjglfOv95gNmjMdz3Ewh29FoBP3Ob5uOka+5C5db7PelR4PUvvQdok0bObAhp4TkyiJ/8hXkjb9IyDZAONjIyjcuJ9LdSM87DwnQkSQFf97Q/2fvvMPjqo4+/M4W9S73bmNwB4PppvdOSCihJRAIIfDRkxASQkkngSSENEoooYfQe+8YYzDuBdy7LduSJattm++Pc2WvZEm72r1bJJ/3efRIe/fuuaPdu/eeOTPzG0Yf+GsKit3JAgqFmpjz9YNsrJ5N74rdGbfrd/F5s/e6UxvcyjGf3NjpPp8e+peEx1+2tZoLpj1DwLnheZFtvfzyPD7+MvF4di9LPKr1SdU6rp85rV2RFB9w+577sXdl4uqMV3w2hxk17YvCjS4q4G/7jSfXm3hS3clvraS2gzLE/Xrl8od9kleWnL48xLvzg2x2pBiGVAgXHpxLji+5DJhgQPlqRojNG8KoQlOD0twIqlBUIkw6zE9pZeJzg0hA2fRRkK0LwoQb2H5pEMgdAP1PzsNXnPj/EHhpM+HZ9abnb0jNb2c4qfSR84O+eDpR3YyH0JdriMzbgJTm4RlZQXjuBggr3r0H4h2R2nKeHh3x++nTs3hiWseFz23xe4Wvf3NCl4+TNHdNhk1zuv66W9IvRLPnw3sS6mIx/azvzMpIKt3mRx5l/a9/Hd/OIox45WVyhw9PrVHtsGF5LU/9/nNiyng5nHbdngzYNbP9/F6563bmf/Rep/sccPrZHHjGuekxKIqaN5ay9Z0dVe46xAODfpvdjZp3JmzEr2t02s7hjvshFFsFIuF2DndcHNd+udfdl9D4q54+m1DN0k736XXYLynaJbGesR8/fTiRUMdCCl5/IQd8403EhQWsj6ffzLJVr217PGLwiRyw501Jj5sq9n//6pj75OHjvUNvT2j8g965N6Y++FuHXEBBAu0caoMBTnj/9Zj7fXDkSQn19Lv7qxU8sqxjyX+AvStK+PPeY7s8NsCFH6xmSX3n785Jgwr58YTEHYQZK0I8+dmOnuWAMrjiqOR6yX32VjNrl3dsv9cLx5+XhzdBB3PdiwG2Luj4uuYtgWGX5CU07wy8Vk34kxiie6Ve8q+LXUfaEaEv1xB6uYMSLxFyLpqEp1/HpTK2nUMnvDmva0plwbCycnNq1XTaJRGnLwNsbNzYZacP4N0V76bAmtjU/K8LdZCqbHnuuZTZ0hmLp1fF7fQBLPoiPrXSVLLo89gy2wunfJQGS3Zk65S1XXtBBEI17skzWyxZQxxOH0BwzlcpNqTraCQU0+kDqFvwbELjN9Qu79TpAwgH69lavSCh8duyYs3brR4vX/OWK+NmkiYSU1Rd0bAlrqZQUzd1YQEvirfXxSeH/0ac+7Xl2ZWxVcA/31yb0NhATKcP4O21ySmmz1rZ/rVhTQ1JtXIIh5W1Kzq3PxyGTesSU/VUVbYu7Py6Fq6FwKbE/ofwnDh8gC3JaLZCZN6Gjp9UJbwgtXO8Hu34VRZ2vcCzPIHX7CwU5yQm1rFbxW4uWxIf/v4DurR/TgaifQDFlV1L9ymuyHx6UF5R7KbAJb3dbXIaL77yrhemewoSV2CzWLo9AzLzXe0M8fjaEXXZEV9J15WRAXLy4ouW5BS4894U5vdr8ziR/r09g0p/fBGlgfmJzTmGFsb3ulHFJQmNX5kb+7wsTEIVM56JeWmSqYZlhe3b5/eSVIaWxwN5cXy8+UWJHUNE8MXx8fo6+P9ijl8Ux/uapOckpZ3P4WI9nyw92vH7wxm705Xv3vHj+1GUm4Gyx2uXpP+YCZDrzeWowUd16TW983szqHhQiizqnH633Az58d1gckePpvTEE1NsUfuM3r8fA3aLr8azYmAh4w7pmkObCk655mfb1VIdPF4vHq/5/hSWlXPw2ZmRQa88p2vpNTljK5PO17dYspJTD49rN39FWWLj94kta09Z4o5Txf7XdPq85JZQsfelCY3tyymm38jTO92n74hTyc13p6Z67wk/wuczGgJ+XyF7j7/WlXFTRT9v7HvSdcO61t6phUJ/DpPKOnd8Rxf3YreS2C0f2mOvil70bisn2YYRhUUML0rM8btz0piY+/x8fOKtrH6zV2xVx9/tldh708Jho/xUtrN+e8rE5ObAIsLuB+Tg7WSYgSM8FJcl7n70Piqn004sFQf78CaoGppzWgXEmA74jky8FQiA76BhSLkzNxWQ3tvbQ3iGl+Od0Dep8WPRo2v8AIKhCM98uYr3F25g1qoaNKL0K88n3+elPhBmZK8iagNBfnrcGIb3jh3FSCnxCryccjfs9e3U2tIJy7cs57dTfwsKlfmV1DTXEAgHOHTQoczcOJOZ62cSkQi3HHALBw/OfO1U7auvUj97NpHNm8mdMAHdsgXfgIF4cnLQYICcIUMo2HPPTJvJptVb2bSmnrWLqmmuD1K3pRm/z0M4rPQZUszIffrRd2hiN6pUEAmHmfbC02g4TEnffoyefChNW+uoWbeWviN2wZtAbYZbaFjZ8s5yAivqkBIfkeYwnhwfoY2NhOsCIODJ99Pr26PJ6W17+GUTtsava8Rzf+xQ4GXsCHJPPjKp4zdv3gAP/Kz9J79zC7m9k1v4CzdtoXbeU4Sb69BQI5Jbjs+Xg7/XKAoGT066frypfj0r5t1Ped99CYcaaW6sIie3nNK+kygoTiya2BHBUD01tUsoK9kFvy/7rzsLalZwwcw/tfvcewfdRp43Odn/RXWb+OvXnzIov5ij+45k9pZ1fL11M2cNGs/48uT7G0/duIF7vp5PTbAZD8KA/HyaVfnByDHsWZGc4wTw65lf82HVJnI9Xgp9HprDygG9yrh8zHAKfMktJjaHw1zxyTqW1kco80NTBAble5nUu4ALdyvF64JuQkSVNdXK2pow9QHYb4SX/Bx34kHBgFJXHSG/WKivUQLBCI1boc9Ab1JOXwuRZqVxTYRwY4RQfYTwVvAWCiXj/AlH+7aNHY4Qmd0IpR50SxhtjuDp5SeypAnvAcV4i5IPEGlE0XV1SHEuUpxLZFMDhCN4+sT2Q6yqZww8Ap98XcXrc9fT4uOuqwtQkucjEonw5cotlOR6mLJkIwPLC8jxZSgIurULQi3v/i6jjl9TuIk8bx7zNs9j3qZ5lOeXs3uv3bln1j1sDW2lNKeUPvl98MbRHDeVhGpqqLrzr4CSM2IEdbPnENq0mZxdRlD7xhsUHnAg/a7/SUZtBAiHI3z+8lKWzdlEY10zFf0LGbVvfwrLcgk0h1g1v5rC8jyKyzOf4rlxxTKq169lyLjdyS0oZNCY8ayYM5OlM76gfksNfYeNIBIOI5LZZIKmRdU0zt5IuD4IyyOgESj0m1rK+hD4PaBC04LN1vFLkpotXxAK1lJRcSAeT3ITQYv7NK/ppNZ9WWI1VK1YPq/j5155CL7786SG9/gL8Bb0on7J24S2rkNyiikYdigl/dzpv9m4dRWNtSuor1lOc8Mqgs21+PMqGOHLdd3x8/sK6V2ReH+3dPOPRS92+Nwn6+dxxIDkFkzDqpTn5NM/v4TK3ALKcgvYN6eAyjx3GmTneTxsbG6kOhQk3+NFG5W6UIhZ1ZuSdvxCkQjVwSCBCDRHwlQ79bQvr93IXpUlHJlk+nQwomxsjhBQ2GDWKlm8NUyv/CDNYaUgSeXNxoCypCpCZRFUFnnwNSpfr48wtJdQmmC0LJpQEGqqwsz+NEw4bB7n5EJlX8GNZMPGlWE2fRxEAU8eBDeA5EH+AA++wuRcG4/XQ6RACL6wGQIRKPKgfXLJObECyUvedlUlsrwGVJF+xWgghG5qQIrTc//s0RG/xkCYMTe9FntHh4oCP29ddxgV6a7zW/EZ3H9011+XAVXPv3/5d/41619x73/UkKP48+F/TqFF7dPw5QyWn3MOxDi/JS+P0TO+TJNVO9JUH+DB6z8hHIpd6Cwe4aTLd2fIuNQ29+yIj574D1Of/S8AuYWF9B46nFXz2hcm6j1kGGfd+gdyC9LvVFX9Zy7N8zbHvb+nNIcBN+yXQot6JqrKrNmXsnGjEanIzxvCpL2fIjcnuQmVjfh1jU5VPd+bClNnxRwjYVXP+2+C6s7VDSFxVc9wYzWrn/42keb27nVC/1MfJLdX4m2NFkz5BVUr3ujw+YLSXZl03CMJj9+diUfVc1LxCP6+15UJjX/34s94aPnMdp8T4GdjDuXE/onrA/x2zpe8sq7jhY1yfw4vHnpsQmPXh0Ic907nc9LdSwv5+36JOflL6pq58KNOBECAhw7ux7CixLJqVmyKcP+HzTS3o80jwNn75zBhUOIL92uWhpn2TqDD50eM8zJh/8Tn2aufaKZxZcdzpqLRQr+TE1so14jS/O/16Mr27c+9tB+eAYnbrqEwgYdnoKuN+I/0LkTrA9BgFFa9ew3Af0Ln1zSr6tkJv3xxbpf239wQ5PHPVqTImk5IxOnLAOFImH/P+XeXXvPWircIR5JTQEqEtTffHNPpA9CmJjY/9ngaLGqfqc8vicvpA3NB+uTZxSm2qH3qa6r57Pn/bXvcXF/fodMHULViGfM+eLvD51NFJBDuktMHENkSoGlZ+hdRujs1NZ9tc/oAGptWsHrVzjlJzlricPoAwnUJKgTG4fQlQ+28pzpw+gCUzZ8mvqgYCm7t1OkDaNjyNY118beE2tn4oi4xfYJQJMIjKzo+NxX4x6LPElaXbAiFOnX6AKqDARbVJaa8+ZvZi2LuM2tL4qqbP5kWW9Xx7128z0Xz9vxgu04fmPf+tdkdNBCMk7nTOn/9krlhAk2JfbbB6kinTh/A1gVKsCYx1dDIkqYOnT6AwAtx9AfubPx5VducPgCtqt/m9AGEp68hkuLuAj3a8Vu7Jb4m49Fsru/4A9/ZCWuYYKTrF4Swpt/xi9TGf0EPrHIh3SlB6rd07Xxr2prcBTlRmhsa0EjXLqSNdTF64aQADSZ2sQ/XNLtsSc8nGKzZYVsgWJ1+QyxJE9magTZGcRBu6vx8CjfVJDx2JBRfC5dAU3ITPcuOhDRCOIZTVxdqjrlPRzSG42szsSWY2Hyvqim188Stodj/9+bmxO51AA3NnY/fEEguEzAQY3yAYDDBdgtxdl6Kd7+2aEPn76vG0Wqj09c3xjGHa0jtPK9HO34/P7HrzTNP2zPxpowJM7xrSpmZIsebw1599urSa3rl9yLHm/4WGRXnnx/3vr0v+2EKLemcScfHoYoXxbiDM6PoWTFgIANGtf4+5RR0XIfhy8ll9ORDU23WDngL/XgKu5j+IlCwuzvKfTsTlZUHk5u7XYBBxEf/fqdl0CLLDuTFVzPi75+d53/xqFM7fb50wjkJj52T34uc/M7rsMSTQ2nviQkfo6fjI7FasDyvj7HFnaeEH99vV3yexKaolbl59M2LIZkP7FGWWAP068aOiLlPnifxOrkfjIot9PedXRNXltx7eOc1cJOGJafPMHTXzl9fXC4UFif22eb2E2KWkhdCbt/E3n/vbvmdqp/4DklOYM87pjfkRr0/bXRFpHchMjC1In49usYP4KWZq7ny8Rkxm4X2KvRz9/l7M2lYYheCpIlX0bOFG9ZDbvrFPoLhIDd/cjOvLH0lZiRvVPkoHj/xcfzezKg7brz3Xjb9+340HEJyconU1JgnPB4IhZDCQgb94+8U7btvRuxrYcnMKt57ZAGNdc4qj0B5v3x6DymhtqqJmvUN5Bb62OPIIYw/ZIArggaJ0NxQz/RXXqBm3RpG7ncgfYeP5NOnn2DJl9MINDSQX1JCn+G7UFhaxu5HHU+fYbFvjqkgEgiz7u9fElkfO+IvhT56X7o7Ob3dERPY2WhqWsPKlQ8SCtXRf8DplJVOSnpMW+PXNWLdHztU9Gzhe6eR2zvxuszmOy7u9Pmca+9N6prVtHY6VR/+lnBdVGaGN4/yfa+kdOw3Ex4XIBxsYPb7V1G3aQ60mSXkFPRj4pH3kVuQnU5xqgmHw0z+6LpO9/n00L8kPH4gEubWue/y2eZVFPpyOKBiMF9v3YSIcFSfEXxr0LiEHT8wUb/Lpn7E1w07Zp7keTw8fsDh9M5PvAb9+RXruH3BsnafK/J6eOWIfZI6738/s4pX1+wYthLgqjElnDYsuZYCs1eFmbcmTGEOBMOwvlbJ9cPY/l72GeHFk4TtGlGWLQzz1YwgTW2SCXoPFPY5Ihd/TuLjh+ojrPlvgMDGHf0Xf18YdEZewu0cACLVIZofWw/ro+a4fvAdVor/4OTed4DIxnrCn68GVbyTBqJ1zYTnbkCKc/HtOwiJoTOS7D2yxzt+FovFYuk+WMeva9j7o8Visew82HYOnRAIRZhw82s0h+Nzbn0eWPTbzDTx7nLE77Ab4bAfp8aWTqgP1nPoE4fSHIldE3XYoMO468i70mBV+zQtXMjqa68jsGSJEXrxeBC/Hw0GzWNn0UNyc9nl1VfwD8hMGmU4FOGTZxYx/5O1BJs6jqL6cjycfMVEBuxalj7j2hBobOCdB+5h0eefEgmHySssZMBuo1k8/XNCzU14vF7GHXYUR1x4KT5/ZiK9gfUNVN03C62LnSfv7Z1Hr/PG4u+bmYjfsmXLePPNN6mrq2OPPfbg8MMPx5PEKrfF0paYEb/hg8g98/jExl6/Ch65pfOdjjiP3D0PS2j8UN1aNk25neb1s4mEGiASAgS8OfiK+1Ox92UUDD0kobEB6mtXMP3Vs2gb7TN4GLnvz+k//KSEx+/OzKpeyiWz7ux0nzcO/C0l/uxsh/PPr+fx6PL2xdByRPjP/ocxqDDx3s0zNtdyxefttzIZVpDHvQdMIM+bWMqkqnLhh2tZWt/+fGC3Qg/3HJxc9s+HXwWZsihEUwhQ6F/m4eSJfvqVJn//CYeUz94KsGF1+7l2w8d62P2AxFsXbF0cYt1zwR2/th7oc6yfkvGJuzaqSui9WkLT60zzxHamujmX98PbN/0lTG7Ro2cYx/3lg7idPoBQBM781ycptKgDbkmgUel7v3bfjjg488Uz43L6AN5b9R73z7k/xRa1j4bDrLz0hwQWL96u7hmJoM3NEIm0UvzU5maWfPNbGbETYPrry5n1zqpOnT6AUCDC83/5kmAg/WI5Lbz/8P3Mff8tmuu3EmxqpG7TRhZO+YhQs0lJiYTDzH77daY+80TGbNx4b3xOH0C4qomND8xNWD0uGZqamnjsscdYvXo1tbW1fPjhh0ybNi3tdlh6LjGdPoClqxI//2M5fQDvJK70WvXeTTSu/JhIoNZx+gAUws2Eapax4e0bCNYlriz65evn0r7TBxBh0We/on5LYsqV3Z1YTh/AiZ/cmAZLuk5DKNih0wcQUOUH0z5MePyIKld34PQBLGto4ldxKH92xB1zNnfo9AF8VR/huRVbEx5/3powr8wKUd0AjQFoDMKSqgj/+SRAxIV74awpwQ6dPoCl8yI01CWouhlQ1j3TjtMHEIENrwYJVCcuwBKeUU/o3S2wpX2nDyDwr3UJj58N9GjHb9mmrsvpTluWCVW6rquPZoqVXZS2fntF+iX9AQIrVhBauzbu/bfV/2WAlfPjl2WOhJWqFelXy2xh+ZwZ8e03O7793CZcFyDSReXTcE1zRlQ9V69eTSDQWh1uyZKdc5JpySyR5alty5AIkVATzRtmd76Thmlel3gfVo3EVmesWW/TaDsiGFM9ITO8uDp2W64toRC1Cap6rm5oItby6/TNibWKAPikKvac8N21iSvxLlrfvvXV9crmrck7fhtWx16cXrYwPuXVtjSti33ONa5I/LyMLI5DDjRza++u0KMdv0QasQ8qT79gSneiLLesS/vv3mv31BgSA/+AAUhJ/MpIEkMBLJX0Hlwc/84CFf0yJ0QSr2BLn2G7pNiS9vEU+pHcrqXXSJ4Xb0n60zb69OmzQ1pn//79026HxcKAztUtM4HHl4evNLbqcU5l4k2+45kCFZUnM74lExzWJ3YWVa54KPYlVo7QNz92muLwwvyExgYYHcf9aI/yxO9ZA8raP+8LcqCsIHnxuNLK2N+r/kMTVPXsFft1uX0Sd22kfxzva2b09VyjRzt+z10+ucuveevaw9w3JBa3JNA8uqhrbQDc4tETHo1738FFg/nR3j9KoTUd48nNZdDtf0QK43CSRBh8z92pN6oD9jlpOIPHxqcme/h5o8krykztHMBh3/k+/XcdZR6IIB4PvYYMa7XPgFFjmHzWeek3DhCPUHH2KIjX98vxUHnuGMSb/kthcXExJ598Mvn5ZoIwZswYDjzwwLTbYem5yBVxfA+9Hrw5CV5T9jou9j6VQxIbG+h96E34Sga3/6Qvj/J9ryCnYteExx974O87fb7fyDN22nYOlw2NXdv4wJ7XpsGSrtM3v5C9yztXqv39xMRVN3M8Hn48ZniHzxd4PfxqYuILBjfuUUlBJ7ekAg+cN7Is4fH3HOpln+FeBGh5C0rzhTP3zcHnTd6rmXhQDgXFHY9T0Vco751YHZ63QKg8pOPXluztIa9/4vdz337FeCd0XrfqPT1D6v8usVOoes5fU8NHizaChqirD9OrOIfdh1Yyd+Um3v9qI+MHFXPYbn3ZfWiGZZtf+y18eluMnfxwy8a0mNMZCzYtoLaxlrCEKfKZAulCfyFVjVXk+/MZWjqU0tzkZW+TRSMRQlu2QHMAT2EBnvx8wlu24C0uJlhVRbhuK/mjR2XaTAACTSEUCDWHaW4MUtankKb6AFurm/DneCntXYAnAw5KezQ3NOD1eVFV/Ll5hINB6mtryCsoJCcJiWy3UFVCW5ohrEiOh0B1A57cHCRiHguCJ9eLp8CPJNFvyQ3C4TChUIjc3MSL3XsSVtWza8Rzf2x+/T2Y8XXrjX1K8X3nW3gTFKBoNf69N0Ft23TRHHKv+0fSY6sqGqwHXz6Rho14cgrB40PEi7jUKqh6wwyCTVvIya3Al2OuXwUlg/FkoAdttvHo12/xetV0JleMYe7W5WwNNnL24MM4etA+mTYtJk3BIHNqNpPr81Lsy2Hels2MKatgWGGxK22RIqp8taWOqVXV5Hu8DC/KZ2hpIX1cyiCqagywZEuApnCExmCYTQE4ZWgxxbnu6DIGQmq6W4Uhx0dSLRzao7kxgmoEVSEUhEBzmNIKLz5/8tccjSjB6jDNjSE8EfAX+/CXeBEXHFcADUTAK0Saw2hThEgggjSDf2jmswKtqmcM/v7u1/zx9a863eeNhZv509vL+fvZEzlxjww0cAd49v9g5sNx7Bg0CqCJRAld4tF5j3LXl3fRFG4iohEUxYcPr8e7TfjFK14m9p7I3UffTa4vcxNa8XiQSITaN95A/D5KTjwRPB6qn/wvgRUr8BQWEKmpoXD//TJmI0DtpkY+fXYxoVAEr1dYtbAaBXw+DwWlOYw/ZBClvTPvUK2aP4dV8+fSb+RuDNt9z23bvX4/JZXZ0+9KRAiuq6dxRhUajBDa0kxkSzPePvl4cn3QHMbXr5C8EaXkjanMqPPn9Xq3Tb43bNjAwoULKS8vZ8yYMa5Myi07N833PQGb2qkL3rCF0O334/nJxUlNgjvu4xeg+Y6Lyb3uvoTHBvNdbq5ZRvW0fxCsM72vRLwUDD2Iiv2uQjyJT2MikRDLZv2DTas/ItC00SiHooBQ1n8yYw64FZ8/ceXHnsBpww9iZvNS/rfxE7wilPmKWROuoSkcIM9Fx/iL6jXM3rKeCaV9mVSevMK2qvK3r+fxxvrVNIfD26oRc0Q4ZeAQrhg1ISlHpykU4pZZi5izpY7mYJjoyrALhvXnot2Sy8p6f81Wbpq5o+bEg0u2cuXoUk4elnyT7xyfsKE2wrw1YSoKhXEDvXhduheuWhJi8RwjGdpnoBevV+gzyIfP787idfP6CNVTwwQblMA6gCDl+0WonJz8ORmuChJ4YROsdGpASwUp8eMdWwAuO34aihD6dAW6YguekRV49x6U8vlIj4743frCHB74ZHmXXvOPc/bkhN3TLOs//XF44dKuvy4Dzt9tU2/jkQXxq7Tle/P57LzPUmhR54SqqljyzW8SrjJRUv+AAUQCAcIbW0dN+/zoOiov7rwRcaqo29TEw7+YgkY6/y4On9iLEy7NTM0kwJevvcg7D2xPiT3g9HM48IxzMmZPZ2x5dSl176+KvSNQuF8/yk9LPF3MLRYtWsRjjz1GJGKmKOPGjeOMM87IsFXpx0b8ukZn98fm/70Ci1fHHCP3+u8ndOxYzdu3jZ+E89ew4mM2vNl+I3FfyWAGnfFUwmNPe/lbNG3t+Drh8RWw/6mv4vVlfpU/E0Q0wlEf3UBDO0reuxYO4D+TfuxK5OzR5TP5++Lt84TLd9mXc4fukdSY5378DssbOxb4G1Vcyr/3S7wVyDFvf0ZjuGMRkQN7lXHbXqMTGvvNVVv59ezOhQbPG1HE90eVJzR+C4s3hHngwwAt4vfjBng478DkF+rnfBpg8dz2FVD2PtzPwBHJxZzql4RY+3T7Im5F44R+JyT+fY2sbqb57vUdPu8Zk0/u2e4tcjffOw1dv12hVUaUk3vOxE5fk+w9MjvyxlLEQ1O65vQB/OR/s1JgSQwScfoyxOMLHu/S/o3hRmZsmJEaY+Jgy/PPb3P6AIJr1uzg9AFsuje5Velk+OzlpTGdPoClMzZSsyFxJa9kmfbCM60ef/7Ss2gk+1TdNBSh7qPYk90W6qetI9LQNSXQVDBlypRtTh/A3Llzqa7OhMqwpccQh9MHEN7adQXsdFHzxb86fC5Uu5JAzbKExt1a83WnTh9AJNTA5jUfJTR+T+CTTfPbdfoAvq5fwwyXWl08uqL1vOuRFTOTGq860NSp0wewsG4LWwKJqXpOqaru1OkD+GRjDc0x9umIO+bGvu4/sTTxdg4tfPR1iOiOZ3PXRNi4Nbl7eiSiLJnfsezlotmJqXlGs/mjjsfYOje5YFbw/c7VWCML3FPhj6ypbeX0AeiSanRLHMqiSdCjHT+LJW5czm3fGbBvmcViyTTS3SX2LJYehv1GZjc92vH77gFdz7H+4xkZSKU7peMVzWzjnNFdS+3L9+Yzsc/E1BgTB6Wnnoq393Z1L//AgXh77ximr7z4onSa1Yp9TxweV073iIm9KeuTuTq/fU5t3eR+0omnIZ7su4SIz0PxQfHX6hbu0w9PQeaUUls48MADW7V3GDduHOXlyaXyWHZydonve+AtylyLmFiUTfphh8/5SgbjL0uslqqobFfyigZ1uo/HV0jlwIMTGr8nMLlyLAWe9lP/discwMTS+Nr7xOLcIa3nXecNSS7Nszwnj6H5nZ/To4tLKc1JrB7sgN7l5McQWjuwVxm5CYqxXTcu9nX/28OTrz09aFcf0Voo4wZ66FWU3D3d4xGGj+m4Nn3k7snfaysO6jhVtGhccm6n/9DOayc9oxNv07HDWANKkL6tP0cZUYGUpja1vEfX+AH8692v+X0McZcW/nnORI7fPUPiLs9dBTMejH//DIq7PDbvMf765V9jirvs2WdP/nXUvzIq7gIQ2ryZ2pdeRnL8lJxwAhoOU/vyK0bcpSCfwv0PyA5xl+eXEAqE8fo8rFqwubW4y6GDGL1fv4yreq5aMJdV8+bsIO6SjTQs2LRd3KW2jbhLU4u4Sxl5YyoyruzZQou4S0VFBaNHj94pxV1sjV/XiHV/bL7/SajqOH0pJ2XiLoZkxV0AmjbMoXraPwnWmdRMwUPB0EOo2O8KF8Rd/smm1R8SaNpEJFRPi7hL+YCDGL3/rfj82esUp4PGUDO3LHiY6TWL8YqHcn8Rx/Xbh7MGHuKquMv06jXMclnc5Y75s3jTEXdpST7MEeEbg4Zy+W7jkxR3CXPrrEXM3lK7g7jLhcP6870kxV0+WLOVX7Qj7pIrcOXoUk5yQdwFSLO4i5eyOPrwxUPTujDVU0ME6yME1gMK5ft53RN3ebEdcZcxBfgPcOd9b0FDEUJTV6LLa/DsWol30sCY85Fk75Epc/xEZDDwH6Av5kp6j6reKSIVwJPAMGAZcKaqdprQnGw7h4c++IppyzczrHcRi9bXkuv1UVHgZ9HGrQwoK8DvEX5+8gTyczO86v/8DfBlLPnrYrglPtGKVBGOhNnUtImq+iq8Hi8RjbC1eSt9i/ri9xh5/D75ffB6smPSGtq8GfH7Td+53FzCNTVEGhvxlZcTCYbwlRQjvswK3IaCYeqqGwk3KwWlOXj9XnJyvSjQsKWZ3HwfeAR/Tmbf03AoSCQUxu/IVTfU1eLxeMmLp19imok0hZAcL6aIQVGFUE0T4WAEjwe8BTn4Sm0LhXhRVcLhrfh8xSk9zs7g+KX7/tj8zicwbW7rjX4P8n/nk5Ng1KPV+B04f244fS1EQk2IeIw8fKgJT05RUk7ftnHDIQJNm2isW4N4/eQV9Ka5fi1FFWPwZnjRMptoCgfwiIccF97ztoQiEZojIQp97rfPWLF1K1/VVuMXD1XNjZT4/RzSdyB5Lt3zl29toKYpgIhQluujMjeHQr+7c8nNTSGW1DVT7PPSr9BPaQrmAYGQ4vXgmuPXQigYobFeKSwRmuohv0hcEQRSVQKbIwTrQnjyFQ15yC3z4it0572J1IcJN4fR+jCEwdvbjyfHg7ikShqNhiMQjiA58Z2T2ez49Qf6q+p0ESkGvgC+AVwAbFbV34vIT4FyVb2+s7ESdfwWrK3huDs/jnv//sV+pvz8mC4fxxVu6WLPu9xecMPi1NjSCW8vf5sff/BjgpHOxTC84uXXB/2ak0bEbgKbKoJr1rD8O98luKpzR1ny8uh3y82UfeMb6TGsDe88PJ/5H6/dYXtOvpdQIEIkqvp67EEDOPScUXgyEKGa9uIzTPnf44SDAcYcdBjrly5m44plAAwYPZazb/1D2m1qj1BNE5sfXUBgZR2S50WDEVpVsEfhyffR9/p98Ob1+M42SVFdM415835MU9NKSkr2YPy4u8jPT012xE7i+KXl/hgOhQjd8UBMexJW9XzgFtgcayHSS+51d8fYp2NUI2yecgd1C54DVXCE+cWbS/l+V1Iy5ludvr4zVsx7gOWzOy61KO8/mfGH/Cnh8XsCYY3wx6+f4sV1U8kRHxcMPZrvDjnatfFfX7eIO7+ewpZgE5N7DeHmsYe74gDWBgOc/P7rdCQzMrmyD7ftmXimzxebtnD1F/PbfW5CaRH/2G98wmO3sLguwOWfrKexjd7KwAIvd+3fl8rc5J2cUFj53+dBZq0Mk+uHY8b7OWAXd+6HU99sZt2K1sZ7PDDp8BwGDEvc9vrFIdY+0/4cVPJgyHdy8Zcm5qBpIELTP9bC5vbPHO8BRfiPK3fFeQUIzVhL6O1F0BjCM7o3/lPHIDH6HGatqqeqrlXV6c7fdcB8YCBwKvCQs9tDmJtdSuiK0wewti7IV+s6V/RJCV11+gCa09/EvT5Yz/UfXh/T6QMIa5hffPQL6oOZU4tbe9PNMZ0+AG1qYu3PbyRUVZUGq1qzYt6mdp0+gEBjuJXTBzDvozUs/HRdOkxrRdXypXzwyP0EmxqJhMPMff/tbU4fwJoF8/jipWfTbld71Ly4hMBK07dMm8IdOn0AkcYQmx9fmC7TuiWqEebNu46mppUA1NbO5Kuvf5lhq7o36bo/xuP0AQQbE1Sqi+n0AR1OveOjfslb1M1/GjQMbJ9EariZzZ/cTrA2fgXfaIKBOpbP7twhrV77MbUbZyc0fk/h9fWf89zaKYQ1QmMkwD+Xvsy82hWujF0TaOJ3Cz6gJtiEAh9tXMHDy5NT9Gzhii8+6fTM+3jTBtY0JK6M+fMZHd83Zm/ZyvvrNyU8dgu/nrF5B6cPYHVDmL/Nd0fx+dPFYWauDKNAUxBe/DKYtLInwOb14R2cPoBIBKa/n5iaagvrXuh4DqpNsOG1xMcPvrC5Q6cPIDxlK5GF7ih7am0zoVcWQqNRKY0sqCL86UpXxu6MtBQMicgwYE9gKtBXVVtmuuswqS7tveYSEflcRD6vSuOE/O0FG9J2rO7GitoVNIfbl3Zuj5CGWF7b9ZYabtE0v/3VuHYJh2letCh1xnTAxpVdv/FsXNlOM+YUs2FZbNnuFfPmpMGS2ARXd+09Da5NXha7JxMM1tDU1HpyvbVuXoas6Xlkw/0xssAdWf5UENjU2cKMEtj8dULj1lcvxGTZds6WKnccke7KwnZaXnwVow1GvCytryYQaT3J/qrOnUXt1Q2xWx9N2Zj4d6c+VjuHquQds6VbO3ZwFmxJznlqYXVN6/9DgXU1yWcCrl/V8fsTDkG4kwXZztCIojE6QjRvSNz+yJrY72tkrTvtnyJVW6FNK6/I+tTPR1Lu+IlIEfA0cLWqtgqnqckzbfcTUtV7VHVvVd27dzsqjPGQyD93+qTOVb5Sg3sqQalkZNlIynLL4t6/wFfArmWZa4xdOPnAuPeVggLyJqRf0XXQ6K6rNg4aU5ECS2IdczyeGEIjYw86LD3GxCB3ZFmX9s9LsgluTycnp4KiojGttpVXTM6QNT2LTN4fo8ndc1zSY6SK/AH7dvykJ4e8voldt0t67YFI7HSznVnVE2Cf8lGtHnvxsJdL9/XRJb0oblNHuXeFOynkE0pjX9eP7Z/4sSpj1GOdPKjdNZsuMbGi4xrT/Xu7M28c2af1TNnngaEuCLAM3qXj71ZOHni9iaVKikfwxBC9LEgijdS7W+z31TPCHdVNz8ASaFOv6Rme+vlISh0/EfFjbmqPqmpL9+f1Tn1DS51DykJs8395bJf2P3FcH3oXp1ZGtV1uSSB1b88LXDcjFn6vn38d9S/6FsS+oJXnlnPvMffi92ZOMKffTTdReNBk8PnA64XcXGhbdO3xkDN0KEPu/ldGJM37DC3h4LN2xdPmIujxQK/BheSX+EHMxa6gNIeDztiV4bv36mC01FHapy8nX3MDvYeNoLRvPw4573uMnnwoHq8Pr8/PHkefwKgDs2OCVHbSCAom9cVTnIOvXwHeyjykwNducyH/gELKT8vc4kR3YcL4v1FZcQg5OX3o3+9b7LbrzzNtUrcnHffHuGr3+iSxkHT8JbH3GZvcdSF/0H5UHPAjfCWDkbwKxJcPHh++4kH0PfqPePMTs9/j9TP6wN8i3o5b5AwZezEFJcmpM3Z3DqocxzW7nMag/F6MLBzAr8Z+lyEFyS82AOR7/fxx92MYX9KHvrmFnDdkD84clHxtHMCf9tqf8k5EVi4ZPooif+K1hH/fdzxFHahsnza4L+PLkhfB+sXESoYX7ehgHtA7lx+MSqBEqB32Gurl6HE+yguEgeXC+QfmUJyXfP1aUZmHUXv6duj3m1cABx6fXA3noPNyoAO/298P+hyT+LzTd0wZnt068ANyBf+pFXiHuiP6JHl+/GdOQAaWQEku3oOG4t0reUXbmMdNobiLYGoUNqvq1VHb/whsiiper1DVn3Q2VrKqnhaLxWLpHuwk4i72/mixWCyWLpPsPTKVUnaTgfOB2SIyw9n2M+D3wH9F5CJgOXBmCm3g6D+9y9cbYud6A/z0+FFceujIVJrTMV0VeLlxk4lkZYBfTfkVzy9+nkA4sK2Hn8/rIxAOEIkqvh9cNJiHT3iYyvzKjNjZOHs2mx9+mMCSpfj696f8zDPRQDNbXnyR0IYqtLkZT2EhxcceQ/lZZ2WspcO8T9bwydOLaK7fMXE9J8+LeIXKAUUc+K2R9HWpd48bbFq1kumvvcCK2TMJNjfRf5fdOP7/riMnP/Opy1unraP2jWVEmsLgFcTrQbyAgqfQT6Q+iAYj5AwppuLsMXjzM/PZL126lNdff51gMMiBBx7IpEmTMmKHJe2k7f7YfNu9ne9wwTfI7Zt4BCdWHz//Nffg8SSeXBRqqKLqnRsJbF6EeHOINNeBhsCXR6+DbqBol65l9kQTbK7l81fPJNQcXY/lwePJoazf3oza7xZ8OaltX9Id+HDjHP67+gNqglvZs3Qk3xlyJL1y3Yk4pYqGUJDj33utQ4GXG8dO5LgBg105Vm0wxFPL17K2sZnD+lZwUDJR9HaoD0a4dcYmZlc3U5bj4YbdK9i9wp3stK1NynPTAyyuipDnh5P28DNuYHL3Q1Vlxddh1i4LE2xWisqEEeP8lFa4k2QYblCW3tcE7UhOeEthyHl5eAsSj1pqIELo/S2E5zagDY4quFeQ3n58h5bg263jLIF4Cc/bQPirjXgqC/DuOwjJTd8cpEc3cL/4oc94a37XinfvPn8vjh3Xv8vHSorHL4CFCSgiZqCJ+zXvXsNbK96Ke/88bx7TzpuWQovap2nhQpadfgYajK8It/y88+h3Y/rT177+fD1v3Dc39o6AeODMn+1Lr0FFKbYqNls3b+LB6y6juaG1amtZv/5cdGeMiWaKaZi5oUtKnZ6yXAb8tJM6ohRRXV3NX//6V6Kvwaeddhp77LFH2m3JJnaGiJ+bdHZ/bP7Lg9Ac+xqYcDuHGE7ftvET7Oenqqx85BgigY4Frfqf+hC5vUZ1+HxnfPy/Q4mEmzp8PregP/ue/FxCY/cU3twwnV/M/0+rbYPye/HE3jfgy5Jeve1xyFsvEkub8n+Tj6RffvKT+Es+nc382u33wpsmjOTo/u6VZJz93hrWNLZ2YR85pB+DC5MrpYmo8sdXm6lpaO0HXHJoDsN7J/7ZLvwyyILprReyvT44/LRcCkuSc/5UlcW3d/ydBSAHdrkyL+GWC82PbCDyVcfHyDm7F94xiZ83oS9WE3r1q22PPcPKyDlvz7hfn7XtHLKBrjp9AL99ZUEKLIlBIk5fhvhg1Qdd2r8p3MTCzemXy6998cW4nT6AmqefTqE1HTPjzfhlsTUCX01NfyuH9vhq6ic7OH0ANevWEmiML8KeKuo+6Jq8e6SmmXBt/Gq1bvHxxx/TduHtk08+Sbsdlh5MHE4fQHBD8tLzqaB5/exOnT6A6s/uSmjspoaqTp0+gOaGtTRkUJk6G3hx3dQdtq1q3MiMLenvIxwv9cFgTKcP4PfzkldsXVLX0MrpA3h5tXvSFWsbQjs4fQDPL09e/XHlpsgOTh/A+wtjyGbGYMVXO9obDsHqpcm1dgFoXhdHsCoAzesTVA1tCHfq9AGEvkyuTVl4ZusWXpFlNWhNDGfWRXq045dIj+veRe4UbfZUcr1df3/Kc9OvmugtK+va/uVd298t8rq4YpdXlDmxnGjySzpIORXB20lBfTrwFHY9ZUJy0r9yXdLOe1hQkPzqs8XSZYqy87zz5se+d3gLE0tT9fniS0n35WQ+wyKTlPraPzdK/dn7vuTEmVrc34WyhGK/b4eJdGmOe/fAAl/7E9nKvOSn7wW57Y+drLhLTgdZqDkdHK8reOPMcI13vx3wifnpBClI7r2Xgjbnh1cgN31zkB7t+N357fhDpy389eyuvyZpLkt/KmSiXDXpqi7tP6FyAn0K+6TImo4pO+MMckbu0mqbp6wMT1E7Nyuvl74/+lGaLGvNId/eDYlzhaK4MpexB6Ve8Skedt33QAaMGrvD9rGHHIHXl1nHr+zkkV1a9cnfsw+evPTX+B144IGtHD2Px8Pxxx+fdjssPZgDJ8a1m78g0Qlwaicr/tLB5PXvpO5VvFQe2Kn2TYf4coooruy8FUTvIceSk5eZGvVs4YKhx1Dcxkk+oe8+7FqUHfei9vB7vQzJi31OXz92YtLH6p2Xw5lDt5cHlfp9fGe4Oy0pAEpzvBw/sLXzXeITTh2SfO1p72IPEwe3dgP8Hjh2QnL38DGT/LTNAi7tJQzqpMVDvPjLPfhjrPUUjPDgL0vMvZEcD/6jOqlfzfPgOyg5rQXfwcNbOXq+yUOR/PTNm3p0jR/Aui31HHLbewRixP2PGt2bv527F3n+zIg8EGiG38bpIFWMhys/Tq09nbCydiX3zLyHxVsWg8CY8jEU5hQyq2oWgXCAjY0byffnc/nul3PMiGMyZqeGQtR/OpXQ+nV4ysopOvAANByh4bOpRJqb0aYmyMmhcO+98fdNvudOogSbQ3z+6nLWLa2haWsQjYBGIhT3zqf3oGJCgQgDdi1j+O698HQgH50JNBJh1fw5bFqzmi3r1zBynwMY2I4zmAkigTC1764gtKUZX2EOkudFfB40EMZXmU94a4Dg+gYK9+lH3rDMiRREIhG++OILGhsb2W+//cjNtRkHtsava8S6PzZv2AgPdFBOkOsj9+oLkzp+8+v/gTkdlAAU9iX30t8kNT5Aw8qPqV/yNjm9xtNUNZtA1RzyBx1IxX5XJSUcA7BhxTt8Pe23RCJBSirG4vHlkZNXQb8RJ1Pae2LStvcE6kNNfLp5PtXBrYwrGcqY4iGZNikuXly1lNsWzNlh+37lldwxKf4+v/GwuK6BtY1N7FVRSoHP/QWROZubeG7FVsaW5XLq0CK8CdavtceKTWE+WxKiV7Fw0G5+fImky7WhuVHZtC5MJAK5+UKvfp64F7njoXZ+Mxtei0BLVqoHJBf6neyjcGjyTlRkU5DwvAa0KYzWR5B8D55+OXjHFCA5yc/DtClIZHkNUlmAp1fXWolls6pnVtCnOJ+Dd+vNlMVVNDjlDh5olf9d4IeKwpzMOX0AOV2Y8B18dcrMiIey3DJ6F/bm4MEH06+wH73ze7Ng8wIm9p5Ivj+fqoYqRlWMYlRFYgX3biE+H4X77UvTvHl4e/WiacECcocPp/CAA8zfu+yCt6OUxTTiz/Uxcq/e9BlaRN3mADXr6wg1Rxi5dz8a6wLUbm5CI8qWqkbK+6W/12B71Kxfy+x33mDYHnvTe8gweg8ZRt3GKur7VlNYlgUN0SOKv08BOYNLCNc24ynykzuslPqp6whsbCB/l3IK9uiDrzSzjpbH42GfffbJqA1doaFhGeFwI8XFY6ivX4SiFBXuSiQSpK5uDnn5g8nNSX+fSUvH5Pbp1Z74neGEw5M/wORTOnD8PHjOvi758YGCwZPxFfYj3LAJ8Sg5xQMoHvutpJ0+ACIhvL58vFJIfe1ywoHNIH4Ky8ZYx8+h0JfHkX3Skw21oqGGYCTCLkXJK2O+vrr9Gvqvqt2vad2luIBdilOXMj2+Io/xLil5tmVIpZchle46q7n5Qkmlh03rIjTWR9hcBQVFHvIL3XH+Ns+McvoAIqAeiITdCWZpMIIGFSIg/f2Q70VKfOB3x37J8+Md5U4/zC4fuydH/BZtqOOoP3VNjOSrXx9Pji/NUZWGGvhDV5vEeuCW6ti7uczTXz3NLVNuiWvfffvtyz1H34M3Q8pfgWXLWPG9iwiuWbNtm/j94POhjY1Ifj4D/nAbJUcfnRH7AAJNIZ7/85dsWN65gEELwyf24rhLJuBxceWsq7x579+Y9dZr7T8pwiHnXMg+p3wzvUZF0TBnI5sfnQ9xXNqKjxxC6dE7d4PmeJk37yesXWdEkHy+UkIhoypcVrYPjY0raW5eh4ifXXf9GYMHfSfh49iIX9foVNVzw2Z4IIZwVV4OuVd9N6FjN796P8yLIUi0697knnJpQuMDRELNbHjzRzSt2bEkomzvH1K2R2K2A0x59lhCgZpO9vBx8FmZy67ZmYiocsvcd3lrgxGN2ausP3fscRy53sQW5A9668WY+3x01MkJjW2JzfQPAqz8ekcxl90m+hgzKfGIXCQcYcmfOhdj85bC8EsSS1/XoNL00HpYEWh/h3IveZf0Qwozp2hrVT074ay7u66Qd+kjGai3+8OwBF4Uj2aV+/z+s9/Hve9n6z7jvVXvpc6YGFTd9bdWTh+ABoNoY6P5u7GR9b/+zQ7Kiulk7odr4nb6AJbO2MiymRtTaFHnBJoaO3b6AFT56ImHaKyrTZ9Rbah55uu4nD6AundWEKpOn5pWd6W6euo2pw/Y5vQB1NRMo7nZqM2qBlm06DZCofjPaUsKieX0ATQFCIcTVNuL5fQBfJ1cc/n6xa+16/QB1HxxN5FQYt/frVsWxXD6AEKsXdR9VLe7M1M3r9rm9AFMr1nLK+u+6uQVHfOjL6bEtd8V0z5KaHxL52xcG27X6QP4akaI+rrE56/LH4ytwB3eAs0bE7umhWfVd+z0AVSHCU3p3ve3Hu341TZ2XZL2q3XJS+R2neyPurYQCHfyhWiHtVvXxt4pRbR1+tojVFXVpbYPblO3ueuTlkRe4xZNW2Nf8CLhMPXVm9NgzY5oRIl05XuvEN6S/lYO3Y2mpvhbZEQiTQQCmVucsCRAQ/YufoS2dtLCRiNEAonds+vjbDO0ZeOMhMa3dI11TTveW9Y1JfbZLtwa38Ljgtr090LeGWjY2vmctjHG850RjnNNuWldYs6l1sSeP8SzTzbTox2/b00a1OXX3HrKuBRYEoNRp6b/mAmyS9kusXdy8IqXwwYfljpjYlASh0Ji8ZFH4MnJSYM17TNyr64pnnp8wvA9MldDVdKrDzkxGt6W9x9A5eDMpE+KR8jdNf4aQ295LjmDk1dH6+lUVh6K19uRfHvr20hx8TgKCoan3ihLbCrj+y54i7Ojdrg9CoYdTkdTFW9hP3wFiV0P+wyLT0F3xB5XJzS+pWtMrhxCnmd7WqdXhMN7J3YduW33TpRgo7h3n8kJjW/pnL6DvDuoeraQXyhU9E3c9eh1eHxlLiXjEksR9o6LXafpHZ+d7W/ipUfX+AEc95cPWLAuvrDssWP7cPd3MiS0cEsXlQWvng9l6ZdTDkfCnPPKOSzcvBCPeBhcPJg8Xx7rtq4jEDHRQEUZUDiAn+//cyb1je8CnApUlZonn6T29TfQhgbU5yV/3Dg8+fk0zpxF/vhxVF76Q7xFmZ30LJu9kc9eXEr1+npCzdtXqURAPBCJgNfnoe/wYg74xkj6jcicCiVA3cYqnvzlz6jduAGfz09RRQXNDQ2oKgN2G8ORF11KcUXmnNNIIEz1M1/TtLAaDYZBQfweJM9LZEvAPM73kTe2gtIjh+JLUcF8T6Oubh7LV9xDOFRPWdk+bKmdCUQYNPC71Dd8zcaqNykoGMGwYZeTm5t40bqt8esaMVU9b7u309fL2SeSMySxe0kkEiH450s63cd75T/w+ZNbXGtcM42aLx8kWL3Yaeiu+Ct2pd9xd+LNK0t43KoV77Bgyg0dPj9sjysZPPrchMe3dI15tVU8vmIWzZEwpw8ay74VXV+8b+HSqR8wp67jiF4vj5fnjjgh4fEtnVOzMcKcqQFqqhTF6Bf2Huhh1EQ/hSXJxZyWPtRIeEPHz/c/I4fCYYnX4IUXNxF4YRNUO+migulcU+zFf3gZvomZnTMme4/s8Y6fxWKxWLoP1vHrGvb+aLFYLDsPtp1DDM65dwqfLI6v3mh032Jeu+aQFFvUAbdUAF0oRr34XRi0V8rM6SpT1kzhXzP/xfLa5eT78jlm2DFcNvEycr2ZlcsPrl3Lhj//mcCixRQddhi9fnipUfbMMmrWNzD1hSVsXltP3eYmgk1hxAP5xX5ycv3kFfuZcOhAdtu3X0bt/Oz5/zH12ScJOAI5/rx8Jh5zIgef/R0WfPIB7z98P4GmBoZOmMiJV/4EX4bSaLe8voy691caDSTBdKWNbuYpgAieAh+lJ42gcGLXUm53RlQjLF9+NxuqXic/fwi7jLiWgoJhmTbLEoPw0lWEnn8TmqPqUkTw7DYM36lHIi72A4tsWkPw6b/A1mrw5uA94mx8Ew5KetymDXPY+N7NhBqq8Pjy8Rb2pWjEUZTsfh4iiUcP5n76ezYv70S8xVvIwae/k/D4lsxx5vuvsybYsSaBF3jfqnqmlLqaCPO/CNK4VRk4wssu432uXG+W/ruRcCfT+sojvJRPSnzu0fzGZiIfdVBfWu4h74cDkLzuWynXox2/1+asjdvpA1iwvo6f/G8mfzh9jxRa1Q5v30aXnD6A+w6HW7KjMHlF7Qoue/syQpHtE4v759xPU6iJG/brOI0mHaz84WU0L1gAQNO8eWgkTJ+rr86oTW2JRJQX75pB7cbWAgsagYYtQRoIwgZYt3gLBSU5DBqdfH+jRFg45UM+fOzBVtuCTY1Me+F/RCJhvnhp+wRq0bRPefUff+Lkq3+aZiuh/ov11L27cvsGpbXT17JNlcjWINVPLCR3l1J8xbZ5emesWHEvi5fcDkBd3Wzq6uZwwP5vJTXxtqQWbWgi9N9X23lCiSxcSujVD/Gf4M5ip4ZDBB/9DQQdsaRQM+E3HsQzeBSessRTfzUcYP0rl6GOsFgkHCDSvIXqzV+Bx0fphHMSGjccau7c6QMI17NszgMMG59ck3tLepm+qapTpw/MjOu1lcs4bvCwtNi0sxGJKJ+8FqCp3mQV1mwM4fEKI8Ym53ZsmdvcqdMHsOmdMKV7RPAk0JotPLehY6cPoDpC04Pryb+0f5fHzhZ69B37tlcXdPk1L86MrQTpOh/+Nv3HdJEPV3/Yyulr4Z2VmV0pDa5evc3pa2Hr29m3ertp1dYdnL6OWJrBVg7zP3q/w+cWfLzjc8tmfJFKczqkYUZVl19TP219CizpWVRtfKvV48bG5dTXf50hayzxEF62qtPnI0vab3CdCLpu2XanL9qGWV3rpduW5g1ztzl9bWlY8WHC465Z9L+49ls5776Ej2HJDDfPmR7Xfr9ZODvFluy81GzUbU5fC+uWJ9g2JopN78Sn1rllRmLHCs2uj73TmswpwbtBj3b89h3e9chI/9IMCD0UD07/MV1kWMmwLm1PF97KSjwlJa225QwblhljOqG4Mg9vnCtTZX0zpybVqxOlzooBA3fYVtwr8VX+ZPD36/p7lDukJPZOOzkF+a0V9jyePHJzu++q586Ap7Ks0+elpCOl1q4jHUT1PANGJDWur2THa0sL/pLE751lfeMTcssrGpLwMSyZYd84xcVG5mevmm13p6BYaJsMUlSafJpnvLecgiGJuTeevnGUAnXz5KAe7fj9+rQJeLpwngnw7OUZkPe9ZlbXX9OFtgqp5sABB3L6bqcjbH+zBxQO4Mf7/DiDVoEnL49+N9+Ep9Bc3HOGDaPPdddm1Kb2yCv0c/BZu+LL6fzrOGxCJWMmZ26ivc8p36Ri4I4TreLK3hz3w2sYMn7itm2+3FyOv/y6NFoXZc9hg/GUxJ/fn7trGXkjy1JnUA9hxIirKSocBYDXW8Co3W7G77cOczbj6dsLz5gO7hV+H76TDnftWFJYiueANq2J+g3HO3LPpMb1FfaheOyZO2z3V+xK2V4XJzxucfluce239/GPJXwMS2b4xYT41MQfmHxEii3ZecnLF8bv58friGuWVgq7TUxeX2Hg6fkx9/GVQG6fxFQ9fQeUQH7nczH/2ZlZ1HaLnULV8+kvVvDEVJPSskufAqYs3symumZ6FeeACIMr8jlm3ADOPyDDvacePA2WxZGKeP0yyI+/V1m62Ni4kfpgPWENM7R4KN6OGrmkmUhDA8F168kZPsxVIQO3CTSGaKgNkF/iZ/H0KvoOL8Hr9ZCT7yMcilCcJW0HNq5YTvX6tXi9XooqKukzbPuKfs2GddRWVTFozFg8Gf78m1fVEVi+hZxhJXh8XiLBCM2Lq00rh+FlhLY04y/Pw1cZ+0Zi2U5Dw1Jycnrh86Wm/6FV9ewa8dwfI7X1hBYvRxSkrBiP14tnaGraAWlzA5Els5F+w/CU93Vt3FBjNYFNC8mtHE0kUIu/1J1IXNWKT1gw5ZodtlcOOpGxk29y5RiWzPDvhXN5YOWSHbbvV1zGHfsdnAGLdj6CAaW5USkqdTfOtHFqIzVfgK8UvIUQqgFfMfQ+yEdePFG7GARWNhD+uBZCQDgMYcEzrpCcSSWIL7PzSNvOwWKxWCw9Buv4dQ17f7RYLJadh2TvkT061dNisVgsFovFYrFYLNbxs1gsFovFYrFYLJYej3X8LBaLxWKxWCwWi6WHYx0/i8VisVgsFovFYunhWMfPYrFYLBaLxWKxWHo41vGzWCwWi8VisVgslh6OdfwsFovFYrFYLBaLpYdjHT+LxWKxWCwWi8Vi6eFYx89isVgsFovFYrFYejjW8bNYLBaLxWKxWCyWHo51/CwWi8VisVgsFoulh2MdP4vFYrFYLBaLxWLp4VjHz2KxWCwWi8VisVh6ONbxs1gsFovFYrFYLJYejnX8LBaLxWKxWCwWi6WHYx0/i8VisVgsFovFYunhWMfPYrFYLBaLxWKxWHo41vGzWCwWi8VisVgslh6OdfwsFovFYrFYLBaLpYcjqpppG2IiIlXAcpeH7QVsdHnMVNBd7ITuY6u10126i53QfWzdme0cqqq9XR6zx5LA/THV55YdPzNj2/EzN7YdP7Pjd2fbExk/qXtkt3D8UoGIfK6qe2fajlh0Fzuh+9hq7XSX7mIndB9brZ2WVJHqz8yOn5mx7fiZG9uOn9nxu7Pt6Ri/LTbV02KxWCwWi8VisVh6ONbxs1gsFovFYrFYLJYezs7s+N2TaQPipLvYCd3HVmunu3QXO6H72GrttKSKVH9mdvzMjG3Hz9zYdvzMjt+dbU/H+K3YaWv8LBaLxWKxWCwWi2VnYWeO+FksFovFYrFYLBbLToF1/CwWi8VisVgsFoulh7NTOX4ikp9pGywWi8VisVgsFosl3ew0jp+IHAe8KCI3ici4TNtjaY2IdKtzUUQqMm1DT0VEJNM2WNKPiBwpImdl2g6LxWKxWHoqvkwbkA5E5GDgz8BvgCHA2cCNGTUqSUREtAco84jIXsAyVd2caVviRUSGAj8Qkd8AjaoaybRNXaXl/BGRIcAmVa3PAlsGq+rKbDuvRaQPsFlVQ5m2pSuIyG5ARFUXZdqWOPEAj4tIQFWfzbQxPQERubaz51X1Ty4dZzfgn0BfVR0vIrsDp6jqr10afzJwCzAUM28RQFV1hBvjpxIR6Qv8FhigqseLyFjgAFX9d5Lj3gV0eK1U1SuTGT/qOGcAr6lqnYjcCOwF/FpVp7s0/lXAA0AdcB+wJ/BTVX3DjfFTiXOeDyNqLq2qz7g09pvAGapa4zwuB55Q1WPdGN/SOc417cdsv+YAoKpHZMwol9gpHD8gH7hFVZ8UkX2Ah0XkL5jJXLedtDt/fxsYAMwHPlLVuowa1wVExAecCywH/ioinm7yeRQDRwLPqepn3dEJdxytk4GLgRuAeRm25Xjg+yLyU1X9KlO2tMVx8q8HrgW6jeMnIsXA/wHPAYuy+bvlRPtVVd8Ukcsx1+ezVfXFTNvWAyh2fo8C9gFecB6fDHzm4nHuxUyS7gZQ1Vki8hjgiuMH/Bu4BvgCCLs0Zrp4EOPY/Nx5/BXwJOZ/SobPk3x9vPxCVZ8SkYOAo4A/Ypz8/Vwa/3uqeqeIHAuUA+cDDwOuOX4i4gX60noCvyLJMe8HdgfmAi3XVgVccfyAXi1OH4CqVjuLkK6RSudGRL4J3Ab0wSzUtCzWlCQ7dpvjuP7ZOjwF/AtzbXPtmiMidbResBHncUren/bYWRy/D4Ei5+95wEIcp6+7TtoBRORS4DvAHcB/gYuc390CVQ2JyBzMhIRs/zxEpAyoU9U5IvIAcLOIXKiqGzJsWpcRkYmYCPjFqpoxp8+xZRImIv+9bHL6HNYAE4CfYiIO3QJndX4lcIuITM1kRDcWLQ6piFwDjABeAx4TkYtUtdtcz7IRVb0VQEQ+APZqWRgUkVuAl108VIGzCBa9zc2Fki2q+qqL47UixZPUXqr6XxG5Abbd95KeSKrqQ9GPRaTI2b412bHb0GLricA9qvqyiLjl0IN5rwFOAB5W1blupvuLyBXAzcB6Wjtouyc59P6qOjbJMTojIiJDWpwYZxHS7blRSpwbhz8AJ6vqfJfH3UYKP1uAkKr+04VxWqGqxbH3Si07heOnqo1Ao/N3vYgUAI8B33aiDVnrbLSHc1EsBQ4ATgGOB6YCT2fSrngRkfFAH1V9B7Oyd5GIXKeqd2Tr5yAiI4ErzZ/yc+BxYDDQH9iQzRGVDhgKfNkSscT09IyIiF9Vg2m2ZTTwlqp+Em1Lmm1oRUsNp6puFpHvA9eLyGhVXZBJu2IhIrsAu6rqa6r6R2eFeH/g7Ww+R0VkV+D7wEmqukREjgaeFpEmVX0hxsstsekLBKIeB5xtbrHROfdaFiVPB9YmO6hTCgDwroj8ERNNaW553q10Q1I7Sa0XkUq2vzf7A1vcGty5nz4MVJiHUgV8R1XnunSI1SJyN3A0cJuI5OKuPsQXIvIGMBy4wclWcPM6dRUwSlU3uTgmwBQRGZvChdOfAx+JyPsY5/hg4BKXj5ES58ZhfSqdPgfXP1vZrt/woohcBjxL62uOa2VJIrIH5nMF+EBVZ7k1dmfsFI5fC1EO3reAw0TkW6r6dLY6G9E4N45CZ/VnT+BrTPTyfiAXONpxYq/FnEDpSgPpEk5Y/hDMRPqfwEuYVINjnRz2mmz5PFrOFycVbQXG2fsW8CImdecQoBK4NFsn1C20s7ixBsgRkUHAGsfpmwwMF5HHVTVl6VTt2LIMOENEdnMifiqmLneAqj6ZKjs6sg0YiIlArhSR9zCRkQAmGrUgWxeKRCQPU7+8j4hcgMkEKMGkZL2dTedoO+/hZmA25rzESfv8O/CciJyYymjPTsJ/gM9EpKV28hvAQx3v3mUuB+4BRovIamApcJ4L497R5vHeUX8r4Fa9TSonqddiUmx3EZGPgd7AGS6Ofw9wraq+CyAih2EiOAe6NP6ZwHHA7apaIyL9MffspHGutzdh3pMlqtrgzHUudGN8h5W46GhH8R+M87cO4xi0RIndiDahqq85Cx/7O5uuVtWNboydSufGiZ4DfC4iT2LKDaLHdisVFlLz2X7B9tRLaH2uK2YekDRialu/z/bU4EdF5B5VvcuN8Ts9dhbOX9KCmNYONwF/VdWkVyZTieN47AVciolc9gV+iLk4no5xPGaIKcL+BfBNzSJBhygHaiRQ7/wUYv6HfpiwvAf4saq+nzlLd0SMGuw3gCbgSVWd4mwbiFltGgBMUtXlmbMyPkTkSGAXYKOqPuOkq64CZgEbMIX1F6nqB2mw5WBMUfwKVX3fWQRYjKl/WYupf7lcVT9MtS2OPS3naJ6qNonIGGA3zMTzDmAyMAk4UlXXpMOmeIiyuw+wVVUbnO2/xoglnAMMwogEvJNBU7cR7fS1XBNUda2IPIURS/qO89y5wEHAndkeae0OiEmpPsh5+IGqfpmCYxQCHnW51lxERqjqkljbEhi3ZZJ6KOZe9BwuT1KdCFkYU2cpmFITj6o2d/rC+Mefqap7xNqW4NheYK6qjk52rE6OMVtVJ6Rg3BZho3GY9/5lWn+2SQkbicgijFM/m6gIpZtzARE5BbPADPCeqr7k0rhLae3cRKOahGiSM6/oCFXV7yU6dtQxUvrZOsfIU9WmWNuSGH8WRuSp3nlcCExxa+GgM3aqiF80qtooIj/PplXwjnCiMbOAMuA04DJV3SQi92Am8j9yomW9gXOyyemDVkIiN2IcjC3A/1T1JudkvxWT31+QQTN3QET2Bf4BXIZJpz1TRMao6v3O858Cpdns9LWk9zn/y78xq/zfE5HRwA8wN64TManD16TS6RMRr6qGReQQ4FHgEeAuETkfswhzIWYxIADclC6nD7ado6cC33FWnP+OWQWdgXl/6oFdMQsWWYNj9ynAz4AaEZmhqj9V1RtFxI8R8DgfGAm8kw3Ryiin7wpMBP0rZ3J8JiYq9RSmZuMo4ChVXZUxY3sQqvqFmLrPPACJqh9KFmmjHmoCOWwBvlDVGS4c4n+Yxc9onsIsxiTDyVF/NwDHRD12S6hjiqruhREBAUBEprPj/5MoS0TkF5h0TzCR1qQc4hac6/VCN8+VdpguIvuo6jSXx22ppVrh/OQ4P+BOrVyVpjANXUR+j9E/eNTZdJWIHKiqP0t2bFUd7hyjXecmybEvdMaZrKoftxl7cjJjR5HqzxbgE3b8jra3LVGE1nWVYdp3xF1np434dQfaTtKc9K0hwETgn6r6prN9LGbFaUs2Ri+daMQrGPGZDcAemOjlP1X1dWefCjX1VBmfmEZFUS4Cxqjqj5yUlLMwEdaLNUptKxsRI0QTUtWtjtN3FmaV/3kx6Z3PAS+o6i9b9nfSeFx//0WkXFWrnb/HYxzOV1T1VSct6QXgAicKmYsRiqhO57kgRpb7EeACYAxGtXW6qv4tymHdMxVRkmQQkcOBP2EWTr6NUdz7q6peG7XPPs4+J2fLeStGxfXHwKmYWpZ9VfUIJ7vhG5gU1U9tpM8dnMWBOzAZChsw95EFqupKT1sxCp57Y9LgAU7CZBIMA55S1T8kOO5ozKr+H2idclWCyRBxy/52J6ltt3VxzH6YzJBHMJH3lkldCfAvt6JozqLvrWyP5n6IUTGvdmn8DzDlJZ9hFsAAUNVTXBp/AWZRbZkzvqspkyJyhqo+FWtbAuP+A7MY/yIpSGV0Fvsn6nbxKy+mLt+1iJCITHcWJTrdlm1jR43n+mfb5nt7btRTbn9vrwW+i1lgFsy98EFV/Ysb43fGThvxy3bapEMdhUnbekVVN4jJDb5KRDZgTsaRqtpZeD1jOA5TGLOaOseZQNdj6g9GAq/D9pzyTDt9DuWYmqPFwLlRE/4nRORCzEQk4QlBqhFTHH8xpiZxKyYV4mRgnYjkquoqJ7r1poj0VtUrgFpw//0XozT3AxF5zFkxPgLz2a8SkY9U9T1nUvqOiFzsRFObU2FLB/a1fM+GAV+rEYuYLiKrgL+JyMdRzt6MNq/JBgKYgv9JmOjZvhhRlCLgCjXpZDmYWtS0rCa2xbkGtP08twB/wSwG7YWpIQKT+uJmDYjF8CtMrdBbqrqns2DgRg1eC4MwqqFbAUTkZkz61SGYmpmEHD/MteskzAQ7OjpXh6mPcYu72HElv71tXeFYzELSIMzCSwt1mAi9KzgO3pXOdV/VfVXPX7g8XltS3ZfuBkx0ONa2rpKPuVelIkrcQhlmLgImK8cVopybfBHZk9aLEkllXonIAZh7fO82mQAlgDeZsdshFZ9t9Pf29qjtW3H3e/snMRoCB2HOmwvTtbBsHb8sJcrp+z9My4YXMWloR6jpeRPGCIzkY1YKsg4x9TuDVfVdEVkG3C0i31fVWsdpHZVZC7cTFeXbG/ivGGn5V4CPgFPFNOFdhlHxdKXAOlWokfL/D+ATkUtU9R4RCQHfA6aKyBRVXS1GOXGY85pUpTwHMbWDuY4tfxWRZkx0YD8R+cRx/o5ge6pGOhmLScGaCYTE9Kr6VE3d4duYi/+XsP07mUmnL+o8LcREdD92VoLvx9TCTReRBzEriQMxKV9rMM20XYkAJECeGmVlROR7mNY6szBpx/NUdbLz3AXAMWJqfmozZGtPJaimPMAjJv37XTG9bN2iD1FRD8z3vq+akoqEa9lU9XngeRE5QFWnJGtkW1I5SVXTbuEhcUTkkhmrM0RkAkZopMJ5vBH4rqrOcWN851rYF6ftEvCZutjCSFWXO9fdXVX1ARHpzfb2WwnjZBWcAAwUkb9GPVWCC61G1ElpTCG/A74UkXcxjtkhmLZCbhDt3NzBdsevluSdmxzM5+dje0pmy9inJzk2kNrPVlUfEpGPgG9ilNvDmLrcx1JwXwpjnD7FXSXbTrGOXxbjpMGdAxyOUU3LBWaLyCQnBe1tjKDDysxZ2ZqoienBmPSTIsd5/TVwBfChGCGPKzH1XFmBY3NLutw8TJj/Gxjn+iRMOlotJoVmYabsjEXL++9Ehs8G9heRsKr+W4yg0Q3AHSLyvqquBlan0h4n4tQsRkThYMeWu8W0VDkDoyz6nqq+F21/Km2KOkd3xchlP6Wql4jIbEx7lL1EZCZmQeWRVNrSVRy7T8E48aUi8gfgU4wjdZCYVNlJGDGXJc5rlmbKXhEZgVlI+baa2uM8jIrseyLyE+AmETkN09LjTOB86/SlhBonCvwBRj1uA1Fpey7wKGZR6Xnn8cmYXoyFmOtpQjjnz43AGuf7+WdMG6P5mFTPZUlZnYZJqqo+LSInYjJF8qK2/9KN8YG72VHV8x5cUvUUkTMxKeTvYRyEu0Tkx6r6P5fGvxmzEDgKc7/1Y667ydaDrcE0uT8FE3VuoQ64JtFBReQuOqkjU9UrEx27zTiPOxGhFof7elVd59LYKVuUUCPQ976IPKip0z9Yg/lMXf1sAUTkSsyc7wPMefklxgH8VEQua5mrJItsV/V8GvO9ekSsqufOjZhmnU2YE+IYTF+eo0TkYYxzMkqTVDRLFU4a0Z8xDa+/h/mSPglMwShhNgHzVfWNTNkYjZOK1heTdnqNqr4jImcBf8WE318RkVLAr6ob0+GcuIWIfBvTJ2aGqt4rIpdiJtinq4v9aOKwowDTB+oE4HPHlusxN/ufqEsy1V2w5xRMVGweRlTmGVW90nGWj8Sk1Tyoqm42uU4aEZmIabh7JWZCMAkzIVuDSRk5DvitZkHvuygH+7eYFN9vY4RyAqp6r7PPN9lem3Svpr7v006J44A1YtSTz8Wc34+qu/2v9mb7ZP1jdaGlkJj6sscx9p6HcQz+i7knnquqrrRzkBSKl4jIvzDpc4djsh9Ox0TNLnJp/JSperaMhWkXtcF53BuTMuzW+DMwNYTTVXVPZ9ssda/Gz9XetCLyXefPyZiMkZaWQ2dgMhgudek4L2L6Tb+gjvJjKhGRd9z4PjkL/U84c6VdMN/ZCRjF7otVdXayx4g6lut9h50FpolqypIKMCVWh4nIEOD5lnPUheNkTNUTVbU/WfaDEW+5P+rxzRhpezArBC9h0iIybmsbu1sWEv4A/Mz524tJWXgH2DvTNnZiuw/T+2g04HW23YhZFT8o+v/rDj9AbtTfJ2DqVS5zHg9Ksy1+53cBJor2jyhbhmXgvckH3gJOcx4XYiIIf4napzzbPnNMg+MHgKejtp2KEV0Y6jwuyQa7o48PDMXUIX6MSUn9OUaxc3/M5Glwpt/bnvzjXIPfTcNxDsIslIFRmB7uwphfRv29oqPnkhi/FPg9sABTS7XJuRb8Hihz6X2Z1eZ3EfChi+/7s5g6vGHOz43Asy6OP7vNY0/bbUmO/5nze7rzu7DlvUrVD/CqC2N8CviiHvsxZQJu2Xioc69cjlG1PR2TNu/KOdnmZzYmVXtWsu89pv1Hy98vR91nD8MsCLlhfwlmXvkwRsk++rl/JDn2bJz5E0bv4fOo5+a4+PnOjv48MdkArn2vOvvxYMkoYmj7OcwDxonIDc7jzcAeTorBJcD3VfXrdNoZD+qcvRgRjOHOKmpYVW/AfIHOk+2NQ7MNDyaV9oKobe9hopQPi8jQqP8vaxCRfCffHRHZQ0yPQVS1WUSGi8ifVPUVTMrLBBEZrGmUxxdTTxQUkeEYIY93MO/rXo4ty9JlSxRNmAbT6wDUrLhdjmlzcYezrdr5nU2f+VZgEVDmpEeipgZqPttFKOqc7Rm1u+X4InIxRkH2EcyC1dmY2onJmJScX+Ge/LalHVQ1DEScrIWU4KTrXY9JJYft6XrJEhGR3cQo0xY4UcWW+nE3hCL+C1QDh6lqhapWYiJzNc5zbtAil98gIgMw9Y/9XRobTFZNb4yoyDPO30n3SoviNRF5XUQuEFOH+zKm/t0t/isid2Oua9/HLMrdl+ygIrJXBz+TMIvryVKOcUBaKHK2uYKqvq+ql2Eaht+NydRxq7ZyGcbJOxOTln2yM3bL38kQXULWR1WfBVCTIlnc7iu6zgOYbLingW+LyNNOmQNsb3ifKPcB00TkXsz87++wLdLtZpbUA5j0+FtE5BbMQsK/XRy/Q2yqZ4YRkSLdroQ2CJMGtUFE9sI4eTdibnDHYKJRT6iLofJUICJ7YOr3PsV8cRT4Gybi85Kq/j6Dtg0DilV1dlQqWo6qBkSkFyZtYwlmMnAyRinxYuDvqro4U3Z3hJieOzdjJit+4GxV/UpML7r/Ylb6f+3s219T2O4j6v3cF5MC8zlGGTWCyZd/XlV/K6bWsERV16fKlnZs82iUgI2YvlfnA/upaR0xGVPTeRAmWv1uumzrjKj3tKUfYznmutAf47i+h0mFO0tVP8ugqTsgIsdionvnqupKEcnBtPI4BzheTfsQr+OYWFKImNq7PYE3aS3J70o9UqrS9UTkSEzUI4LJdrkG0w6oBLMA+nwnL49n/IWq2q7IWGfPdfEYv8BkXByJmUQqJq35pmTHThci8i22p/F+2DKZd3H8ozFzHAFeV6dVVZJjhoH3aV/NeH9VzU9y/Asx5SzR4iu3quqDyYzb5hj5mHnIWZjFvZfUqHC7MfZpmO/T7ar6gogs0SQat0eN+xuMsNgvMen9DZio9BHAt1T1JBeOMUNVJ0Y9/jkms+kU4E1NsmWEiIzDtHWaoylsKeQsQkR/r9Ki6mkdvwwhIoJJgbof0xx8EEbefBXwGuZi8nfgP25cBFNFy8TU+TtHVQPO39/HNJffByMl/23MKttQ4A+ZikiIyGUYR+kYVZ0p23u07YIp6H0cU4tWAbyNUav7G3CsGjGUrENMMf9/MWkCRzrb9gYGOBf0Vk5Pim05EvgnxuEfgInwrQLWa5prOp3P9IyWhQYnsu5VpyZARH6GiUC9jjk/T8GsgL6mLhVwJ4KYlhvNzt9ljoPkU9WQc93oj3Gevo1Zub1HVd9I5+fcgd3R1wI/ppbsb8DVqnqfs90L/BZTNH8CRpnUOn4pRrbXJbVCjciDG+N/pqr7itOnK5X1Ks4CXbUb542IvIGJMD3UshAlRsHyAkxd21FJju/BOBmfOI9zMeldW5IyvPUxdgN+hEnz3BZtUZfqH1ONiNymqtfH2pbAuHMwaYY7ZEeJyEpVHZzM+M44/YD9nIdT1SXxFWfs/2La87yGWZB+3+3ru/M9/RVmrjZJVQe5NO4FmMX/XTCZVCsxmR+3uXHui8h8YFybxdwLML0+i1R1aLLHSAfO/bAvrb+3Kak1bkXb3E/7k54ftjvd5ZgJ0AhMvcFpGOnYH2JSo2ZgwuUZt7kD+yuc3x7n90jMqvIETISvP+bEPgGYg/myZtr2qzHpcROdx70wTW9/0Wa/Sc5nMSHTNnf0/jt/l2BuPvdhmiW3bC9Ps02jgDeAyc7jwzCrfudE7ZO22jPMqmMzcHOb7SMwK6dgxFCOxjQQPtj5vu2Swc/Vg4lsnIuJoDwGlDrPDcbUIu3hXDeuB27DTFCz6XysYHut4flE1XlE/Y+VmbbZ/rj6+f8Ik462xDl/p2D6SKbiWPe4OFa58x1qqfHb7NwbbnPr+okLtYgxxp/pzBf2de5ZkzCT+GTHrcOom7b9qQNqXbR/ejvbkq7xw9TEjerguW+4MP5pLddm53GZG+NGjXcsjt5Aqn+ce8ql6TiWS/b+ATiqne3HYfrxZtzGOP6HKzCtweayvc4ypbWtLT824pcB2qyM98GkmN2BUfiZIyKjMXnKR2JEECZomlUP40FMPdm1GKcJTLPLPwMrVfU3UfuVYHp23aRZkqYqIj/G1EGcjbmZjVZTCxedXlcKFKrqmgya2iFOesyJGPufwkxafoXJo78D4+BeoylM74yyxYd5L28F/quqP3W2X4BxYk5Ql9W3YtjTEskdDEzFpFbd7JyLTwIftTlHx2LEfS5T1ZnpsrM9HBvXYVLyJqtJ3S3CtERZpqp/cfbrg6lN9AK/V/cbN3cZEfkRJqVnKOYcnIFZ9T0XeFxVn+z41ZZUIUapru3NfgsmHfvX6oK6ZyrS9To4znRNMpUrzuNcqKoPuDDO7RhH+BlNwYRLRL5Q1Uluj5tqROSHQEsNW3QZRTFGBOS8FB476c+2bbqhs+1LdUn1sc24KT/nReQWVb0lRWPfo6qXpGLsdo7lyvc21YjIIkypiWvKynEf2zp+6cNJ0yLK6bsYsyq6h5jmsT8HjtDWKYgDNQtTDEVkf8xE+VzMykVfjNx2YYuj0Tb1K50T/za2tjhy4zCF7x+pSZu7GrM6/e0WhzTa5mxGTOPhxzGO90kYp2868CKmnmQM8CtVfSmFNrS8r72ARlWtF9MO4XjgA1W9T0y95+2YGrS0tY9w7Gv5Dg3DTLzuVtVbROQwbdM30HG2fOm2sY292+r5MH24TsFMyv/qPD9Unb5IUamfvTCXlLTfPNripPn+FlNvejBGcXQORnntTIxTcBFQ3x2+Yz0JMf0ew5gIMpg04QLMAsNBqpqsoEPaEJHXVPW4NBxnhaoOcWGcOoxSZRjTUkMw39mSTl8Ye9wWobQrMcIcz2IyHMAcwLVrmbRusN4LUye/NMkxSzER19/RujF5Xaqvw258ttJODauIzFbVCclZ1+6xUuJQtjlGypzLdC3WOMdy5XubakTkXUy2TlIN5xPBNnBPL96WD9mZJF2Iifahqn8SEQVeF5HjVHWGsz3rnD6HMpwG7ZjavTNVtVaMQM1a2EFZMO0ndwvOZPpETBPaj4HficgVqvoXEYkAr4rIKao6vRtNSPcGHlDVZ0TkFUy07XiM+M8FItJXVden0pF13tfTgJuA9SLysqre5Tgu14rINzCrt39Ml0MV5TwdAPQRkQ2qOsVZqJgqIs2q+jtn3201cZoFTcMdu/fCpEn/CFOvME9EKpyV2FIRGa2qC1quI1mWCeDFRPsbMNexOkyk/yOMwuNT2RCV3Ek5qs3Ea7Zsr8dLOLLifMbtXV9ccW7aw02nT0wvrXafwixmJo2quqVk2JYvMO99i3jJj6MPi4mkJY3s2GA9BxcarKup9doiIjcC69QoUR8G7C4i/1HVmiTtTvVn+7mI/AlH9RGTffFFJ/snQzr6ybYnguMWbqmRAun53qYKJ8gDJi3+PRF5mdYLNn9KtQ3W8UsTThrM98Q0Q/0as/o3FrMKfjeAqv5ZjIrT0yIyBghmgyMiponl/moamx/pbN6EkZ7dAhyoRoDiGOAEEbmp7UQ6k/+HiEzApMkdjVHG+iZwk4j8RlX/6jgqqbo5p4qVwKktjgDwgJi0yknANHWEClKUWtTiXPkxaX1XYFRQ33Iiuy2LGMdhlKpein6d2/ZE49h1PEYo6c/AYyLyfVV9TIwk/FwRKVbVn2kGhVA6oRTTWL7UOTcPBL4QIyJwKCZCnVWIUUQdhGlD0+BEBz5V1U9E5E2gl6rOIurmZkk7XhHZVx3lV+e70NIOIeFFuRQ6Na0QI2DyY0wKsZsCJn0xtVTVbQ8JfJLk2NsHEzkFo/oI8J4bmRiqOjzZMeLkNBzFVue4a0TEzc/9aWBvMS067gGex0SmT0hy3FR/tldg+ie2pK+/iXH+XEFMC6S1qtqkqjc6c8O+6mILJBGZrKofOw8ntbPNFVIQoU/L9zZFtHx3Vjg/Oc5P2rCOXxoQUwv3S0zKUx/MhPhR4P8wve2qVPUZADVy9/9SRx0zSwgCF4qRzO2FKQKeJiL3AbsBg6NS+m7MhuhJCyKyh5rU2e9ghGduwtj8O+BREfmObq+Zyso0zyhHa3/MquuHGKWvfYBvichbmFTPYtztM9Muji1HY2pQizDF1OtF5BDMCla+qv5GTGbzSSJytqo+no73Vkxa5y8xEthDgfXAb0SkRFX/JSLjMUIuWYUYBdJ1qvquiISAnzif+50isjtGxfMxVf0os5a2+z1pEcZ5CpPaeTpwjIisxFzrbku/lZY2XAzcL6ZWVDB1wReJUfX7XaKDSoy+rC5G+p8C/oUpL3BTBfYljArgjLZPiMh7bhxARH6PuVY/6my6yplc39DJy7oy/uXAoy0RMjEtX85W1X+4MT6mxZQ6i3ktSpBuElGTtv5N4C4na8QNWfuUfrZq+r/+NOaOifMUcGDU47CzbR8Xj3EXTg/YqIXQbduSIYWLNZCG722qUNVbM22DrfFLMc6NcSNwqqq+KCJDMIpEjzqPv42pt3hSVR93XpM1DkiU0zER07T1c1U9xXluNGbV5duYWpEH1LQPyAr7nXS//wJHqhHIuBajkPpTETkBU1N5iarOzaihcSAih2Naf7yLSek8FZPOcwQmXbge+KeqPp1CG1rOhfHAg5i02fGYusL/qeoq55yY4mwPYOq9PtT09A/MddKFhgD9MO/HJBE5E3gCOF9VH41+Taps6gpiei7egpmM/0ZVG0TkUExE/WFMqmxDBk1sFxE5GchV1f+JyMPARlW9xtl+AKZ+5y5VnZdRQy3bEKeJu7rUTkBEltI63TAaVRf6gjnH6ZYCJrAtLW1iy8RajIT7l+pSqwtJsciIGMGmXTEZM7/DiKI9pqp3uTT+VEyGxs+Bk1V1qYjMUdXxboyfKsQ09P4JMA7Ia9nukmPT0ec6U1X3cGHsAzBO5dWYzJgWSjAKzG4cYyZmseYLohZrVDVV6bDdCicb5ow2CzZPqOqxqT62jfilGFXd7EyE/iAi76vqCjGNRQc4u7yC6XNyqoi8pKp1WTQhbZlQ+4BFGIXRv4nIfap6saouEJGvnahEy6Q7KybUIrIr8CfgOlX9ytk8A5Pi+XvM/3JNN3H6dsOs2H9XVT8QkR9gmhpfpaq3OZFXr6puSOX775wLB2L69P1EVV8XkdMxN5BvisizzjkxsMVREZGnUnk+RJ2jJwMnisj1zndsT0z0CUw6xauYnnfb/pdU2RQPbT6nzRhhhpOBH4nIn1X1fRF5DhNVvQ/TBDejRL3Xgpno/AzYVUwT2uuBO8UI57wIvCgZFHSytI+qbhGRlzCCUG6Ml9J0w6iI4otierCmTMAkxZSxPRuj1OWxvdHXE8exdC11TFVvF5PhUYvJOLlJ3VVsvRC4FLPotVRMiuPDLo6fKh7FpHmehLH/u0CVi+NXidEeeAFARE7FBBHcIAeTreOjdZlLLSZjww1CqvpPl8bqifTWqDpWVa0Wo9SdcmzEL02IqTv6K6ZZ9ADgXFVtdJ4rwvTBy6YUyZZJ3tGYlb7ZqvqwmDzzVzG9R17C1M6dCGzQLKqZEiPP31J0fbSTStIbkyZxMvC8qr6WMQPjxHG6r8JEVZ8Ffud8LhdjJts/VNW30mhPGaaWa5qqnupsOw0T+f0K856H1KhppmURwImGtjj57zjb9sXUYDRh0hAvUtWPs2Fhos13ayJGXfEvmCjZkRgFwJcwan23quqUDJnaLiIyUlUXichAzIrxKEzd8kRM7elF6fz8LV3DzWhQm3Fdr2NLV0QxlYhROv49JltDMO/RDar6hEvj/xGTTne3s+kHGJGl69wY39I+LVFoiVL3FJFpqupKKqaY9P9HMf1owVxbz1fVxR2/qsvHGKrblaI9mPTJpOahkka12e6MiHyBia6ucB4PBZ7VdLSqsffl9CEiR2EaXPdzojP5Lc5fNiIix2LSAH4E3IkpXr4dWIOJOJUCj6jqsxkz0iFqMr0rkI9pyDsM0+4gDFzdNvrQXSamYloNfAfTD+1DdepBReQSYL6qftjZ65M8dsv7OgHwYxx+H6bh6Kuq+n/OfqcD8zQDaX0i8hOMBPg/oyLPOZhI5Bhgsaq+kW67OkNMKuc9GGXc72Kikn/GCG5chGmo+ycnepYVOJG+ARilzveBpRhxpzqM2NMZGHGD3TQL2ktY2kdE7lfV77k8Zts6trMxi0M/c2n8PFVtirUtWxGR/myvzfpMVde5OLYHuASTxQLmPn2fqrpSCymm9u42jD6BOD+qLim2Ovfs32HE7qJTJrPaqReRT1V1fxF5HbOovwZT8rCLy8cpAtAUKCKLyGOYaGUYmIZJ9bxTVf+YxJjdfrEmHYjR/rgHcy8VzAL1Jar6esqP3Q3mvT0KJ/J3O3C4qroqcesmYpQ878H05eqHcfw+x3yhf+WkZBSral2mHago5+QUzER6DkaE5ueYOrNLMVGVSzQDPVOSQURyVDUgJv/7u8BgzITKldXiOG04FbgB+Mw5/g2Yms5PgU/cnkR2FRH5DaZ28/tR2yZgas526CmZDYjIbcAmVf2D8/hOYIiqnuY8LlOjlJsV360228Zg6lq+gXFQ52IWVtaJEdHJmswFS2vEKPGOB1a7ef+R1Nex7dAHrL1t2YiIvK2qR8ba5tKxKoBBalR03RpzEab2br5bY7YZ/yPgZszC18mY1E+Pqt6UiuO5hYichBFaG4wRRCnBZGi84NL4pZj3pSWK/j7wS3WpPtc5xgxVnSgi52IEXX4KfOHG97a7L9akAzE9Mfd3Hn6qaWrP5EnHQSzbUdVXMbUxr4mIx1lFzzgiUihG4hsROQKzsn85RjTkVkwfn+sx+eyXiEipqtZB5uqlnKiO86fs4th7OEYOehCwSFXnYAqMI5iUtG6DmD5zATE1D9/G9E7aCBwgRt4/HTYMwKRMHolJ5ewLVKvJTd8fOEJExjmrzumwR5zfe4nIwSIyDiOWtKeI3OQ8dxDmHBjc8rpMO33tfM8XA5ViUmdR1auAIifdA0wkLdNtUKLrhsY4v73OBPAFTJThU4zY0B+dyb7t05dFiMi/nO9Iy0RyJvAf4EsnBdFNyqL+dqWOTUT6iakhzReRPZ3v/V5i+r0VuHGMVCEieY4j1ktEykWkwvkZxvb0PTeO856IlDjH+gK4V0T+HOt1XWB9qpw+h3xVfRsTiFiupmfpiSk8niuo6kuqukVV56jq4ao6yS2nz+F+TDbFmc5PLaaPopv4ncWgbwAvtM2KSpL22ipke6uFtCGmDVKjkxJfBvws6v6fUqy4SwZQ1eedFb+sqIlz0lD6ATeLSC2mgfT3dXsdTyEmFF0MfAk87uaqUyI4E+bnROQnqvqZiNRjGkX/AHMRO1VNQ/nJwFTgSs1CZcQWoqKW+2JSXj4HFotpMP8EpiZxo4j8Eyh3M1WoHVs8UeemByPs811M+tZ31LRuOFxN64GR6YyiOu/RiZja0i8xCxSfYXo+vSgio4DRwBXq9CzLJGJqNMOO3ftghJxWAW9jlFmPEJPrX4JJpQpC5h3VaBvE1JOeIiLnqxEHOQjYV02/xh9gBKqmuZVaZnGVg1X1UufvC4GvVPUbzsLRq8DjLh3ndxhnMrqOzQ2p+2OBCzALedGNjWsxC6jZzA8wNbADMA5Zy+JPLfA3F49T6tzrLgb+o6o3S8cNruNGTIonmEblTwLP0bpW65lkj+HQ7Cwcfi0i/wesxgiPdBtSFH3eRVW/FfX4VhGZ4fIx7saIns0EPnAcj6Tmds61ZSDOYg3bz/sSsnyxJs38E9hDTCu0azEq3v/B9OtNKdbxyxCpyNdOBDHy+89iJJr/g7kQPKuqnzoOwDwnFeM9oAK41s00kkRx0uCeA/7u3PDmYCSnx2OEc5aIqaP6B6aA9quOR8s8jmNwJOZiMAU4F3gH4yT8Qp0aNSfSVpMKG5yo6VZ1mr87rMGk916HeR8XOXbeLiJnqOqiVNjSiY35mAjk1WqUL/thWkucjMmRLwPy1Ch7ZjpNsh/mgn6bmF58j2MikQdiPt9bMVHq83EWXlR1TYbMbRdn4eR04GLH6ZuAuU5cDdt6P2W8xtfSIdH9YI/G9AHDSct17SCq+riY/lktdWzXu7Q4VYqpb95XU9iqJhWo6p0Ypdsr1KXWBx3gcxZvz8SUN7jFyVF/NwDHRD1WwC3H7yqMQ3Al8CtMi6LvujR2ukhF5lajiBykTu/WlgiRmwdQ1b9i6hNxjrECc31PhvYWaxQTvcz2xZp0EnLmfacCf1fVf4vIRek4sHX8dmKclJP/Aber6hQRWYf50t7rRNL+4Ox6K1AJFKqqG41VkyJqQv8mMBnT1PcsTJ79rcA5ItKImVxfn+1OH4ATqboeuFCN+uRhmBtguMXpS6Uj46z0TcXc7Nc727xq1BlfwqwC/txZ0b8S084hLU5fix3OwwhmMtuSZrxORP4OHKGqAYyKGM5zmY6a1WDEZX6DWeU/U007jvMxq+enq+p3xaTTFjhOdaad1ej0zkLM9WAophH7fZh7xtmqOjXTtlriokZMLdJqzLXyItgWic536yBilH3f0e3S82Ui8g1VfS7JoX+FiRwuFiN1/pSmqQ7GRSLi1OwCiPsN1n+JUQv/SFWnicgIjMpuUqjqhUlbFt9xpjl/bsVEpbsjL6dgzB8CD4lJ0RZMO5ALUnCcbTiOyC8wc6pEx3gIY/e3VPVpETkY2BejDJ9VImsZpk5EbsAs/B7sRL396TiwFXfZiRGRCzEF+VeJWf7dA5NutjcmqvILYDlmlebEbEqVdNL9bsNEKA/E1O+dhlk5PAjojbkRfpDtE1RnEnY2xmn9r6r+1Nl+AcZ5PcHl3Pv2bGiJ7LwGHIbp1RR06kZOxfRAPASj/jXXSfNM6fsqprZxsxNp8rWklDo3ptOBY5y0029gJrRnAk2Z/qzF1EzkqRE+qgD+iEmfvgV43XGmz8OIGZynaVDxioc2Tl9foFZVG0Xkx5iI5Euq+q7zfHQ6sCVLEdMD9K+Yz+8vqvqgs/1YzPfHFcl/SVETcRH5EpiEUaw8CzgFkzb5OPCMOnXm2Uyq3pt0ISIPYXrG1jiPy4E7NElRLxHptB5OVU9JZvxU49yf1qojVuJko/RV1WUuH6cEQF0UzeokFVgwqsy5SYz9maru6/x9MSar5TlMxPhFVf19omP3JJyMoHMwZRIfisgQ4DBVTTbiGhMb8du5WQJc7EwCzsKsAE/EpHAsxgiKBIC/ZZPT53AYpqfdoyJyN/B/mFq476lqq9WqTDsC7dEyyRaj6tSopkdiCDheRC5W1fswNWznYmorU9L7RkSKMXV8szGRqXMw9XFB58I0BZNq+qVjzzbS8L7uAkwXkeFOam+OqgZU9VdihH0+FdO8/gJMDWfGW6M4q3ZHYVbzdsFE/K7F9Ok7CdMGY5WqPuIstgQ6GivdRDl912D+hwIReQ0T6bsUOE5ECtWIGlinrxvgZDsc18721zFRIrdoT9zJjfmFOufaG8AbzqLK8ZiFstsxC3zZTkobrEcjqak12113bDTthtN6AKY33eOYbJOsELrrAk9hFp1bCDvb3OrjdxVGzKUOk4W1F/BTl6JmfTHZHNVtD0vyAizRUasfYBaYqkTkdowYmHX82Jat9DSmRAmMcF9ayias47dzMw1zoboNI+BxJ6ZWbjjmxvQ7IKJZICvfDi192h5Vo3z5EsZpecJJLajXLBabcJy+04CbgPUi8rKq3uU4Dtc6Uaxi4I+aooanjtN3GzAdeBHj/DUDxU66UAmmdccjqTh+LFT1LTHKg1+IyN7OhCNXVZtV9Rci8jWmBvJdVc24WpiI9MbUwjRiJqX9gB85EcvLMA7U9SJyuxr1uoed12XNd0tEzsBMrI/D1Jsepaq3OQ72FcD+IvJOFi4EWdpBRO7C1Ne0i6pe6dKhPheRPwF/dx5fjonMJUsrZ8DJfHgBeEFMy6HuwGvAk84CJZjJ8GspOlYqnCePiJSrajVsaxnhxtyxH6bu9GzMvftljHDcXBfGTgc+NeUFADjzEDcd+u+p6p3OwnwlJiXwYcwiSLK8hGnWPqPtE2JqdZPB40SFPZiswioAVa13FrctgIh8H6OMXYFZ5B6IUaB3vc1LW6zjtxPjTN7+IiL/iXYuxKgMHQT41RH6yOTENCo6dhBGYbQW09/mbRH5uar+BvPlmQLc62ZKhNtE/S9+TA3fFZhVt7dExK9GKVExE+8P1Uj9psQ5cFIRP8OoSG3F1IqUYFISyzD1NPc7x89Iap+qviZG6e1zEdmn5Tx1nPu9MUJEGU/3cpy+H2JWaD/GnIt7YAr0B6jqGid190mMbPNVLSlC2eL0OTRgIr8/BoZh1FLBpFD/DpPCap2+7sPnUX/firlupoKW0oAnMY7mmxjnL1nO6uiJbnQeXo9x9n7oPH4TswiUFM415E4RmayqHzubU1FrdgcwRUSewjiWp2OuEUnhLMy+hmltlYtxAN8TkVtV1U3V01RRJSKn6Pa61lMxURu3aHHiT8Cotc51skSSRlU7FBFR1XOSHL6U7Sq2KiL9VXWtmEb03S2qm0oux9Q+TgVQ1a/F1DGnHFvjZ9mG44wcjZng/UxVU3ETSQgxAgW3YprKX4GJlM3B5I5/iXFUL29xlLIZETkas6rTF5O6sV5EdsUop/5DVX8jIudgUgNfVFW3JNejbdjmyIlp3noC5ib8CCbd90pgIfCkqi51+/hdRUSOxyhfjRDTl+xd4AeqmnFFSTE1mjcAXsyE7hrMZGkU8H3gFSe1swzohRFJmpkhc9vFiazOxjh7fwc+U9UznOd+gFkc+J7a5rvdlnTVlbVM9FJ9nO6EEwkahXGKF6oLNduyvfl2yhvZO9fcw52H76jqPJfGzcX07Dsbc+15AbhfVVe7MX4qcVL5H2V7T8aVwPmqutil8R9wxh6OWUT0Au+p6iQ3xk83ToS+bzbMJ7IBEZmqqvu1XJedecR0Vd091ce2ET8LsM3p2xdTj3Rjpp0+MaIEw1X1dWel6PuYFLSjMAqTnzpRlEmYOo88Vf0qm9LmoomK9I3HONYfA0OAs0Xkf85qz5GYldUHMavCIeDDFNkSEZGRwFpMjcV6jECKOk7K3zDnwpNuHz8RVPVVEblcjFrrFuASVX0u05+3c/yQiLyOaStRiWmB8UPgt5i62XOdKPr3gcM1C5Rx22EMcI6qniwixwGTROQATDr1BcC3rdPX7UnX9+RlIKWOSHdCjELzQ5h+aQIMFpHvquoHSQ4930l3HyCtxToEcx13bQLpRJuqgDwAERmiqiuSGVNE/oNpv/QKcKuqzkne0vThOHj7O/OTVLTougizCLtEVRucFNvuqnraEqG3Tt923heRn2H6HR4NXIYpuUk5NuJn2Ybj/FWqKTrN2ITacfqeA/6gqg+KUcv6JzAPszr4fcfJ+wawNNuiJx0hIgdi/o+fOA7t6ZiJ9TJMyuJKESloSWFK5WfgRNB+hbnpTgK+hVHvPB54X1UfEJHibEijjEZEjgDKVPWZLHD6BmNqU+5T1U1ilGZ/h2nEWoqZJN2Kcar2Apar6tuZsrczxLRuuA34l6rOEZHbnKf6YL6H8zNnncUN0hEZco6Tlshid0FEvsAsqix0Hu+GqWVLOnIjRoDrdYzaaStUdXmy4zvHOAWTwTAA0y5nKDBfVcclOW4EqHceRl/HWxzXkmTGTzVi2izcjFG7Bngf+KWqJtUAPWr8ycAMNbVx52HuIXe69blaMouTtnsxRu1UMN/j+9Ixp7GOnyWrEJGxmPSJW1T1eTFiJ4WYCMovgENU9Uvnong3pll7d3H8yjDO6zRVPdXZdhpGXesrTIpdSI3cv6tOjZhecbkYJ3M3TJTvdOCbzu+j1dT8neVsu0azrJl4NJl2+hwbfo2Jir6CSfXchHEEKzHtLw7AKJz9TqN6j2WD7Y4d38M4qK+p6nwR+SUwSKNk2iWqjYal+yEidWyfVBdgajghhZNrEblM3etR1+0RkVlto2/tbUvyGDmY6zq4lEoaNfZMTD36W05K2uGYNjRpaTadrYhRZJyDieaCEV/ZQ1W/6dL4szApnrtjsknuw/SCPdSN8S2ZQ4yy71xVHZ2J49tUT0u2UYG5eD7vPH4VU3v2L+e5B8QUmX8buCGbnb6o9M4JGAdgLka6d5aI/E1V/09Vn3UuAvNUtbnltS47faOBpzGiLVWYJugPO7aciWkmXCdGJOBJEXlPHVGfbCXDkb4WZ+hmjJM3AZPG+TWmJsPv/L0S+K6zzzbHL4OR9LYO5wxMG5SxIrIZ+APwoogcq9t7C2atMq4lNqpanK5jiRHf2lVV/yFG7KjI1vMARpjqPkz9NJgWPZ93sn+XEJFDgf/gfippC0Eno8Ejpjb8XRH5i0tjd2d2UdVvRT2+VURmuDh+yJk/nIppqfVvEdmpne2egrO4v9CNlOlEsI6fJatQ1Y9E5EQRWYLpJfixqv7ZefqnzoV1C6bAfEq2RE/aI+qifQPwGTDY+XsSpgfd/ar6PVX9X6psEJFhwP+AP6nqU862KoyilB8Yp6pbReQQ4Ccickk2R/oyjZNadbqTNveJiNyDET5ZCQQxAggnAqNV9SQR+SoFtR9dJvp7IiLfxdQeblLV7znR4LswjeZHAAeLyBvqkDmrLd0FEbkZo7I7CqNs68c4OpMzaVeW8EPM9baldcaHgJsR0T9heqW1SiXF3GfcoMapY/sAeFRENrA9RXNnplFEDlLVj2BbaqabvWTrROQGTCTxYCf7yc7Zew7lwFwxyurbvk+qukPattvYk8iSdagR8vg+JtJ3DICI5Klqk6o+0WbfrJ2YOhPqKzAKnhdiJkbVavoi7g/MEKOWNl9T1yrhcOBtZ7XQgykWH4ZJpz0NOFVEghiH9Bbr9MWkABgJfFNE7sdEUk/FRGzfcBYmCoHJIjJBVWdnztQdEZFLMRGHnwIfOg7hf4Fvici+mMWW57P5e2XJSk4D9sT0BEWN8Fbaoo3ZjKo2i8jDwMPq9DRzGX+L0+cc7ysx9fpucSrGobkGc+0oxbT+2dn5IfCQU+snwGaMEJZbnIUpHbhQje7CIZh7i6Vn8ItMHdg6fpasRFXfdqJlX4nIAaq6sTvUG0nrfnceYBEm3e9s4DtqWjcc7qTLjEzD/7MEuFhME9izMJGePTCFxM2OXfMx7TtezeYIajagqktE5CeYmpd7MO0Z6oGbRWStqs4WkQuBClVdlElbwajvYSJ79SJSCRwMfAM4A9MI+OmoRZXPMJFpi6WrBJwMh5ao8k4/QXXEG27GpFN7nG1h4C5VddNx+iKVqaSq2hKNiIjIy5jryU5/j1DT/HwPESlxHrvaP9hx9t4FzhGRRzCKmH9x8xiW9CMiecClmAXk2cC/0z2v9aTzYBZLV1DVVzA3zbkiUp7NTp+I7CIifdtE7tZghBWuA36oqovEtGz4U5qcPoBpwFMYxcYSTIrRZExNyPuYYvEfW6cvflQ1oKot0ehdMeqd5cBNzjmwOUucvr44556IFKnqJkyN528xgkKnqWmifJmzmmyxJMp/ReRuoMzJ1ngLuDfDNmWaazDX2n1UtUJVK4D9MNkA17h4nEsxomFXOj/z2N4sPmFEZH8ReU9EnhGRPUVkDkbMZL2Yli87NSJyleP01WHu6dNF5BgXxt1NRG4WkQWYFPwVGCHGw1X1rmTHt2SchzDZX7MxKup3pNsAq+ppyXrEyOTXq+p7mbalPURkKPAFcLKqTnG2eZ0C3hMxUZbhmKbjV2LaOaS10byIVKjq5qjHhwG/wUR+1lqHLzGcKNp44GqMMzVWVZdl0qYWnNTeczAy4EuBvwE/wbSY6OXUdp6JSfv8lhXisCSDmF5U26TJVfXNDJuUUUTkS4xa8sY223sDb6gLLS8kheqAIvI58DNMauc9wPGq+qkYsbDH3bC/OyMiM1V1Dyeb5lLgRkw6b1ItU8S0ufgQuKhlAVFElqjqiKSNtmQcEZmtqhOcv33AZ8meM13Fpnpash51mslncURqEEYls0REfgfcpKpBMQ1X+2CaoB+C+b5d7qR5pvV/aXH6nNqPozH95n5ma/qSw4mivY9pxjoxG5w+EdkV8KjqQhF5FCOGdDym6f1tzkLFyyKyEpNu8l3r9FmSRVXfFJGpOPOKtotNOyH+tk4fgKpWuVWDp6lVB/Sp6hsAIvJLVf3UOeYCk8W609PyJpwA/EdNk3s33phvYlTL3xWR14Anoo5l6f5sa7WiqqFMfJes42fpNmSb0+eIF3gwIfvfYKIrVzhOXz9gCvALVf0S+DL6tZn4X5zJxr6Y3nM3tjjUluRoqet0aj4yukDhRCAXAhtF5FZMO4Z7MKv2I0XkB6p6mYiMx1z/N6rqqkzYauk5iMgPMJHkJky7GMGkue/MUYpAgs91lVSpA0aXLbRVq8yqe3GG+EJE3sBk89zgzAeSFmlT1eeA55w62VMx2SR9ROSfwLMtzril27KHiLTUgwqQ7zxOWW/VtthUT4slAZyL/G0YFbsXMWkeuwH/xaR0lgB7qer9GTOyHRznr9IpHM/WCKolCUTkCEyN1VWYHoPlwFbMZLPSee5BVW3KmJGWHoWIfA0c0F6Ea2fFEXJpr+2BAHmq6krUT0wfvx1Q1feTHLfFfsGIgjW0PIWL9ndXZLtK9hI1St0VwCBVnZWCY5VjyjLOUtUj3R7fsnNhHT+LJUFE5AJMD7fXgbcxzt4tmMbYT7Wk3rRR+rRYUo5Tb/VXjIJrX4wK6bcxEd+1wGRV3ZI5Cy09CScl7Zuq2hBzZ4srZIM64M6MmL59MxzF5PMwtdR3quryDJtmsXSKdfwsli4S7ciJyLmYHP/XMHLaEzECLguBJ23tlCVTOMJCfwb2V9XNzqqxHyjIhlpES89BRPbENG6fimkTA4CqXtnhiyxJISJPYuqFPsTU8C5X1asya9XOg4jMwiys7Q48CNyHUcluNwJrsWQLtsbPYukCTnpkRERGYiInjwPrgYsw+dmPiMjfMHV0T2bQVMtOjqq+7CjEfSqmF+amTNtk6bHcDbyDiTzZ7Ib0MDZKHfDf2B6c6Sakqiqm3/DfVPXfInJRpo2yWGJhHT+LpQs4F/rjgV8BrwCTgG9haqeOFxG/qj4gIpeqal0mbbVYnP6MOcBbIjLJphxbUoRfVa/NtBE7GRlXB9zJqRORG4DzgYOdmj87p7ZkPbaBu8USAxEZICLDxTAKo+B5JlCLcfj8qvok8CpwnIgMsE6fJVtQ1eeBg63TZ0khr4rIJSLSX0QqWn4ybVQPZw8RqXV+6oDdW/6OUg20pI6zMGnNF6rqOuAgoDCzJlkssbE1fhZLJzjNap/GiLa8CvQHTgLmYaJ+Z6vqYhGZrKofi0hfVV2fMYMtFoslzYhIe7XMaptOW3oyTm3rORjFzaXAM6p6V2atslg6xzp+FksHiMgw4CXgz6r6b2dbGfA5RiRjnKpuFZFDgJ9gGmTbhugWi8VisfRARGQ34GznZyOmlv9Hqjo0o4ZZLHFi85Etlo45HHjbKdpu6dkzDHgUOA04VUSCwA3ALdbps1gsOyNOf9AfAoc4m94D7lbVYIcvsli6JwswSqonqeoiABG5JrMmWSzxYx0/i6VjlgAXi8ixmHz+fIx88+uY3P6zgfnAzxwRDdsQ3WKx7Iz8E5MF8Q/n8fnOtoszZpHFkhq+iemJ+q7Tv/IJTFN7i6VbYFM9LZYOEJEC4BLgAmARcCcwBxP1Oxe4qaVhsXX6LBbLzoqIzFTVPWJts1h6CiJSCJyKWQA+AvgP8KyqvpFRwyyWGFhVT4ulA1S1QVX/Ahyhqqer6oeqWg2UAgcAZeJoaFunz2Kx7MSERWSXlgciMgIIZ9AeiyWlqGq9qj6mqicDg4AvgeszbJbFEhMb8bNY4sSpYzka+B0mvfPlDJtksVgsGUdEjgQewKTHg8mKuFBV382YURaLxWLZARvxs1jiwHH69gWuBW60Tp/FYtnZEZF9RKSfqr4N7Ao8A0SAN4CZGTXOYrFYLDtgI34WS5w4zl+lqq6zNX0Wi2VnR0SmA0ep6manrc0TwBUYBeQxqnp6Ju2zWCwWS2us42exWCwWi6XLRAu4iMjfgSpVvcV5PENVJ2bQPIvFYrG0waZ6WiwWi8ViSQSviLS0hToSeCfqOdsuymKxWLIMe2G2WCwWi8WSCI8D74vIRqAR09gaERkJbMmkYRaLxWLZEZvqabFYLBaLJSFEZH+gP/CGqtY723YDilR1ekaNs1gsFksrrONnsVgsFovFYrFYLD0cW+NnsVgsFovFYrFYLD0c6/hZLBaLxWKxWCwWSw/HOn4Wi8VisVgsFovF0sOxjp/FYrFYLBaLxWKx9HCs42exWCwWi8VisVgsPRzr+FksFovFYrFYLBZLD8c6fhaLxWKxWCwWi8XSw7GOn8VisVgsFovFYrH0cKzjZ7FYLBaLxWKxWCw9HOv4WSwWi8VisVgsFksPxzp+FovFYrFYLBaLxdLDsY6fxWKxWCwWi8VisfRwrONnsVgsFovFYrFYLD0c6/hZLBaLxWKxWCwWSw/HOn4Wi8VisVgsFovF0sOxjp/FYrFYLBaLxWKx9HCs42exWCwWi8VisVgsPRzr+FksFovFYrFYLBZLD8c6fhaLxWKxWCwWi8XSw7GOn8VisVgsFovFYrH0cKzjZ7FYLBaLxWKxWCw9HOv4WSwWi8VisVgsFksPxzp+FovFYrFYLBaLxdLDsY6fxWKxWCwWi8VisfRwrONnsVgsFovFYrFYLD0c6/hZLBaLxWKxWCwWSw/Hl2kD4qFXr146bNiwTJthsVgslhTzxRdfbFTV3pm2o7tg748Wi8Wy85DsPbJbOH7Dhg3j888/z7QZFovFYkkxIrI80zZ0J+z90WKxWHYekr1H2lRPi8VisVgsFovFYunhWMfPYrFYLBaLxWKxWHo41vGzWCwWi8VisVgslh6OdfwsFovFYrFYLBaLpYdjHT+LxWKxWCwWi8Vi6eFYx89isVgsFovFYrFYejjW8bNYLBaLxWKxWCyWHo51/CwWi8VisVgsFoulh2MdP4vFYrFYLBaLxWLp4VjHz2KxWCwWi8VisVh6ONbxs1gsFovFYrFYLJYejnX8LBaLxWKxWCwWi6WHYx0/i8VisVgsFovFYunhWMfPYrFYLBaLxWKxWHo41vGzWCwWi8VisVgslh6OdfwsFovFYrFYLBaLpYdjHT+LxWKxWCwWi8Vi6eFYx89isVgsFovFYrFYejgpdfxE5CoRmSMic0XkamdbhYi8KSJfO7/LU2mDxWKxWCzZhr0/WiwWiyXd+FI1sIiMB74P7AsEgNdE5CXgEuBtVf29iPwU+ClwfarscJvw0tmEP30ZQgG8ex6Bd/xBmTYpLtYtfYmlM+4kHGzA6y8gJ683/Xb5BgN3OzPhMVWVeYseZumq18jPq2Ti6B9SWT7WRat3ZMa6N/hwxeMIwmHDvsP4Poe5Nva9y17lyVXvE9Iw+1eM4abR51LgzXVtfDcJhsNcOX0Ks7dU7/CcXzz8eMzunDBgcNLHeWvtRu6Yv5StofC2bYPzc7lp910ZXVqU9PjpYtPWCK/OCrKhThndz8sx4334vJLUmKsWh/jywyCR7W8NeYVw+Km55OQnvqamYWXzxyHqvgoRaYJIAFDw5EHRSC+Vh/nx5iZnO0BkdTPBt7agdWG8uxfgO7gEkeTHtcQmm++Pq6ob+O0r81mwro79h1cwe/UW5q6pBWD/EZV4RPhyZTU+j4dvTBzIDSeMJs/vTaeJ7rB1A7xxI6yeDsMmw9G/hLzSTFuVMKrKv+f8m5eXvEyfgj5cueeVjOs1jg9WfcB9s++jKdTEuWPO5dSRp2ba1LiJNDSw8geX0jhzJp6iQrx9+hJYsMA8WVAATU0QiWzbXwoL6f+rX1F6wvEZsrhrzHp3FZ+9uIRgcxiNKKqtnxeh1bZ9Tx7GPieOSK+Rlh6HaNszza2BRc4AjlPVi5zHvwCagYuAw1R1rYj0B95T1VGdjbX33nvr559/nhI7u4LWVBF44EaiZ3r+06/DM3RMBq2KTXPjRj574cR2nxt9wK/pPeTohMb9etkzfDbrtm2Pc/wlnHb0C/h8+QmNF4sVW+bw92kXo5hzVvBw9f4P079oZNJjv7r+c25d8Eirbcf2mcStY85PeuxU8JMZU/lk44ZO93lq8pH0zy9I+Bi1wSAnvfsF7V0hCr0enj10Evm+7J/wqSp/ebOZDbXb/5NDdvNx/O7+hMes2Rjh/eeb232usEQ46oy8hMfe9HGQ6k9CHT5fNMZLv5NyEh4fQAMRmv60Bhq2T5r8J5Xj27c4qXHdQES+UNW9M21HKsnm++NJd33InNW1ce9/wYHDuOWUca4dP208dAosfX/74wlnwrfuzZw9SfLkgif59dRfb3tcllvGv4/99/+zd9bhkVxX3n4LmsXM0oyGycOG8YzHzI6dOLYTxw6jN7jBL5xsssmGNxvYZBPbSeyAHceJmdkeDzMLRjMjppbUXPD90QPSiLuqpZbmvs/jx9O3qk4dNdS95957fodbH7kVzTz9PPndFb9jdfHqyXBx3Bx53/sJvv76+C6SJKqfehJnRUVynLKJtoZe/vbdTeO+7pb/t4r8isl/TgsmD6t9ZDK3eu4G1kqSlCtJkhe4BigHCk3TbDpxTjNQmEQfbMU4sndA0Adg1O2cJG/GTmvdY8Me62wa50O1H42tA6+Nxnpo79qdsL3R2N/+xqmgD8DE4GDHBltsv9K+a1Dba517bbGdDHZ2d456zvMtjZbu8XxT55BBH0BAN9jr77Nkf6LoDpoDgj6AA836MGePjZZjw18f6LE2mRasHdm30Y6PBeNYdEDQB6AfDFm2KxgzKdk/tvVGxhX0Abx4YOQJqJREiwwM+gAOPT05vtjEK8dfGfC6O9LNPw79Y0DQN9R5qUxo27bxX2SaBF57zX5nbObQ5paErtvz6nGbPRGcbSQt8DNNcx/wfeBp4ElgO6CfcY4JQ48tJUn6kCRJmyVJ2tzW1pYsN8eFlFsyRFvpJHgyPjILlg97zJuR+LaBzPSB10qSQkZa8mbZitIG+1ros2fbQ7Vv8Gdb5U3dOYkC1+irqgsysyzdY0n28LOKElDhS87Krt2kuyU8ZyyQFWRYe/SlZw1/vZr4QiIAzryRfRvt+FiQ89RBT3+5wNoqomDspGr/mO11kJc2vu3tswun4OqD6oKcM/qOgtTeuTMa1VnVA16rksqKwhWjnpfKOIqKErrONcv6LqBkU1CZ2O+mZHaWvY4IzjqSKu5imubvTNNcYZrmOqALOAi0nNjCwon/DzldaJrmb0zTXGma5sr8/Pxkujlm5LLZKKuuAlkBJOR5q5EXnDfZbo1KRt5icssuHtSeU3IhJbPfnrDdBbPuoDAvvtqsKl5WLPo0Xk/ygqVFBRezquQGJGRkSeGCsrczN/d8W2y/o3w9C9JPB61ZDh9fnnObLbaTwbeWrMAtD7/Ncl1+Ecuy8yzdY2a6lyuLB9uQgE/NqyLfPTUCBVWReNsKJ94T7hZnSly92Fp6c3GlTFn10I/PlZdYi/xy1zpwFQ2da6dmSuRfZjGyBKQMFcc12eCM30ee4UJdm2HZrmDspGL/qCoyP7h5Cbm++I+lIseDo18urNep4HGc/t7PzPPxlWunaMD0ll9AenH839kz4JofTq4/Fnn/4vezuii+hdOrevnC6i9wWeVlvHfhe1FlFVmSuXbmtVw7c+i0j1Sk5Cc/RvL2S1dQR39uZ7zlBryrViXRK3uoXl5AxcKccV2TV5HGnFWJBcMCwUmSluMHIElSgWmarZIkVRCf2TwP+DLQ0S95Pcc0zc+PZCdVcvxOYkaCoOtI3qk10xkNdRINt+NOK8XQwzjdubbYDYXbcai+pOX2nUkg6keSJLwO+weqLeEugnqEKm/hlBC62OvvIqhFOR4IEjZ0ijxelmTnku20T5SmOxrjaCBE1DRJUxUqvJ4pkdt3JppuEohApte+zzUaMelojtHnN8jIUSkoVWz73mi9JpLLROsB2WWCKaGmS7Z+L82oARETKT11Ps+zIccPUrt/jGoG7X0RSrI8GIbJzmPduFSZ+SWZRDSdFn8YVZEpyZoaq/7DomvQ2wSZZXEljWlAW7CNNGcann79cW+0F83QyHZPPZFY0zQJ79uHo6QENSuLwM5d6O3tZFxyMZGGBsKHa5BcTmRVxT1vHmrm1BLoCfgjhHpj5Jb4OLixmd7uMLnFPtJzPWQWeKnb2YauGZTNziY9d4r/3gS2YLWPTHbg9wqQC8SAz5im+ZwkSbnA34AK4Ahwi2maIyYspVrgJxAIBILkcBYFfqJ/FAgEAsG4sNpHJq2cA4BpmmuHaOsALk3mfQUCgUAgSGVE/ygQCASCiSapOX4CgUAgEAgEAoFAIJh8ROAnEAgEAoFAIBAIBNMcEfgJBAKBQCAQCAQCwTRHBH4CgUAgEAgEAoFAMM0RgZ9AIBgTRhIVgAWTg2mYQ/5bIDgrEc84wQQynmeueD4L7CKpqp4CgWDqE9J0vr+3lhdbOihwufjk/CrW5E+9elCC05iGSeyJLvQtAXDGC7qbLTGkbBXH9Tko1e7JdlEgmDg2/Ape+j5oUVj9QbjsG9Omrp8g9YiGNJ77wz7qtreRnuvmonfOpWLB0HWVj+zu4OW/HKC3M8LMpflccuc8nG4xdBckjljxEwgEI/LHuuM819yBbkJTOMI3dx4ioGmT7ZbAAvq2APqbfaCZEDQxm2NggtmpEX2gHTMmZpcFZwmN2+DJL0KoC2IBeO2nsPfhyfZKMI3Z+EgdtdvaME3oaQ/z9P/tIRbVB50XDWs8/X+76WkPYxomNVtb2fx4/cQ7LJhWiMBPIBCMyB5/34DXId2gti80Sd4I7MA4Fhn+YNDA7IxNnDMCwWRybPPY2gQCm2ip9w94HQlqdLcEB53X1RQkGh4YELbU9STVN8H0RwR+AoFgRJZmZwx4naYqzErzTpI3AjuQK0fYypkmI+U6Js4ZgWAyqTgfOGNbZ+UFk+KK4OygeFbWgNfuNAc5Rb5B5+WU+nB5B27rLJmdNeg8gWA8iMBPIBCMyDurSrihrACfqjAzzct/nDMHj6pMtlsCCyjneFHXZYBXhiwFqdIFLgmp2IHztnwkVeQ3Cc4SihbBDT+HzArw5cMlX4F51062V4JpzKrrZjDv/CIcboW88jSu/shiFMfg4bjDqXD1hxeTW5qG060wf00xK66qnASPBdMJyZwCKlYrV640N28WWy8EAoFguiNJ0hbTNFdOth9TBdE/CgQCwdmD1T5SSAMJBNOErmiEh48doTcW5eqScmanZ062SwKBYIrywoFWnt/XyqyCNG5dVY7bIVb5BQKBYKojAj+BYBoQ0XU+sulVjofiCeL/OHaEX61aw7yMrMl1TCAQTDn+tvkon39w56nXrx5u57d3ikVYgUAgmOqIHD+BYBqwqbPtVNAHEDMNHm1smESPBALBVOW+DUcGvH5mbwutPeFJ8kYgEAgEdiECP4FgGuBVBi/e+xShzCgQCMaPzzXweeJQJFxC0EkgEAimPCLwEwimAcuyc1mdk3/qda7TxVvLqybPIYFAMGX5+CWzcamnhwcfXDuTTK+YSBIIBIKpjsjxEwimAZIk8cNl57K5s42eWIwL8grxquLnLRAIxs/51bm8/PmLefVQO7MK0jinPGuyXRIIBAKBDYiRoUAwTZAlidW5BZPthsBGYt0Gkiqhpom6eoKJpTDDzdtWlE22GwLBmIg1N4Np4igunmxXBIKURgR+AoFAkGIYMZPmf0YJ1hkgQeYyhfxLnZPtlkAgEKQUpmHQ9KUv4f/XI2CaZFxzDSX/9X0kseNFIBgSkeMnEAgEKUbPLj0e9AGY4N+qEzqmT65TAoFAkGL0Pf88/n/+C0wTgJ7HH6f36acn2SuBIHURgZ9AIBCkGLEuY4g2cxI8EQgEgtQleuTIoLZIff3EOyIQTBFE4CcQCAQphm/2QOl8SQXvDCGnLxAIBP1JW78e+m/rVBTSL7lk0vwRCFIdsQlaIBAIUgxvhULh9Q7823RkB2SfpwqBF4FAIDgDV3U15b/6FZ13/x7TMMl5z7txz5s32W4JBCmLCPwEAoEgBUmfp5I+TzyiBQKBYCTS1l5I2toLJ9sNgWBKIEYVAsEUZY+/k+/u2U5nNMqqnDy+tmg5qix2b08kpmlSs1uj5ahBWpbEvGUOXB6xMieY+kQ0nV+8UMPGug7OKcvi45fO5mBLL795qZaYbvDuC6pYNyd/st0UCKYdWkxnyxNHaDzUTdHMDFZcXYXTLYbrAnsQ3ySBYAoS1jXu2vw62gkls+dbm4jt2sx/nrN6kj07uzi4XWP/Vg2A9ibwtxusu8E9yV4JBNb55iN7uf/NBgA21HZyoKWXDbUdhGNx4aEXD7bx8MfWsLgsczLdFAimHa/89RB7X20EoPFQNz3tYa784KJJ9kowXRDLAwLBFOSN9tZTQd9JNnW0T5I3Zy/H6waWWOhqMwn1DVbkFAimGo/tbBrw+qUDbaeCPgDdMHlyT9OZlwkEAosc3tI64HXNtjYMQ6g6C+xBBH4CwRSkwusb1JbhcEyCJ2c33jMEV1QHONxiq6dg6lOW7RnwOsfnHOIc70S5IxCcNaTnDtw1kpbtQpZFvyKwBxH4CQRTkOr0TC7MKzz1WpEkvrTgnEn06OxkwUoH7hNjX1mBRec6UFXRQQumPl+7bgGZnvhkks+p8L23LuaGc0pOHb9wVh43LSudLPcEgmnL2ltm4/LGM7EcboV1t82ZZI8E0wnJNFN/+XjlypXm5s2bJ9sNgSDlqO3r5WBPNxcXFuNSRMruZGAYJv4OE1+6hFOs9llGkqQtpmmunGw/pgrJ7B9DUZ39zT3MKkgj3R0PAuvbA8R0g9mF6Um5p0AggFhUp+N4HznFPiHsIhiA1T5SfJtSBK2vmZ69D+LMnUta9eVJu49paHS3bAZZIatgBZIkFn2nKpphsKOrncZQEMM0WJSVS4Uvzfb7GKbJ9q4eorrBytxM25VDuyI6OzojzEx3UJE2tbar9nQa9PWY5BXLOF3JC/pM0yR8zMCIgbdSRlJEgClIHuGYziuH2ukNx/A6FWbmxZ8rumHy0sE23qjp4N3nV3L+rLxJ9lRwNhPavh2tsxPf+ecjezyjX5Ci9HaGaanroaAqneY6P4c2tjDvvGKqlxdMtmuCaYgI/FKAQO3ztL3wZSC++tqz60+U3Hiv7ffRYgF2PvchAv7DAGTkLmHxxb9AVgbnbghSm95YjNtefw5/LDag/WOzF/DOymrb7qMZJp/Zso9tXT0AVPk8/HL1QtId9jw6tnaE+eLmdiInEtc/Ni+LW2dMjZWEfZtjHNwRV/RUHXDB1S6y8+2fSDENk8YHo4SOxIU1HNkSZbe7UETZCEESON4d4uZfvU6TP3yqLd2l8vv3ruKu+7bS2hsB4Mk9zdy4rISf3rpsslwVnMUc/9zn6XnkEQDUggIq778fZ9nU23p8eEsrz/xuzyDxlvqdHZTMzuSmf18xSZ4JpitiuScF6Nz4M04GfQDRjgOEW/fYfp/W+idOBX0APR076Tj+ku33ESSfB4/WDgr6AO6uPUBY12y7z+vtXaeCPoD6QIjHG9tss/+7g/5TQR/A3Yf8RPTUV8WMhEwO7Tz9PmsxOLh98OdhB8F641TQBxDrMunZad9nLBD05/ev1g0I+gB6Ixrf+NeeU0HfSR7e1ogu1AYFE0x4375TQR+A1tpK5732T5ZPBBserhlWsbPxkJ+e9tAEeySY7ojALwUwtcE/bD1o3+D6JFrUP6gtFhncJkh9OiORIdvDum5r4NQTHRxgDNWWsP3YQF/Dukk09eM+tJjJmenR0aE/EssYocGDAl2MBQRJojs49ASGPzR0e0ybAj9YwbRC7+4eU9tUIBwYecIwEhSTfAJ7EYFfCuCrvnLAa0n14Ktab/t98iuuQFZOywSrzgzyyi62/T6C5PPW8hkMtdFvbX4RmU77tu5eWJBNZr9tnU5Z4vJi+/J6ri0bWJZiXaGHdEfqP5Z8GTJ5xQP9rJijJOVe3moFpb9qvgLpC5JzL4Hg5hVlDKUcf+f5lYPay3M8uJ3iuyiYWLwrV+KsrDzdIMtkvfWmyXPIAgvWlAx7zOlRySu3P29fcHYjVD1ThK4t/0eg5knUtEJyL/wyjozhHwZWCHQfpqnmISRJpXj2zXjTK5JyH0Hy2dHVwf8c2ktbJESBy8P6whLeVlaFS7F3IHY8GOaho81EdIMbygqZkzG4hqAVnmkMsKk9zMw0BzdVpuFSUj/wA4hFTWr3agR6TIorFIqrkjcAjvkN/Ft1jJhJxhIVd9HUeI8SQah6jo9k9I8b6zr5y8YGjneHyE1z8ZalJVy5sIgDTT3cdf9WmnvCLCvP5jd3rsDjFFIBgolHa2+n849/QutoJ/OGG/CtXj3ZLiWEaZjsfa2RpsN+sou91GxtpbslRE6Jj+v+7RzcvqkleCZIPlb7SBH4CQQCgSBlEIHf+BD9o0AgEJw9iHIOgrOKF+v/yBvH/o5L8XL5zA+wuPCSyXZpUtEMg7u2vM4efxcQ37t9WVEpn5u/BI+o65d0Wo/p7N0cIxqG8tkK85arSJJQ2xRMffoiGt/81x5eONBGcaabmG7QFYxywzkluFSFh7YeI9vn5HNXzmX93GkgO7/zAXj5B6BH4LyPwbkfnmyPBNOYgD/Cy38+SFNNN0UzM7noHXPxZbkI+CO8dP8Bmmv9A9oFArsQI0PBlGF364s8fvh/Tr2+b/dX+Fz638j1lk2iV5PLD/btPBX0ARjA083HyXQ4+eTcRZPn2FlAJGSy8dkouh5/fXC7hjdNonKueKwKpj7/+fg+HthyDID2vtPKRb99pe7Uvxv9YT78xy289sVLyEubwoPTlj3w0Ac5pa79xOchbzZUn90Ti4Lk8fwf9tOwpwOAuh3taDGDGz6xlOfv3UfD3s5T7XrM4PpPLJ1ETwXTjembKCKYdhzu3DTgtWHq1HZtnSRvUoNNnUOrv27pbJ9gT84+OluNU0HfSdqOC4VDwfTg9ZqOMZ0X0Qw213eNfmIqU/cK/UsqAVArSh0JksexA50DX+/vGvD/M9sFArsQgZ9gylCaPndwW8a8SfAkdZidnjlk+5yModsF9pGZI3GmtGpmntjmKZgeLCzJGNN5sjT2c1OW4nPG1iYQ2ER+efoZr+PqnXkVA9vPfC0QWEUEfoIpw4qSazm39EYUScWt+Lh29scpSZ8z2W5NKl9duJQ858AtVgsysvjorPmT5NHZgzddZukaBw4XSBKUzlSYuUBs8xRMD75y7QJWV+UAkONzkuFWkSS4bF4B1y4uRpElMj0O/uPGxZTneEexluJUng8XfxkcPlBccO5HYOHULA8gmBpcfMc8ckvjCtk5JT4uuTPeZ19yxzxySvq133F2T24L7EeoegqmHDE9jCypKLIYZJ/EH40QM0y8qopXFe/LRGIYJoYBqipW++xAqHqOj2T3j4GIhtepYJgQ0XS8J8o3hKI6DkVCnSLlV8aEFgXTAId79HMFAhuIhjWc7sF99nDtAoFQ9ZxG6OFuAjVPAeCrvgrFbX27nmkadBx/ia7mTYR66nG4s6lY9AF8GTMs255IQlof25ufIqZHWFp0BRku+4qIT1W6oxGeaT5OUyiIQ5aJmQZ1vb1Up2fw/uq5tqh6vt7WxcGeAAVuF22RCBVeD+sKc1BsUq6M6iYvNAdpC+usK/RQkTb1ahbJsoQ8jca+AgGAaZrc+3o9z+xtYWael/rOILVtASpyvHzysjlU56fxz+3Hcaoyb1laSqZn6v12B6E6J9sDwRmYhkHvM88Sra3Bt24dnoULJ9slW2mp66Fmayu6ZjBjST7uNJXjB7tx+xxEghoZ+W5mLS9Ank4TLIJJRaz4pQh6uJvGh+9ED7QCoPgKKLnpjygua8HfoU3fpbn2n2e0yiy74h7SsgfnzKUiUT3Mz968k7bgEQC8jkw+ee4fyHYXTbJnk4c/GuW9b75EayQ85PF8l5sH1lyKaiEi+dXBI9xf3zSo/fLiPL62eFbCdvvz7xtb2dwRVwx0yvCT1QUsyp7C6oACy4gVv/GRrP7xw3/czFN7WoY9nuZS6YtoAFTmennsE2tJc4m5ZIG9NH75y/j//lD8hSxT+tOfkHHFFZPrlE1sebKeDQ/XjnrezGX5XP3hxRPgkWAqYLWPFFMIKUKg5ulTQR+AHmglUPOMJZuxiJ/mukeGOGJwZM/vLdmeSPa2vXwq6AMIxvxsOj7U33X28GzL8WGDPoC2SHhYxc+xEDUMHmxoHvreTe20haMJ2z7J4Z7oqaAvfk94sL7Xsl2BQGCNcEzn6b3DB33AqaAP4EhHkCd3D/28EAgSRevsxP+Ph083GAadd98zWe7YzrZnGsZ0Xu22NvxtwSR7IzhbEIFfqpC0os9D251aRaYH+zq1/J8cZIvvkTTMdweS93UVn6tAkBqM95cofrkC2xmqP5hGfcRIfeygc6fR3y2YXETglyL4qq9A8Z3euqikFeGrtradweHKpGjmDYMPSDIVC95nyfZEsjB/LYW+0zmJPkc2q0qun0SPJp/Li0opdHuGPV7o8rAiO/E8SKcs8/bKobfSXlmSR57Lei7MrAwn5+afFlFwyhI3V6ZZtisQCKzhdihctah4xHMy+glPzMjzcdWis3frvSA5qNnZZL3tbacbZJnc90+dsctoLLuyYkznzVpRQEbe8P29QDAeRI5fCqFH/ARqnwXAN/NyFJf12kimadLZ+CrdLZsJ9tTjcGVRsegDeNPLLdueSMJagB0tzxLTw5xTeBnprtzJdmnS6YlFea6lkeYT4i6aYVDT18vs9AzunDEbtw3iLm+2d3OwJ0Cxx0VLOEK5z8OF+dmWVxNPohkmLzWHaAtrrC30UuoTOUJnOyLHb3wks3+8/80jPLWnhVkFPurb+zjUGmBGno+PXzqbGbk+Ht3ZhEORuf6cYtLd00DcRZBymIZB34svEqmpIW3dOtxzp4Y2wVg5frBroLhLuoPjB7pwpzmIBDQy8jzMXJaPLIsVP0Ecq32kCPzGgGnomNEQxDQktwfJMXXFJ0zTRIv24LAoGnMmmh4GE1Q1+TLYoVgvLtWLLClJv1eqE9Y1OiJhFCTcqkqW077vpmmatISjZDoUDMCXxDIRMcM8UY5i6mxCiIQMkMDpkohF4/9PBkbUBAlkh/32Tc0E3URypc77LgK/8ZGs/rE7GKW9N0xeupssrxNNNwhEdWQJXKpCVNPxh6Kke5xkTMWgL9gJnmzQo6DHwHVit4GuQSwANqhqCwQjYRomkZCGJIHDrWKaJnrUwDBM3D4HWkynpy2Ey+fAm+EU2z0FgCjnkHT0A5vRnr4XoqFTbdL883Bc/T4kKXUGS2Ohp2M3BzZ8nXDfMXxZs5l3wXfxpo9tq8FIbN/3K/bX/BnT1JlVdRMrF/17Uh5QfdFO/rTzy9R2byXdmcvb5n+JBflrbb/PVMA0Tf5jzzaeaj4+oL3al85vVq/FpVgLind09vC5bfsJ6captjX52Xxt8Sy8qr0B98NH+vjtwW4Cmsm6Ig9fXpKDK4Wlq2NRk1cejdDbFZ80k+R46a/0LImVlzjJyLbHd9M0aXs2Rs9OHUmGrFUquRfaN8COvdaD9oIfNBNlsRfHW3KRRC3Cs56DLb28755NHOs63eeVZLmJxHQ6AjEAVFlCM05PGl8wM4dfvWslmd4pEAC27IUH3wtt+8GbFw/ytCgsfjvMuhSe/BIE22HmxfD2u+PBoUBgM8cPdvHs3Xvp64oLnDmcMiagReN9rsMtEwuf7n9dXoUbPrmMgkrrO8EEZzepO7pKAcxIEO3J3w8I+gDMfRswDky9racH3/wW4b5jAAS6D1Gz5b8s22xu38yeQ/egGxEMU+Ng3QMcbXrest2heOLwr6jt3gpAb7SDv+75JlF9eGXL6cwrbc2Dgj6AmkAvv63Zb9n+V3ceHBD0AbzW1sV9dY2WbfenKajxs71d9GkmJvBSc4i/1/fZeg+72bs5dirog3jQB9DbbbLj1Zht9+nbr9OzXQcDTA263tAIHdNtsW20xtCe6oaoCQboO4LoW1L7fRdMDF96aNeAoA+gsTt8KugDBgR9AK/XdvLfzx+aEP8s88gn4kEfxAO8WAhMHXb+BR7+WLwNoPYFePH7k+enYNpiGOaAoA8gFjVOBX3AgKAPIBLUeer/9kyYj4Lpiwj8RsDsao3PBA51rHVsMrypgq6FCfUeGdDW13XQst0u/2Abnf7kDAAaewfeK6T10hWyNxCZKhzq7Rn22B5/lyXbmmHSFdWGPHaoN2DJ9pnU9sYwzmg71Gtf8JQMulrP9Pg0/s7hj42XSOvgbfhDtSWC0Tz4uTZUm+DsY2/j8M+WZFw34TTtHP6Yccazp3lXcn0RnJWE+2IDgr6x0tMWQtft62MEZyci8BsBKa8UPOlDHpMrF06wN9ZQVDcZeUsGtGUXrbZstyhvJWcKeRfnW7c7FHNyB9rNcheR76tMyr1SnZW5wyt2ri8YWY1vNFRZotw7dK7m6lx7814WZTtxKwO/PytzUzuHtqRq+K2u+aX2PVK9VWfYksBTYY99pcoFZ/wZcnXy83MFqc+FsxNTA147J3EV4Qml+uLhj50pqFa9PqmuCM5OvBlOcsvGr2BdVJ2BksJpEIKpgfgGjYCkOnC89ZNQWAWyEq8f4/SgXHwbcuX8yXZv3Mw979vklq7D6cmnoPIqqpd/zrLN7Mw5rFn+TbLSZ5GRVsW553yJwrzlNng7mMtmfIA15beQ5SpkVs4q3nvOD89agZdzsnL55OyFuPrlmcrAVUVl3FIx07L9n66YT6XPjQwoEmQ7VO6cUcpNFfZKtmc6Fb67PI8FmU6KPQrvm53BNWU+W+9hN7OXqJRWy0gyyDJ4fODyQOlMhaVrrJe5OIm3UiH/cgeOHAlnvkThdQ5cefY8sqUMFec78pFKnEg5KuoVWaiLUvt9F0wM33vrYi5fUMhJEUFJgkvm5nPejBzSXAppLpXiTDcOOV6FzKXKfHDtDD641vpzZ0K44X9g4VshvQTKzoWChZAzEy7/Ntz5MFSugcxyOP/fYM2nJttbwTTlqg8tomJBDqpLQXXK5Jb5yCn2oTplHC6FvAofcr+c64LKNK78wKJJ9FgwXUiqqqckSZ8GPgCYwC7gvUAx8BcgF9gC3GGa5oh7jCZb1VMgEAgEE8PZouop+keBQCAQjJeUVfWUJKkU+ASwwDTNkCRJfwNuA64BfmKa5l8kSfo18H7gV8nyQwDRcBeNB/9MsPco0VA7wZ5aFNXLjCV3UVB11WS7N+m81L6T59t2UOrO5dayi8h0TI2Vjwcbavnb0To6I2HChoEE+BSVBZlZ3FhWxToLWz41w+Sfx1rY1d2LT1UIaTqFHhe3VBST7bJXua8vZvBgfS9HAxprCj1cUuy1xe7+Jp0dR3WyPBJr5qikJancQrIwTZOeXTqhIwauQonM5eqAGWC7iL3sjwu7eBUc12ejlNi31VY/0Ia+rw0py426uhxpKqg+TgCp3j8+u7eFnz9/iPr2AGHNwOdU+Oj6at6zZgZ/eOMI2492s7oqm3eeW4ki6osJkky0vp7OP92HEQ6RfeuteBYvRvf76bz3DwS3bgVdx714MTnvvhNHYeFkuzsqpmHy+j9q2PdaI1pMR1ZlVFUmq9BLX3eESCCG6lSIhjQUh8Kam6uZf37JZLs9ZgxDZ8czT3B8/15KZs/lnCuuRUliOSjB+Ejait+Jjm0DcA7QAzwM/By4DygyTVOTJOl84BumaV45ki0xo5k4pmmw9al3EfTXDHl84bqfklN8/gR7lTo80bKZb+7/06nXC9Ir+P3yz0yiR2Pj7w11/OTg7hHP+drCZVxRXJaQ/Z/ur+fvDc2D2mf4PNxzwRLbCrgDfPLNVrZ3nk50//eF2dxQMf78h/7sPq5z3xunF0oKMyQ+cbnLVr+TTcerMbreOC2ykzZfoeg6+7aSAsRe9KM97z/dIIPrS6XILutbqPXdLcQe3nvqtVScjuv9o09Sng0rfqncPz65u4mP/GnrkMeWV2SyteH09+UDF87gK9ctsO3eAsGZaF1d1F51Nbo//r2THA6qHnyQ5q99jdCOHQPOdZSVUf34Y0hOe5+TdvPCn/az99XxCdO97QvLKZqRlRyHbOaFe3/L1sf/eer1ksuu4vIP/tskejS9sNpHJi3HzzTN48APgQagCfAT37rSbZrmydHMMaA0WT4IoK9z37BBH8CxffdOoDepx2PNbw54vbe3gZpA0yR5M3YePFY36jmPNR5N2P7jx1uHbK8LhNjnt0/2vymoDQj6AB4/Zl05dGv9QFXSlh6TY53J29aeDHp3Dyzd0Ldfx4jZ+zdoZ5ZwMEDfZM/nq+8Y+Dsym3oxWkTJCEjt/vHBLceGPdY/6AN4YIRzBQI76Hv++VNBH4AZi9H5xz8MCvoAYseOEdi4aSLdS4iDbw6eVB2N1x48nARPksOeF58d+Pql50hmWplgfCQt8JMkKRt4CzADKAF8wJj3FUqS9CFJkjZLkrS5ra0tSV5Of1RX1ojHHa7ciXEkRclyDFxZkpHIUO3ZaphMMh2jz2hmWZj1zHIOvyUvc4Rj48WnSpy5ezHLaf2x5BtiW6cvtcVCB6Gc8TWUXWC3lpHkHvxeS1k2fb5nbuuUQPKIrZ6Q2v1jjm/458aZv9XcEc4VCOxAyc4Z1KYWFIIy9MNQzclOtkuWcXjGv+0xLXvqqC57Mgaq43rSM5Cm0G6b6U4yVT0vA+pM02wzTTMGPASsAbIkSTr5rS8DBlehBkzT/I1pmitN01yZn5+fRDenN560Ukpm3zLkMUl2MnP5pyfYo9TiPRWXk6mezum7vfwS8l32lixIBp+ZuwhlhAdphqry7hmzE7b/0dkVqEPYf2t5IWXDlHpIhAynwp2zTncSaarEe2Zbf//XzVVJ7+fm+dUKuWlTS8Q4Z62DU09KCXLXOZBszqdyXJs9sBpLjoK6yJ6JD/XCqgHBn3JeOVLGFIu+k0fK9o8fuaiaDPfggakswb9dOhv1xHfQqch84ep5tt5bIDiTtHVr8a1Zc+q1a/Zsct/zbnI/8IFB52a+5QbcC1J/6/HaW8fXN8uKxPrbp85vbd0733sqp09WFNa9632T7JGgP8nM8TsX+D2wCggB9wCbgXXA3/slr+80TfOXI9kSOX7WCXQfIhJsQXFk0Fr/OC5vEWXzbkdWxAx8UI+wtfswJe4cZvqs1cCbSAKxGP84doTeWJSd3R2AxIX5hVT40lmRk4fXYjJ1ezjKvp4+Zvi8NARDFLidzEpPjvBNQ1+MowGNpTkufA57ArSoZlLbZpDpkSjOmlpB30n0oEnouIGrQMKRmZy/wQjq6G/2IuWqqEus5VaeiRnVMI50I2V5kPPH9t05S3L8Urp/DEV1ntjdxLHOIEc6QhRmuvjI+moy3A6a/CF2HfOztCKLgvSpswohmNoEt27FDIfxrl6NdKJvixw+TKSmFiRwlJTiWTR16isHuiNsfeoIuqbj8sUn9UpnZ9HbGaGl3k/JrEyO7e/Cnebkgptm2T7pl2z6ujppPnyQwupZpOdMkRqfUwSrfWSyyzl8E7gV0IBtxKWrS4nLVeecaHuXaZqRYY0gAj87MPQIvZ37cbhziIU7SMuag+JI/S2NyaYh2EpIjzI3PTERlLHSEu6jPRJkXkYeimTvAP5wr5+HGupwSjLFPh8X5hdS6rVnAG+YJvt7AmQ7VYo9bg71BHApMhU+jy32Ia5eeaAnRoZDpsRrv/JXRDNp6jYoypRxO+zpPE3DpKvdxO0FQwctBlk21dgbcB/dJNxs4MiUUdOS1/GbEQOjOYZc4EDy2Pt36HWdGP4wco4XOceDlDbyqt/ZEPjB1Ogfdx/343UqzMxPozsY5c3aDjI8TlZVZaMqMhtrO3j1cDs3LC1hVkF6UnwQCKYrnU0BDN2gpy1Ew94OohEdSYbSOdmYBmQXetFiBr0dEeacW4jDOX3qFpumSUvtYdxp6WQV2lsfeLqT0oGfXYjAzxp9nfvZ/fKniEW6TrUpDh/z13yf7MJVk+jZ5GGaJt/Y/yeeat0CwOKMGfxsyUfwKvZvRft93VZ+X7cVA5NSTwb/vfQaij32DJK+tH0jr7S3DGq/rqScLy5Yasl2RyTKpzbvoz4QQgLyXA7aIjEALinK5euLZ1lWyfRHdT6zsY3DvXG7N1ak8emF9uVo1LTq/OmNKOEYOBW49VwnC0qsdZ6hgMnrT0To8w98dmbnS5x/lQuH054ALdpl0Pi3KFqPCTLkrlPJXmX/Cr1eFyb65zYIm+CQcL4tF2WB9Ukh0zSJ/HojdAQHtKtXzkZdNfxEy9kS+NlFMvrHvojGnb97k60N3fF7VGaztaEL48RXvjDDRbpb5XDraSGmqxcV8at3rbDVD4FgOmIYJk//djc128aenyvJcP0nllI+b3DO41Qj1NfLA9/+Mm31tQCcc/k1XPaBj02yV1OHlFX1FKQOdTt/MSDoA9BjAWq3/XRyHEoBNnUfPBX0AezqqeORpg2236cl3Hcq6AM4HurhD0e222K7ORQcMugDeLTxKAd7/EMeGyt/qW+iPhAC4hWmTwZ9AM83d7Cpw5p9gL8f6TsV9AE83NDHQf+I9arHxaM7YoRPmI/q8Mj22MgXjIHDO2ODgj6ArjaT+v3aEFckRudrWjzoAzCg4xUNPWj/RF3sya540AcQM4k+3mWLApu+o2lQ0AegPVeDGbHvfRLYz182NpwK+gA2Hzkd9AG09EQGBH0AT+xuZsfRbgQCwcgc2dU+rqAPwDTghT/uT5JHE8u2J/51KugD2PHM47TUTh3V0qmOCPzOAiLBoYODSHD8ksLThdZI96C25jOCYztojwRPBX0naQnbI2nfEg5ZOj4areERd5jRMsrxMd0jpA9qawnbFxR0nxEo9YRMDItBTTAw/PWhEY6Nl1NB30l00JIQ+Jk9Z3wGvToM/ljGb7dtcNAHgGZgBqwH4ILk0dgdTvA6a88cgeBsoK8rsb4zMk2em70d7YPaetqHLiElsB8R+J0F5FdcPq72s4HzcxYM2NYpI3Fp/lLb7zMvI49Sz0Bp48sKq22xvSgrB8cwWy19qsoKiwnVlxQNf71Hkbkgz/qWzEuKB+YKZjpkVuTaJxixpHzgts5FZYrl7allM4ffKlo6w74cjLR5A2058yScufbn+SlnqHjK8z1IZ+r2J2J31dAl6KSSdOQc+3JEBfZz7ZJi+mtJKGMQlnCpMhfOFiIOAsFoVC3JQ02gbFHFoulRfmvu+WsHvPakZ1C5eOnkOHMWInL8zgJM06Dx4F/paHwFQwsjK06yCldRNu8OZOXsrcN0oPcY9x17gbAe4a0lazgvZ35S7tMU6uUPR7bTEu7jssJqrimeY5vtur4ePr11A+3R+AyiIknMT8/iiwvPocpnPY/wueZ2nmxsJ9fl4JysDF5p68Qly9xWVczcDHsEZF5uDvL4sQCZTpl3zMygKs2+PDZNN3n5oEZdm0F5jsz6eSpOG4KaYzUaRw/rKAqcfIRWzVMpLLc3+d6/QyNwUMeRJZF9viMpAi+mZqK91oNRF0EudaKuy0By2TMnqB9oI/bMYQjGwOtAmZ2LuqYKKW34547I8RsfyeofXzzQyn1vNuB1Ktx+bgUPb2/k+X2teJ0KH75oJqVZXj7zt+10BaNUZHv59R0rmF0oBF4EgrHQUtfD9uca8LeE6GzuQ48NHIurDhmnR0XXDACqFudx6XvmT5t6eIc2vcHu55/GnZbO6re8ndyy8sl2acogxF0EAoFAMG0Qgd/4EP2jQCAQnD1Y7SPt104XWEILtNK1+VfEOmvwlJ1H1vIPIFlclTMMjcNbvk9r/ZOYRlw4Q1Y8LL74l2Tkpn6x04mgLtDM/9Y/TnO4i0vzl/Ku8ktSfmbt70fr+NWhfYQNHYn4ap9XUbiupJIPzZqHKie+ahPRDf7v8FE2d/qZne7jI7PLyXFNndXhqGby9O4YtW0GpdkyVy52kOay7/M8Xq+x87UY0QhIEigKOJzg8khUzFGZMd/6ozVQo9O1ScPUTWRFQo+YeKsUctaoyDasWgoEQ2GaJr94/jC/fLGGkKbjkGVKs91keZ30hmK09EYIRDScisxnrpjDh9bZs3VdIBiO8IEDtP3sv9FaW/EsPYdoXT1GIED2O24j8y1vmWz3xo0W1Xnu3n3U7+5Ai+qclAFQHBK6bkJ8kQ9Jhhnn5HHxu+bj9omaywJ7EIFfitH67BeJtu8FINp5ENPQyDn3E5Zs1u/8FS21/xrQZughdjz3fi546wso6tldhFczdD6569enBF/29x3FKavcWnbR5Do2Aod6/fzkwO5Tr01AM016NI37G2pwqwrvmzk3Yfu/OHiEfxyNiwId7g3SGArzP6umTnHcR7bH2FwfVyhp8ut0B03ev86eUh3BPoPNz51OsjdN0Ix4Lb9QwKS7PYbDCWXViT9eI60GTf+IcloXKP6PaGs8EMy/ZOoE4YKpxZ/ebOCHzxw89TqqG9S1B4GBYj1hzeC7j+9nblEGF83Jn2AvBWcLRjhMw/vej97RAUB49+l+L7R9O0puHmkXrpks9xLixfsOcHjLYDGTM7d7mgbUbmtH1/Zy3V3nTJR7gmmOEHdJIbRg+6mg7yTBhlcs220/+uzQB0yD3o7dQx87i9jfd3SQyucrHXsmx5kx8o9j9SMef6XVmmLrq60DFU53dPXSF5s6Evz7mgbKUh5uNYjp9mxrbzoyuuRlc4Nh6R6BWh2GcTdw2JptgWAknt07tAr0cDyxqylJnggEENq+41TQNxR9zz8/gd7YQ92uwaqWI3FkVwemkfppWYKpgQj8UgjFlYnszhrQ5sissGzXk1E17DF32vCFlM8WSty5OKSBohxV3oJJ8mZsLMwYWVGz0qKwS7lv4CpwvsuJR7VXuCSZ5KcNfLRleyVUm552mdmjG0rPsrYV05kz/D2cOWKbpyB5zMz3jev8OYX2iDwJBEPhrKyI76Uf7viMGRPojT1k5o1P1Tgj34M0BmVdgWAsiMAvhZAUB7lrvojsjA/a1YxyclZb2+YJMGv5Z1FdgwOFoplvw+0rsmx/qpPjTOdTs27CLce3z81LK+e9lVdMslcjc21pBfPSs4Y8VuT28OFZ8yzZ/8TcKoo98a2RGQ6Vzy2YgZLiOY/9uX6pgyxv3F+fE25a4bAtZzOvRKGoYvhHZ16xzMyF1nbR+2bLpC/qN9g58U9HlkTeepHrIUged108ixl5g4M/dYiB55yCNN55buVEuCU4S3EUF1Pwuc8iueL9kVpQcCoQTFu/nqy33zyZ7iXEpe+ej8M9tolU1SlzyR3W+nOBoD9C1TMFMbQweqAVNaMMSbInNjdNk76u/YSDrUQCTRTNuBbVKaS3+xPQwnTF+ijzTJ1aVEcCvRzu7aHA5catqjgkmUpfmi1BjmGaHAuGKXS7cClTb47IME06+sz4ap9if9Aa7DPo6zZwekBRJJwuCV0Db7p975XWF38+yy7Qek0c2VLKiw5ZRah6jo9k9Y91bX0cbO1lbmE6qiKTl+aisTtEQbqLFw+2Ma8onVkFog8RTAx6by+634+zrAytqwszHMZRXDzZbiWMYZi01vfg8iq0HwuAZFJYlYmhm7TU9WDoBrklPnLL0lHs2q4imBYIVc9pRKR9P9GOA7iLltmyxRPA0CO0NTxLb+deMgtW4nTnoEf9aLE+2wI/3YhRd/RxOrr3Ul58MSUF59lid6LxqW58U0jopjkUZGd3J1HD4Onm47SGQzhkmQtyC7hjxmwUC6qeADu7erm75ihHAiHKvG4uKsyh1Ovh3Lws21f/OiM6G9pCFHlUluW4bAluZEkiPz15QZKswLFag3DIZMY8maIK1bagLNJqEGqM5/kpLgl3mUykySDWJeGdIVve9mM0RzGORZErXcj5yV1BNBq6MTqCKNU5SBlT5/d1tjMjP42IZvD5B3cSiup8+vLZhDWTh7cfpzDDTYZ7mqw8N+2Axu1QuQbyZk22N4IhMEIh+l5+hfDeveidnfjWXkjGVVdNtlvWME2CPVF2vdRKb2eEvs4QsYiBw62QU+Rl2RUVbHy0jrajfcxcms+Ft8xGmSITsLoWo3bLJnQtRvWKc3G4h37utx89QuPB/ZTMnkteRdXEOnkWI1b8UgT/zj/Rtel/4i8khfyLv4VvxqWWbOqxINueeTeh3oZBxyTZwcK1PyS7yFqQputRHn/pXfT0HTnVNrP8es5f9hVLdgUjs6G9lS/u2Ig2zO83z+ni4XWJb1f93eGj3FN7fMhjK3Iy+MkK+wrJHvBH+eSbrYROiK9cVerlS0tybbGdLHr9Bi/8PUL/t790psTKi60HNt1bNNqfjw1slDgl9uIulym91Znw+6+92Uvssa5Tdh035aAuTU6eVuzpQ+gbj8VfqDKO25agVI2cnypW/MZHsvrHf2w7xqf/umPY4x6Hwp8/dB5Ly7Nsv/eE8frP4ekTfZUkw9v+Dxa9bXJ9EgxA7+6m7pZbiTUMHMd4V6+m8g/3TpJX1jAMk4d/tJWmGv+Yr3G4ZN7/o3Upv/qnRaP8+aufo7W+BoDMwiJu/86P8aRnDDhv53NP8cxv/ycuiy1JXP7Bu1hy6RQP5icIq31kan+DzhJMQ6N7++/7Neh0b/2dZbttR58dMuiL3zNGw967Ld/jWMsrA4I+gNqjjxIKj0+1SjA+7q07OGzQB9AejfBCS2PC9v9yZHilvi2dPWzv6knY9pn8ubbnVNAH8OTxIMcDqa0guufNGGe+/cdrTQK91hQ3TdOk87XYEAdO/zN81CB0JLH7mKZJ7IV+gw0TtBfGPvgY170CUfRN/SYPNAP9tSPDXyBIKb7/xP4Rj4diOr9+sWaCvEkCugYv/dfp16YBL35v8vwRDEn3ww8PCvoAghs3Etqd2urbw3F0b+e4gj6AWMTg4EZrat0TwaFNb5wK+gD8Lc3seXGwsvwbD9zHqU7UNHn9gfsnysWzHhH4pQCmoWPq0YFtWsiyXV0Lj3jcsOEe2pA2TDQ9Ytm2YHjC+uglBXpi0VHPGQ59FOnokG5fSYHwEGUWwjbaTwaaNvT7o1uNV00wR/9oMYaIDcdqnzNrRUWTtOtDMzgzOjZjY/jjBClBRBv9Nxicyp+nacCZfWQ0OPS5gknDDA8/jjFDU/Pz0qKJ/W6iodSeEAXQIoPHfrExtMVG+JwF9iICvxRAVl2kz7l+QFv6AutKVfkVl6I6hs/jK571dsv3KC++CKdj4BJ+Qc4y0n2llm0Lhuet5VUjHndJMteVJq62t64gZ9hj5V43q3IzE7Z9JjdWpA14EC3JdlGdkdoFyucuG5wenZUHGWMo9TASkiyRsWRktTdHVjzPL1H76qqB2zrV1ckR6JAy3chzBgolqStF+ZipwnsuqBrxuATccd4UVvRUnbD83QPbVn9wcnwRDEvm9dcjpw9+RjnKy/GsWDEJHlmnclEu6bnjTAuQYP4FJclxyEZmr74AX/bp8YPT42XBuosHnbf0ymtHfC1IHiLHL0UwDZ1AzZNE2vfjKVmFt3KdLXbDgWaO7ruHQPchMnKX4PTkEQk2k1OyxnJ+30lC4Xa27/sV/t4aigsuYOHsO1EVIeKQbN7saOXVtmZawyEO9Pjp02Ioksz8jCy+tGAphZ7x1Qo6k7trjvHgkSYCmo5bllmWk87C7AyuLy0g02mvsMPurggvNgcp8qhcU+bDm+J5DACtxzV2vxkjFoHSmQrzljtQHdbzHk3TpG+vTvCojhmTUDMk3KUS4eMmsgsyl6go3sTvY5om+s4gxrEISpUbZaHXss/D3kvT0Xc0Y3YEkWfnocwYOb8PRI7feElm/3jv63X85NlDaLrB1YuKyEt3s/u4n6IMN7esKmdV1fATRFMCw4Cdf4XGbTBjHcy/brI9EgxBtKGBrj//heC2bZiBAN7Vq8n/1CdRhggIpwrBnig7nj9KzdYWQr0xYhH9ZLobnnQHM5cVcHhLK5GARlaBm+s+vpSMXGt9+kTR29nOrueextA1Fq6/jOyiwQGraZoceOMVGg/so2TOPOZesG7aK1bbhdU+UgR+AoFAIEgZROA3PkT/KBAIBGcPopzDNKBjw0/p3fsAmDpqeikFV/wIZ1aVLbbbjj7H/je+BubAveGSpFI2711ULfmoJfu6EWPTzh9S0/AIcHLfuoTHncfyhZ+kqvTyhG0bps6jB3/GpsZHcCoedEMjqPmRJZW15e/g2jn/Zsl3gIN9x/jPg3/lcF8j5+XM5//NuY1sZ3IUDu2mT4vy1pefJWgMzhfIUB38dc0lpDsS2zLZGAzzrR2H2NMbGHSsOs3Dj1bMJ9eV2tsxk4kWM9n8QpSWowPzoCQJyqoVzrnQgWKxdmD7K1G6N+pgEN+UbwASZJyjUHC59ffeaIsRe7gDozGKPMON88YcpAzRJZztHGrp5bbfvEFHYOyJpLPzffzktmUsKrVvC/iE8sJ34c3/jddoUZwQ6oJ518H1PwPX1OgPzgbCBw7Q9NWvEdm3D98FF1D83e+g5ubS9t//Ted99yO7XOR9/N/Ifrv1NJaJ4Pk/7mXfa2MXbJmxNI9rPrIkiR4JzgZSfz/VNCdQ/yK9e/5yStFB6z1O67NfsMV2NNTB/te/PCjoAzBNjaP77qGz6Q1L99hf82dqGh7mdNAHYBIKt/H61q8TCLUkbHvDsX/w6tG/EtGD9EY7CGpxFSzD1Hip4Y/sbn3RiuuYpsmX997Lvt6jxEydVzp289Oaf1iyOZF8YvMbQwZ9AD1ajM9v35iw7e/tqR0y6AOo6QvxX3tqE7Y9HTiwTRsU9EFcy+ToYZ2aXdaS8CMdOt0bTgR9cPr/JvRs1+k7YF1UI/pAO8bRKOhgHA4TfbTLsk3B1Oc992wcV9AHcKgtwMfu24oxiihUSrL3X/DS9yHcDcEO6G2Ki77sfhBe/M/J9k7Qj+Of/gzhnTsxYzH6XnqJlu98h54nn6L9l7/C8PvRWltp/trXCR84ONmujsrhLa3jCvoA6ra3s+eVocssCQRjRQR+k0ykZeegNs1/BGMURc6x0Nu1jwE68EPQ0z58naax0NY52P+TmKZOR9fuhG3X+4e3DVDfbc33zlgfR0NtA9p29tRZsjmRHAn2jXi8pjfxkgu7unstHZ/utDePHHh1tlhTJQ0cGvn60DFrgZ8ZNTCbBw7ujQahxHu2E47pHO9KrO9p6AzS2jsFv0NH3xz+WIO1iVGBfWhdXURrB044BrduI7Rt68ATTZPQtm0T6FliHD/YmdB1dTtEqSyBNUTgN8m4ChYNalMzKpBV6+Io6dnziWuvDU9G7mJL98jLGez/SSRJITdrYcK2qzJH9q1ylOOjkeNIo8w9UHVwcUaVJZsTSYV35C1IM88omDoeFmaNbHvRKMenO7mFIytvZhdYe7T6Zo98vads5PuPhuSUkYoGCvTIZWfv1l1BHLdDoTQrsb6nLNtDQbrLZo8mgLJVwx8rP3fi/BCMiJKVhXPGjAFtnqVL8SxdOuhcz7LBbalGyezRha6GonJxrs2eCM42ROA3yfhmXEL6greDFB/IKWlFFFz2fVtsOz25zD3/26ds90eSFMrm3UFOyRpL95g/853MLL+eMwNMtzOX85d9HZ+3KGHb55bexAVlN+OQXaQ5svGocQUvGYW15e9kceElVlxHkiT+Y8G7mZNWhoLMBTkL+FT1TZZsTiQ/X3E+bnnon3CaovL9pSMMaEbhSwurmZc2tNpjpc/D5xdUJ2x7OjB3mUpB6dDvfVm1wqzF1nLlXLkKWauV0z+rk7eSIGOJQtpca4EfgPPmXKRSJ0ggz3ThvH6KKzQKbOH371lFtnd8qr0z87z84p3LkeUpqMq38EZY+1lwpoM7C3wFIKuw8CZY/6XJ9k5wAkmSKP3xj3AvWACyjG/tWoq+/P9Iv+oqcj/0IWSfDyUvj6JvfB333LmT7e6ozFpRwNxzC8d1TdXiXBZfJEriCKwhVD0FAoFAkDIIVc/xIfpHgUAgOHsQqp6AGQqj7zwA4SjygmrkfPtnrs2eTvQ9r4Fpoiy6ECnDvnvEeo7Rd+gx9FAnSDKu3Dn4Zl2DrE6tbTN9wUZqGx5DkhWqK67H6863xW5bsIFHDvyEkNbLJVXvYX7+hbbYPcm+3gaead1GZ7SXNNXNmtyFnJ8z39Z7JIMdXR387MBumkJBIoaBZhoYgEOS+PzcJVxdVpGwbc0w+PXBBv55rBXTNFmek057JIY/pnNJUS4fml2OY5jVxjH73xnhtdYQJR4FVZY40hdjZZ6bc/NTv1aRppkc2q7RelwnPVsi0GMS6DHJK5ZZfpHT8spH55sxAgd0JBc4cyU8ZfFVPjvrHJkxE317H0ZbDCQJSQZlgRe53Npzx4xqaFsbMWo6kXxO1BUlmH1RjGN+5LJMlPkFNv0FgmSgGyb/3H6cPY09dIeiPL2nhZhmkJ/mpCDDTVQ3CUU0WvsixHSDuUUZfOemRSwsmWKKnj2NsO1PYOiw7HbIOvG8bD8MO/4MTh8svxN8eSPbESSdSE0NnX+6j2h9Pc6ZM5CcTmSvF8XnQ2ttw7f2QtLWWNu9NNFs+Odhtj97FF2LL74oqkTZvByiYY3Oxj5iYQOHS8YwQY/qpOe6uf7jS8nMT17dVbuJhkPsfuFZejvamHv+WoqqZwOgRaPseek5upobmbXqPMrmJZ4SNFloHSECW1qQVBnfqiKU9KmTKjHlV/xMXSf2+4cwO7vjDaqC4103IBfa97A2A36i934DQicELTxpOO/8BlJalmXbsZ5jND58J2YsOKDdU76Gwit+ZNn+RBEItfD4i+8iGosLirhduVx38Z9xOa0NBoKxHr798tXo/ZRJ71j8n5a3eZ5kc9dBPrnz1+gMFNP47Ky3cXPpWlvukQx2dXfy0c2vjXjO1xYu44rixLaFfHLTHrZ2DS/gck5WOv+zOvGH9YtNQb6xvWNI6aFPLcjipsrULsz70j/DdLcP/ez0ZcBlb088eG1+LELf3sHiLlnnquStG98WvJGI/LEV49AZQh4SOG/PR5mTmP+maRK9Zyvm8eGFhZQLK3GsnznscbHiNz7sXvH7f//Yxf1vNozrGkmCf911IYvLpkjwF+iAX54Hgdb4a082fPR1iPTBb9ZD7ISicVYlfGwDOKfOYHu6Ed6/n7pbboVodMTziv/j22TdfPMEeWWNZ+7ew8E3E1A8l+DO71xAeo51DYiJ4P6vfpamg/sBkGSZm7/8bSoWncM/vv9Narduip8kSVz/6S8y59ypE7hrnWFa/nsrZjgusqZkOin89Apk98SspVntI6d8jp9Rf/x00Aeg6eg7Dth6D/3AptNBH0CoD/1A4lL5/ek79PigoA8gdPQ1Yr2NttxjIqg/9uSpoA8gHOmgofE5y3ZfrP/jgKAP4Nm631u2e5K/N742KOgDeOD4K7bdIxncXTu6XPUvD+5NyHZXNDZi0Aewo7uXtvDIHfFI/KOhb1i92YeOjKxWOtn0dhvDBn0AgR6IhBKfUAscGFrR07/VWomI/hidscFBH4AJ2sbEFVvNxt4Rgz4AfZOQI09VglGNv206Ou7rTBPueX3qKCKz56HTQR/E6/bt/Bts++PpoA+g+wgcfHLi/ROcovuBB0cN+gA6/3TfBHhjD4c2JVjmyoQDG5rsdSZJNNccOhX0AZiGwfanH8Pf2nw66AMwTbY/9dgkeJg4wa0tp4I+AN0fJbS7YxI9Gh9TPvCT1MERtqRaFz4YaG/wEu5QbYnZHmZblSQjKVNn6VhRBv8dimJ9VsqlDJ5pdcj2vS8ueegVFJdi38pKMnAro3/HXUpiP291jNsJHRa2MzpHuHakY6mAPIbHi6VdsMNcK9k4mSgp0rCCv5LDgvNjudaKfUFSUWQJR4LPDY/D3n43qTiGWNF2eIZvF0wakntsW89l19RJjZEs9HGqc2r8zlTn4HGa6nShqI74FoFRzk1lhuojLfWbE8zU8XQYpIpipIri0w1eN8ryBbbeQ563GinntDqllF2IPG+1LbbT51yH4hus7JQ+90ZU79TJLZhRdjVp3tPbCjPTq6kovtiy3Yuqbsel+E69lpC4dvYnLds9yTvL1+M9I2hVkHlPxRW23SMZfHjWvFF/vJ9fcE5CttMdKlcXj/zdu6Iolyxn4sHx7TPThwzwFAnePSvxMhQTgS9dprhy+HdMeDiYAAEAAElEQVQ/t0jC4Uq8Y89cMXSEl3OBfZMRUqaKstw3+IBTQr0w8W22ckEa8rwzcnvPeCvUtVUJ2xckF5eq8LH141fsdaoyH1w3/PbdlGPBjZDfL487ZyYsuQVWvAfS+40nSlfCrMsn2jtBP7Lf8U7k7FFKH6gquR/58MQ4ZAPLr0gs/15WJeadXzz6iSlAXnklc847rcfg9HhYed1NpOXksuTSK0+1qw4nq2+YGlt0T+JdUYiSdXrc6Cjx4VkwdcpsTPkcP4gvIRs1DXFxl1kVSB779z+bsQhGzQ4wTeRZS5Ec9s0uGdEAwSMvY2ghMA0cWTPwlKywzf5EoWkhjja/hCyplBWtHXIVMBGieohna39PMNbNJVXvIcdbaovdk3REe3m1YzchPYJDUlmVPYcKb+oLUHREwvz28H4O9fnpi8UIajGCukGOy8WPl51Luc9antzLLR3878EGYsAtFUUc6g3SFIrw1vJC1hdZf8i1hDTebAtT5lNxyRKHe2Msz3VR7kvt1VaI57I11es0NxjkFEr09Rh0NpuUz5aZMd/67GWwXqNnl44jW0JNk3EXy7gK7Z2nM00Toy6C0RFDckoQA2WOGynD2tKiaZoYtZ0YtV2Q5kRdUIAZ1k6Ju8iFI9eAFDl+4yMZqp7bGrrY09hDhlvhFy/UEtF05halUZ7txR/SMAydQ60BesIa6+bk8+nL5pDtm1qz9sRCcOBxMAyYd01czAUg7If9j8dfz7kKbNrdI0gc3e/H//gTxOrrcc2dE98R5XCg5OYQO9KA74LzcVYkLmY2GTTs6eDlvx4gEtQwDBOXV2XRRWUE/VGa63robQ+RluNCVWU6m4OUz8/h4tvn4XBNjRU/iI/N63duo7ejneoVq/FlnQ7gG3bvpLu5kaqlK8jIs0cIcCIxIhqhvZ1IioRnQS6SOnHraFb7yGkR+CUbU4tBXzdk5iJJMkZnM+gacr499VQMLYIe6kBNi8/kaH1NKJ4cW4q4nyQcaMQwdJyuLFSnvcIZMS1ANNqLz1tEKNyBLKuWRV3OpC/axZHunZSkzwFJItudeH3A6YJhmmxob0HTDfxajLCmEdA0luXmcU62PbNPD9Y3YpgmszJ8dESiLMzKoMQ7NRLLzyQYNdENSHfbt5U0GjLwdxuAhNcHsizhSbOvA9DDJqYGalpytr+aAR3MeLBm+jXkYld8G6gdtk0TszuMlO4C3YCwhpQ5+ndHBH7jIxn9Y19Eo6EzSHcgiiRBdX4aPWENCYjpBi8daCGmmSwpy8TpUFlSlonXNYVEwsN+CHYDRlzApacRgm1QuBgUNR4Mdh+BjNIpH/gFY0G6I92UpJVMtiu2YWoascZGHCUlQ6b7TBV0zaBhXwchfxTDNOlsDFC5KJe0LDfuNJW6ne2E+jRKZmaQke+dMqIu/YmGgoQDfWTkpf5k+lRBlHNIMnrdLrQnfgehPsjMAyTwt8UPpmXhvP0rltQ9g0depv2V/8CI9KCml4IkofUcQ3ZmkHvhF/HNsKZeGQm1seflzxDoPiEGIilULHgPlYs+ZMnuSQ7WPcjWvT9H18M4HZlEY34kSWHujFtYsehTttzjL3u+xdamgcm/lZmLec85P8TnzLLlHlONfd1dfHjzq0PI0gD1B1GB3593ETPTEts2ua2zm09s3j/ksfkZPn5z3uKE7E4Wj++I8dphDcOERaUyt57rRLWYS7jjtSj1+/VB7XnFMqsvc+JwWrPf8WqMro0a6OCdKVN0gxPZYV9QFnusC31THwNUdhwSjjvyUausDTCM9gCxv+3C7AzFc/p0EwwTuTILx9sXIblTf1X3bOXu1+r4j0f3oo9zTvhr1y/gfWtmJMcpO3n5B/Di98GIxV8rTtBPiIc40+C6n8AL34GuevDlw1t/C9XW0xYmg4cOPcT3N36foBZkUe4ifn7pz8nzTJ0UkqEI7djBsU9+Cq25GbWwkNKf/ATv8mWT7da4adjXySM/2z6ofdcLw4tfFc/K5NqPLcHlnRrPz21PPsLL99+DFolQOm8Bb/nsV/Ckp3Yqx9nAlM/xSyamYaA9fW886APwt58O+gD6uom98NfE7esx2l/9LkYkroKn9R5H6zkGgBHtoePV72FokYTtAzTs/u3poC9+Uxr2/I6+rtFVIUcjFO5g8+4fo+txdcBozB+/hamzv/bPtHRss3yPzmDjoKAP4Ih/F8/V3W3Z/lTlizs3DR30nUADvrFra8L2P791eGXcfT0BXm3tTNj2RFPfrvPKoXjQB7D7uMHW+sEB23jo6TSGDPoA2psMDu+ypsAZaTHoeiMe9AEEaw38221U9awJo288I+gDiJnEHrSuTqY9fTge9AHEDE6++caRbrQN41eNFEwMTf4Q304g6AP47mP7MIwU30HUdgCe/4/TQR+cDvoAon3wr4/Hgz6AQBv86xNx2dIpRne4m+9s+A5BLa4avrtjN7/e8etJ9so6Td/8JlpzMwBaSwvNX//6JHs0fkzT5Onf7Br3dU2H/Wx7enylViaLvs4OXrj3t2iR+Bj2+P69bPzng5PslQBE4DcykWB8i+cImB2JS5Pr4S6M8PD2jWgPRsjaADvoH1piO9hbb8kuQG/gKKY5/AC6p9e6vHeDf/ewx1qD9ZbtT1X8sdHlrdsiQ8j1j5HwKAO4vf7ULrnQn9aewX9La+9IYfPo9PpHfn/6uq3Zj3YOvj7Wad/g02yNDX+wR8dqCoDRHhj2mNk+uHyNIDWoawuQaOymGSbBmLUJlaTTNoZST9oZz01/A0SH/z6nKsf7jhM1BvYTtf7aSfLGPqKHawa8jtROvb9J1wwiocR+K13NU+P52dV0HNMY2I91HheTfqmACPxGQPKkIZWMrHAmz0k8FUX1FeDMnTPscUd2NWq6NQWnnNILB7VJsousglWW7ALkZi3A7coZ8pgsOyguOM/yPRYWrEcaRnd+Qd7gv+1sYW766DmUS7MSz/Mr8Yyc13LFKKqfqcTsQpkzFernF1tLkM8rls9UpB5AYYU1+54KBemM3Ty+avuS+uXZnuHLRlS6kMZY0mM4lNnDfz+U2VNH/exsY1lFNpmexLaR5XgdpKV6nl/VhfHtnCORcYZ4WNVacI1yTQoyJ2cORb6BufAXlV00Sd7YR9rFF5/xev2k+GEF1aGQWzaEqvIYqFw8NZ6fRbPn4skYOE6ZudweNXyBNYS4yyiYfd1oLz+A2XYMuXIBpiRj7HoZDAN53rmol70LyULRLq2vma5NvyDaVYu7ZDWSLBM6tgFHVhXZq+7CkW4tIds0dBr23U1zzcPoWhhvRhUzzrmLzHx79sR3+Q+xY/+vCYZaSE+rpC/YiENxs3D2eyguONeWe+xre40/7/4aYT2ALMlkOAs4v/ytrK+8w/IAdaoS1jU+tPFVagNDF9tenpXLj5efh5rgdzOm67zlxa306gNnJVVJ4q45FdxcOTUkpU9yuEXnhf0aUc3k/FkqyyutD1BbjmtseylG5MSORkkGjw9mLnBQvci6/dAxnc7XNYyIScYSlcxz7B1U6wdDaK/0YPRqEDRAB7ncifOWPCSvtSDTjOloL9Zi1HYhZbgwNQMiGsriItRzy0e8Voi7jA+7+8fdx/38v3/sYvdx/6nVP5cqI0ugGybRM/aBSkBlrpffvXsV1QVTIEA6uhGe+ya07AXFAbmzoG1/XOWzai1c/1N47WdQ+xKULIXLvwVpU1OYoqa7hp9t/RnH+45zZdWVfGDxB5ClqT3fr/f00PqjHxPaugXP0mUU/PtnULKyJtutcRPsifLwj7cOuYInySd2F/f7qbm8KiuvqWLpZVNHvbS1vpbX/vpHejs7mL/mIlZe/9azdsxmJ0LVUyAQCATTBhH4jQ/RPwoEAsHZg1D1TDKmoaNvfhrj6AHkoiqkggqMvW+Ay4Oy8krkPHtqyml9zXS8/kMi7ftwpJeSc/6/48qba9luJNjK0X330tX8JuFAI5gGsuImu+g8Khd/CF+m9aK7vYHj7D18L+FIJzPKrqGixJoS6Zk8WfNrNh1/BMPUyHQVMit3JZdUvRuvw3rJiKdatvDrusfwxwJIkkSOI40PVl3NFYXW6yhu727i78f2okgSt5QvZkGGvbVqrnnxCXq0oQU/VmXl8pOVF1iy/2xTOw8fbWFPdy8n71Kd5uFnKxeQaaF4+0keO9rHyy2h+EqCCTlOhdtmplOVlvqKZdteDdNw4PSkmSRDWobE7CUq5bPtf6yGGw26t8Q/hcxlCp4y+7Z9mr06sVf8mJ0aygIv6vIpsGojSBrhmM6t//sGO475T7WpskSO10FEM+iNnBZKqsj28M+71pCdZl9d26SjReC1/4ajG6BsNaz5JDjccOQN2Pi/IClw/segdOrV0j2b8D/yCD2PPY5aXISjuITuv/0NU9fJvv2d5H3gA5Pt3ogYhsmTv95J3c7xCWnllnu57cvWU2gmmlBfLxsffoCOo0eYsWwlS6+41tJOOYE1xIrfKGgv/hV9yzNDH3R7cb7/P5Hcie3VPolpaBz7603owdOKoZLipPSWh1C9iedSmabBlifeQWgYIRfFkc7q6/5hqa6frkf513NvIxhuPdW2btV/UV5sTy7B83X38GTNrwa1z8haxkdXWlMo2+mv40PbfzbksZ8t/ijn5iQeeNf0dfLeTf9AM+PJzW5Z5f7z3k6R255B9a2vPsfx8MhJ3pcXlvD1xYkNXp5rbucbOw8PeazI7eSBdcsTsnuSfxzp5ad7uwe1Zzpk7r+omDRH6nYKB7ZF2b91+MT8ZWsdVMyxL/iLdRs03B3BPBl9K1DxbhfOXOvvkWmaRH7ZjNlyWuzFcX026ip7a32OB7HiNz7s7h9v/MWrbD/qH/3EE2R6VHZ8/Urb7p90/vUJ2Hrv6dfnvBPWfAJ+vfa02qfqgX/bCFlTZ1vd2YT/kUdo/Nznhz1e+JUvk/Oud02gR+Pj8V/vpG57e0LXVi7O4bq7ltrrUJL52ze/xNG9p1VM19x6B+e99dZJ9GhqY7WPTN3RVYqg73tz+IPhIEbd8KqTYyXSuntA0Adg6lFCDa9YstvXdWDYoA9Aj/XS1bzB0j1aO7YNCPoAjhx/2pLN/mxqfGTI9rrubfjPuO94efD48O/voy3W3pcXWutOBX0AYUPj5bZ6Szb7M1rQB/BSW3PC9p9tGn4msjkcJaRZU+97tnFo//0xg03tiauRTgS1+0b+24/V2qts2HdIPx30AejxNjswW2MDgj4AfefUUI0TJIfxBH0A/pCGnuplHPqz6wxJ+d0Pwt5/DizxoIVg/+AyQoLUwP/ooyMe7/rbAxPkSWI07E68ZE7DnqlTSgmgr6tzQNAHsP+1lybJGwGIwG9UpPRsS8fHguIbOnFc8VpLKHe6c+PbVkY6x2PtHl7P4O2LXos2+5PuHFrByql48TisrUqUjVDItngYtdKxUjjEKnCBy9rKcH/Gkh6dpia+6lTgHl7VUwacZ8pkjte+Z/jvZb7bvm2MycDjGeW4z97kdTV9sD01zZ57SGkKnPF2Sxmp/f4LkotLHf9vW5GnkGBDRsng12cqeQ51niBlcBQWjXy8OLXFxxzuxPtmJYV3wwyFy+vF4R7YaabnTh1V8OnI1PoGTQLqRbeA88SXVlEh8/QXVl5wPnLZ8OUYxoojvYSMRe8c0OYpOw9P+fmW7Lq8BVQsfB/DfcwFVdeSmX+OpXtkps9k3szbTr3OSKtkfvXtlmz2523z/x+qPDAIkVG4dvbHcSqjjMBH4fbyS8h3Ds4TzHdm8s7yi4e4YuxcUTiL5VmnO581uRVcmFdpyWZ/vjB38ajnfHtx4rvl3jmjhJJhgr/bZ5SgWFTmes+sTPJdgwOMq0t9LMpO7Xyh5RcNHxS7vDDHZvXNtNkK3hmnf8OeCpn0efYEZ5JPQb0k69QjQspQUC+2njsrmLr8x42LxnX+21eUJcmTJHHV98BxYhLO4Y2/Xvz2uKLnSeZcBXOvnRz/BKOS9+EP4Sg7/b2T3O7T//Z6KfzCFybDrTFz6XvnJ3ztNR8dve9PJRwuNxe9633ISrxf9GRkcuFtd06yV2c3IsdvDJjRMGbLEaS8UnD7MJvrwOlBzrV3VinW20i4cTPOvHm4RqjvN17CgSbCgWZ6OvYQ7msgq2AVadmz8WZU2XaP3sAxwpEucrMXII+yyjhedENjS/PjeNUMvI5M8rzlZLjsmTEyTZNXO/bQFe1FkRSynD7Oz5lvm+T1gd52VEmmOs3aCuJQhGIx3r3hJbojYfLdHtIdDmKYzExL57PzzsGlWPscNMNkr7+P9nCEp5vayXSqvHtmGSVe9+gXj4GYYbK3O0qRW6YjapCmylRMAWEXiCfn790Swd9mkpYlkZYhk5kjk1OkICdp9SPSaoAJrkL75+sMv4bZpSGXuZDUyV29ETl+4yMZ/aM/GOXr/9pDOKYxrzCTmGFw88pSXjvcCZi8UdOBQ5G46+JZzC7MsPXeE0LYD827oHAhePrt2mncDrIKReMLfgUTj6lphHbuRC0oxFFcRO/zz2PGYmRcdhmSc+Q6tKlANKLxxj8Oc2x/N75MB6FAjJA/Snaxj+I5WdRtbcPhkfH4XPjbQqRlubjmriWo6tTckRHo7qKr8TiFs2bjcKb25G6qI1Q9JwDJ6UYqn4sZ6sOo24WcX4aUbv9A3oj0oqYV4syaYavdWKSbQNdBTCNG6exb8GXNstW+pkU41vwyTkcGedn2dpjBWA9H/DvJcOYRivXSpTXhj7QwM2s5mW7rW0ofbd5IfbAZp+Qgy+mj2llsa52juenJ29JgACVeDyFdoz0cpCum4lEVWsMqumGAxcDPxOTFpnY2d/aQ41Jo7Qnzy4NH+MaS2QnXB+yPQ5Y4J8fFc40B6npjzMpw4lVl8mzc6mmaJkc6DEwTqvJk22oIxaIGAb+ExyezaLUDRZXobNHpbDHILbJ+H63PJNJi4CqSUU9sHXUV2Bvw6UfCGHVhpBwHUrqCXOlCsiloNU0T86gfvbUXsy+KMjMHIjpyWSZSggXCBRPHsa4QbodEsz/G/pYeLpydR2dAI82lsu1oF7ph4g/F+OOGI6S7HFy5sIgl5VmT7fbYOL4FIn1QuQYkCepejq8Aqq74sVgIttwbDwoX3ABe+/v6ZKAbOltatuBW3SzJXzLsedtbtxMzYqwoXDFlavrpvb10/fkvOMvLyLj6agAkVcW7/LTIWMbll0+WewnR2xmmZlsbGJCZ50KL6CBBJBjjyI4OKhbm0FLXQ1ONn6xCD6VzszF1ptyo3TRNGg/ux9R1CqpmcmzPLjILi8gpmWI7BaYRYsVvjBj1u4n985egRUFWUC+/E2XRGtvst730TQKHnwBATS+l6Npfo/qsyf+bpsm+179Ex7EXBrQXz7qZWSs+Z8n2SXr6GnjsxXdinEiMdzmzufHyh1EV66tCNV1buXv7vxPVhyhwiswtC7/KiuJrErKtGTrXb/g6XbG+QceuKFjOt+an9laEnd2dfGzzayOe86uVa1icldigpTkU4ZZXtjHc0+HBtcso9FiftXvHi400hk4LlcgSfGlxDleUWs+H1HST378Spa49LrJTkSPzgYucOBRrwU3LMY0NTw0URMnKg+72k/+WWHONC9WR2H36Dug0PxYFHVCg6DonaXPsneWN/KkV4+BAER2pyIHrfYVIbmuDQTOmE71vO+axnsEHHQqOWxejVA2fGy1W/MaH3f3jN/61h3terx/3dbetKud7bxs+4Jh0TBP+cjscOCHakjcHkKD9wPDXKA64/e8w0x6V6mTRE+3hvU++l4NdBwFYW7qW/7n0fwYEdpqh8bFnP8YbTW8AMD9nPndfdTc+h32558kguG0bR951B+jxfsJRUUH1E48jWZzYnExef+gQ254+Ou7rJAlu+cpq8kqnRskdXYvx9+987ZS4i6QomCc+x3NvupULb7tjMt2bsghVzwlCe/nv8aAPwNDRXn4A0zBGvmiMRNr2ngr6ALTe4/Ts+atlu/62rYOCPoCmw38nEmyxbB9g064fngr6ACLRLvYevs8W208e/tWQQR+AicFjh35OohMX9x59dsigD+Dp1q3s8tclZHei+PKOTaOe86Xto58zHN/bUzNs0Afw/7btT9j2SZ46FhgQ9AEYJvxqf3fCn2t/dh3XTwV9AA2dBjsarKthbn0xNqitu73/v02OHk78Pu0vxuJBH4B+4rWNGE3RQUEfgNkcQ9sy9G9iPOh7WocO+gBiOtqLtZbvIUgOumHyhzfqE7r2r5uPEo7Zq2hrK7Uvng76ANoPjhz0AegxeO5bSXXLDh46+NCpoA/gleOv8OrxVwec89LRl04FfQD7Ovfxz8P/nDAfE6X5G988FfQBxBoaRlX1THUSCfogPnfx8v2jfGdTiENvvj5A0dPs9zlu/OcD9HVNLYXS6YII/MaIGTxjIBMOgmFPJ6eHuga1GeHBbeMlNqwNc4Rj4yMSGWwnGLInqOyLjvxQCMb8GGZin0HLKH//cEFhqhDQhy7c3p/QGM4Zjs7IyMFGZzRx2ydpCg1twx8z0G3YiBAYoipEX8S6YW0Mf3oklPh99KA54murmIERfjMBGyazAtGRj/eNclwwacR0g0QrM5gmqR34BRKrm0bAWtmgiaAzPLivPLOtIzy4hMBQbamG7h9cXiR2/PgkeJIahPrsnQhMJsGe4UvDmIZBuHeYCUJBUhGB3xhRFl4w4LU8dxWSak+uirtkxRklHSR8sxLbwtif7OLzcLgGb6ly+0rxZSdenLw/c2eeWYRTYoFNqp4ri0dWVVtWdCWKnNiG9zsqLhm2JEKeI4PVNr0/yeLGktEVQm8qr0rY/nuqh5A378eHZlnfn/+2ynSGSim7rMSLakOu2aIyGWe/r4dDgcVl1rcHlVeP/NiUFSidmfh90hcOvDZjkb1bmuQqN7iHeH8VUJZ4rdufXwAjSI4r56S21PrZjNuhMDMvsa1/5dkesrwpLKox+3Lw9isPJCujljsCYKl9KtXJ4pqZ16D26wszXZmsL1s/4JxLKi4hvV8JJKfs5JoZ1scZySbr7TcPbFAUsm+7beiTpwhpuYmnwixeP3LfnErMXn0BzmHqHxXOnEVeRdXEOiQARI7fmDFNA2PHSxhHDyAVVqIsv8y2wA9A62vGv/vPGOFu0mZfi6d0tS12Q33HaNj9f3S3bsY0dLIKVzJz2Wdwuq3XHzzJwboH2VfzZxTFybKFn6S04Dxb7JqmycbGf7Gn7SWCUT9RPUTMCONSfJxTeDlrK28bVOphPGzo3MdPDz9MS6QLSZLwym7Oy53H+yqvoMQ9dP3AVOIbu7bwbEvjkMcuLSjmm0uspUn9ue44vzl0lP4LXDJwS1URd82psmT7JHu6wvx4dxctEZ18l8IVpT7eVpmO02Ie3kmaug3eqNEwTTi/WqUk2565ri0vRjheayBJMHOhQvlslbq9GoYBVfNUsvMTv4+pm/i36YSO63jKFDKXKbaJrpzE8GtEH+7EbI0iOWWkUieOc9ORy+1RWzOae9HeaMA40g2GgZThRsr2IM/IQVlWPKL4jcjxGx9294+BiMbH7tvCa4fb0Yx43m2218mCknQaOkI0+UPEdBMTUGTwOlRWVmXzs9uWkuFJ4cAPoKMGNvwKon2w/N0gybDlHsAELQxNOyDQAUYUPLmw9jOw8n3x5KoUZ3vrdh44+AAe1cPt829nRuZgkbia7hru23cfMSPGLXNuYXH+1CgN0P6rX9H94N+RMzMp+tpX8S5dOtkuWcIwTP70ldfp7YyM+RqnR2HVtTNYellFEj2zn/aGerY9+SiGoZNdXEprXQ2ZhUWsvO4mPOlTUBE4BbDaR4rATyAQCAQpgwj8xofoHwUCgeDsQZRz6Ie+rwZ9w3YwQVm1GGWxPbXwjPo9aK//E8JB5CVrUVdeaYtdACMaoPPNnxJq3IQjoxJkmVh3He7i5eSc+ykUV+IzIqZpsvnxtxPuOwrIONx5xMJtAHjSK1l62W9RnfbNuBw+8k827fwBhhnDoaZx+Zpfk50527Ldfe2v8kzt/xGIdqNIKgYGSwsv54rqD9lSM/CZ1q38oeFZDEzeUbae64rOtWxzKOoD3fz88AbqA12syavkrurVuJTEf4Jf27GZ59uahjxW4nbztwutyVvf+doO6gKhQe2LMtP4ycr5uG1SVXuuMchvD3bTGTHwqRK3V2dwc1X66BeOkc31Gq8e1JBlWD9XZUm5tceeYZjsfjNG/X4d88yUOAlKZyisWO+wVNKhe3uMjhc1zJPpHDLx+h0q5FygknOutd0G2oZeYi/5IXTiD3BKoErIJU4c12Qj5yRu3zRMtJfqMPa0QIYbx6XVyKViZneqcKC5l9t+8wZdwcG5RCcXns/MAyzMcPHQx9ZQmjX0tq6UoXk33H01RHpAccK5H4Ejr8fr+i2/E468CoefB9UJaz8bX/GbYuzv3M8PN/+QY73HuKLyCj6+/OM45OlRQqXnyado/u530dva4kmlJ3DOmoV77lxC27fjrJ5J4Re/hGumvWWx7ETXDR7+8Taaa4bPgRsKd5rK+/5rre07QARnF9Nmxc9o6SB2z0MD2hy334BcVmjp3mZfN9H/+yL0E8pQr/0Qyjx7tmK2v/wf9B0aWqHKN/Ny8i/+dsK2dzz3YXratw97PC1nAcsuvzth+/0JRzr5+1NXD2hTFQ+3XvuiJbudoUZ+8Prb0c3BihrXzv44F1W+y5L9g33HePeWH2H207D8zdJPsmSIbTJWME2Td7z5AA3B0w/6d5Qv5uOzE9sWu7Ozg49tfX3Ec64qKuUri5aPeM5wfGPHQZ5rGV5c57y8LH6wfF5CtvtzqCfKB19rGaQg+p3leVxYaH0QWdem85uXTouJSMAnLndRlJn4VsyDO2Ls2zyywsu85SpzlyU22Iq2GzTcPfIWoLJ3O3EXJBZ46/uCRP88vNCFVOjAfVfieXjahga0Z2tON3gduD5+PpJjbP6KFb/xYeeKn26YLP7GUwSj4xdpmZnv4/l/X2+LH0njO8UQG1opekg+8goUpXCJijOI6TGu+vtVtIZOC9LctfQuPnLORybRK3uIHDpE7Q1vGRDwDYdzxgxmPv6YbXVb7eaJ/91F7ba2hK4tnZPFjZ9JrF8XTA9EOYcTGPWDVZ6MumPW7R47OCDoi99rj2W7Jwkdf3P4Y8eGPzYW+rpGltwPdB+2ZL8/ja1vDGrT9BDhSLcluzVdW4YM+gAOdlh7fwA2dR0cEPQBvDnK+5YIjeHeAUEfwJudiX8/f1c7uqTza+2Jq9Ft6hx5JnJXd2/CtvuzuT08ZNmIje2DVxoT4VDLwCU5EzjUYk15sO346MqXTfWJ3yNQO/q1vbsSt6/XDCF32g+zJYbZm7h9o/aMCYNgDLPJnu+LILnUtPUlFPQB1LYF6A2nsOJgb8v4gj6AbfaUJpooDnUfGhD0AbzeOPIE4VQh8MYbYwr6AKJ1dcSOD53/ngo0He5O/Nra8a0SCgRnMm0CP7lgcKFqaYi28SLlD1YvlArKLds9iTNn1rDHHDnV1mx7Ri4A7/TkWbLfn9ysRYPaJEnB6bS2Za84bfitosVpw793Y2WWr2RMbVbJd/nIdAwUzpiVlvj389Ki0X2s8iVe5LXcO/JqW6kNxdsBqtOHXhWblW6PSERx1uBHXLGF1T6AjJzRZ5Gz8hK/h6to9Gs9lYlvs5ULR1mJTFfAm7j/UsEZ3ztFRsqzrhYqSD5l2R6UBLeRZXkdpLlSOHvEmxtX8hwPKV64/UzK08vxqAOf3XOy7Ul5mWxcc8autK1kZ+MoGHn8M5lk5Ce+myUt256+V3D2Mn0CvxllKKuXxGXGZBl5+QJkG5QH5dwSlHVvB4cLJAl57iqUJfZ1BjnnfwZHTjy4kd3ZKJ64mqQjawa5az5vyfbi9b9A6q96KZ3+uGXFxfwL/tOS/f5kpldSVdZ/q6fE6sVfsJyDV5YxjyurP4JDdgESihQftM7OWc0lM95ryTbAuTnzuL3sYhySgiop3FxyIevz7N/a45QVvjJ/PbnO+AN/YUYBd81KPJfwhrIqCl3DdwAK8KOlidv/4bJ5uIYZAKarCt9cYj13E2B1vodbZwws63BZsYdryhKTlD+ThaUy585UkCVQZVg3R2VWobXv5NxlDjJHEH31ZUgsOj/xnBpvhULaguEfzd5qmbRZif8NyvI05MXDBGIZCs6bcpAsqKqqF1YizzyhGuxRcVw7FymVZf4Fp/A6VX5w85JhS90MhyzBb+5YmbJb6wBQVLj2p9D/rytZAQ5fvG+cdx2k95tQm3MlzE39cgf9SXem86013yL7RBmnVUWruGvpXZPslT34zjuXnPe+d2iFVacTR2W8xJGan0/J9/4TyZm6z5wrP7AIhzux4ffbPrfCZm8EZxvTJsfvJGY0BqaJ5LL3R2/GoqBrSO7kzFzroS5kVwZIEka4G8VjfbXyJL1dh3C5s3F68gj3taDrQXw257CdRNNCdPXUkJs93xbhlZNE9TC6qeGQXUT1IF5Hpm22AUJ6BMM08amJ19cZC5ph0KdFyXLac5+WYJCtne0c6vOzOjuPY5Egy7LzqE635/2p6wnQEYmS5lBJd6iYkkSZ1/73KKQZhHUDhyyTNkINuESJxEwkCZyqfQPTSMggEjJxp0E0JIFkoMgynjR7/NcjBnqfieySkBQJPWqiOEHx2GPfDBuYMRNMkLwyRAzwyLYJB5ihGDgVJGV8/oocv/GRDFXPmG6wv7mHimwvte0BHLJEts+FS5XxOmVq2wN0BaOEYzrl2V7mFGYgTxXBCUOHxm1QsACcXoiFQIuAJyt+vLsBXOngsa/k0UQTM2IEogGy3FmT7YrtGMEgmr8H09DRm5pRS4pxFBQgqSpaVxdKejqSmsIrz/3wtwVpP9oDikROcRot9X4MzcCX6SI9x4vDJRPqjXJkdwfl87Mpmjl1v5MC+0hZVU9JkuYCf+3XNBP4GvCHE+1VQD1wi2maXbbd15kc9SrJ4QSH/TNIeribQN1zSIoL34xLkB1eYt319B16HHfRUlwFg7dQjvseUT+tLRtwZ8yg89hLGHqY8gXvwZdpbSspQG/gODUN/yIUaqMwbxWaEaK9cxctHZVUl1+Px4Z6eAc73qS2axu6ESXNmYOBQaFvJvPyLkCWrA2Cw3qU59q2E9IjXJK/FB/JDfxUWbYt6Hvy+BG+v28nJ7Nq/nasHoAKj5efLD+fQo+1SYrv7T7MU43tGMRz405OEeU6FH60YgHVGdZW5V5qCnDv4R7y3AofmZPJju4oHkVmfbEH9ziDhdFwOewdlIYCJod3abQeN4hGTKJh4mrCDlh9qUJBqfVnRbjZwL9ZQ+s1kb0SziyZtHkKXpvKOEluGVwm2pu9GIfCKAs8qCvsU1OVPA5Mf5jYlmOY/gjyggKUOXmpvSo0gUxWHzkawajGj54+yN7GHmK6zsGWPiKajkOWKMxwI0kS7X1RDNMg2+vk0vmFfO7KuXicU2Cw3dMIm++BI6+BOx1kB6huKF0BDRsg0BZfGVz2Llj89sn2NmEcsmNaBH1GNErnvX8guHEjSnYWksuF5HCiZGaQduGFeFeuILRjB71PPIF78WJ8q+0R3ZsIejpCPPCfm4gEB+fUKg7Qz0iX3frUEW7892UUVmZNjIOCacuErPhJkqQAx4FzgbuATtM0vydJ0heBbNM0vzDS9dO1TpEWbKfp4XejhzoAcGRV4Z1xKf5tvzt1Tu6aL5I+78aE73Fk9//RsOe3QxyRWLz+F2QVJr5toL1zF8+89lEMc+iEfoeaxtXr7iE9LfGcyMcP/Q8vHvnjkMdWldzA2xd8OWHbMUPjfVt/zKFAPAk8y+Hj7uX/TrHbvtXWZPGbQ/v4w5GRxXkeuvAyCtyJ5RLc+vI2GsMjK0v+9tyFzMtMLFC495Cf3x/uGfLYrHQHv76gEEeKriD0dhu8+HAEYwQNjNWXOSiuTHwg3Pl6jM7XhhY1yrlAJWeNPRNc4XtaMGtPf87yQg+uW+3JjTFa+4j+fgtop8Vw5OUlOK8ZOVfnbFzxs9JH2tk/GobJyu88S2cgOvrJ/cj2Otj45ctw2DxhYyut++G3l0AsMLbzV7wPrv9Jcn0SDItpmtRedz3Rmpphz0m//HJ6n3nm1Ov8T3+avA9/aCLcs0QoGOX3n3k1oWvf+rnlFFdn2euQYEoxVVQ9LwVqTNM8ArwFuPdE+73AjRPkQ8rRd/CRU0EfQKy7np6dfxpwTveOexK2bxgaxw78aZijJvW7fp2wbYB9tX8eNugDiGl9HDry0LDHRyOqh3n16F+HPb658VF6Ix3DHh+N1zr3ngr6ALpjAf7ZNFidNBW5b5SgD+B/D+9LyHZA00YN+gC+v6c2IfsA99cNHfQBHO6NsaHNHlXPZFC/Xxsx6APY/mri6oamYdL55vDlIro2aZhnFlJL5D4hY0DQB2DsDWFq9kwG6puODQj6AIxtjZhD1IcTpEYf+ejOxnEHfQBdwRiP7khdFUUANv5m7EEfwLahJxwFE0Noy5YRgz6A3mefHfC647e/xTRGV12ebJ6/e2/C1z57T+LXCgQwcYHfbcCfT/y70DTNk1Wnm4EhC+1JkvQhSZI2S5K0ua0tsXonKc8Qq63mmRWhB1WIHqf9ka43rcnaD/I1wXNGuHqU600MErdvDPH+G5b8nTjGMjTXEwwOxroJQLcSH4xyrQ1xTdIYy/uT1I0U/ffdWrIzhBE7/R7O1hTIK58ExtVHJqt/TPSZAaCl8o8WEuhLU/zvmeYkFMBNgaAP4ivriTJFhiiCFCbpgZ8kSU7gBuCBM4+Z8X2mQ/4CTNP8jWmaK03TXJmfn7qyvFZIm30tsuu0CIeaXkrGwlsGnJO56PaE7cuKg5LZtwx7vHKRtS0Rc2feijTCV0hR3MyqvClh+07Fw7mlw19/TtEVZLoS/26syV1Apbfg1Os0xc0NxecnbG8ieVtZ1ajnfGhWYgXW0xwqeWPIlf3s/MQFgm6sGH6LaIVP5TwLctfJpmqeijzKk3PJ+Ylv85RkiewVw1+fuVy1pLp56j5eBaliYC6iPMeNZJMAjrKiFM7YrisvLkTypa7a3mSQSB+ZrP7xhqWlZLjH/91Nd6vcsNT+Mji2sur98Xy+sbL45uT5IhgV78qVOMpHThPxXbhmwOvsd9+JNNrDOQW49M4FCV97yR2J9esCwUmSnuMnSdJbgLtM07zixOsDwHrTNJskSSoGXjRNc8Skj+ma4wegBdoI1DyFpDjxzboKxZVBsOFVIu37cBctw1NiPdWl4/gr9HXtw+0ro7PxFQw9SvmC95KRZ104prunlkP1fycYbqMwbyWaHqajazfpaeXMqXobaV5rgwHTNNnT9hKHOjehGzHSnPH8u6K0mSwuuARFtiYo0KeFeLJlM0E9wpUFKyh0Tx3VrPvrDvHrmv2D1jxznU7+e/kFVKYlLtRhGAZf2nqANzr9g0adPlnmP5fPYVlOVsL2Af7V0Mtf6nrJcip8ZG4Gu7pieFWJy0t8SVH2tJNAr8GBbRrtjTqxKGgndi/KMiy7SKFspvXgpu+gRvdmDa3PRHaDI1smY76Kz0IphzMxDRPtxR70uhDKXA+OC+1VyzU6g+gbjmL0RFAWFKAsKhxVNfRsy/Gz2kfa3T/6Q1G+89g+9jX1EI7pHO0MoekGsiyR7XMgSzLdwSiGaZLudnDRnHy+et0CsqZCyY7OWtjwa2h4I67cKavg8EDREji+FfpaQHXCObfB6tTPFZvuGKEQ7b/8JYHNW1AyMpA9HlAV1Mws0tZfRNratQQ2bCC4cRPuJYtJX79+sl0eM+3He3nw+5vRo4PH4JI8eGVPVuDqjy6matH0XAgRjB2rfeREBH5/AZ4yTfPuE69/AHT0S1zPMU1zxIJ1qRL4mbETuQ+qw3ZlOlOPYQJGLIjqtnfwBaDFgph6DMXpQ9cjOBz21EmDeC5hKNKFqrhxWSzYfiamadIb6cSpeAATRVZxKPYWMNUMnYAWAknCJTtwK8kbwGgntqKoNs1KNgX7ON4XQJZNNM2gOxJhSV4+RRaKt/cnahj0xWK4FIWjvSGyXCpFoxR3Hy8R3cApS8SM+PZblyLZ9vvSDRPTNNFNUGQJ1UbBmFjMANMkGjZx+2R6u2N4fSpOt32B2UmMmIERM1G9NgZ9sfh30dRNJIcMBqBgWzkHiG/XMg0TCSleZscxuv9nYeBnqY9MVv8YjGhohoEiS/RFNGQJtJhB1DAozvTSG9YIRKNkeFxTI+g7iRaNj6JlJV7aIdIHmODwxmvEGXp8O7KhxYNAdWoVzNYNnWAsSLprcF8c1sK4k1yyKBkY0SiSopxIXzFBkjB1HSMaRfH5kGQ5/qzRNOQUrt93JuFAlK62AKYGkgp9/gi+DAeKrOLyqETDMdqO9ZGR56aoKhuH0/6+JVlo0SiKw/6xsiCFyzkASJLkAy4HPtyv+XvA3yRJej9wBBh+L2KKYHa3EXvk15itR+INviwcV78fuXK+dduGRsfrP6DvwL84uaNHcvgovPJnuAttKOWgRdjy5G1EAgMT71VnJovW/ZT03MS3HABs3PkDDtU/eOq1ori5et29ZKZXWbIL8GrD3/jXwR8Nap+ZvZx3Lf7OqdW/RDFNk28duI8nWgYOmqo8hfznwvcyw1dkyf6Z9/rvwxv4x/F9qJLMnZVLubNqacL2DvZ08b6Nw6iCHYr/77F1V5DpTGzQEtENvrL9ABs6/EMe/8GyuZyXb211tCOi8+3tHWzrjOA6UUYOIMMh8+Vzcixv93xmT4yXD2gD9EVWVsnctMKJbKEz0jWTl/8VoadrqEmzKIoDrr7dhWKDwqFpmDT8IUzsRBqX5IDSdzpxFyQ+ADD9GpG/tGMeH0LEI13BeW02ygLr9Uq1V+vRXqkfmAxa6MP51kXIucmphzrVSMU+sskf4l3/9yY1bWMXQvG5FJ781DrKs1P4c9U1eOwzsP1+cPqg+lLY+/Doue5Va+Gdf41fk+L8aPOP+MPeP2CYBrnuXO679j5K00rZ1rqNr772VY70HGFF4Qq+v/b7FPqGlFdIKYxolOavfg3/Y4/Fa/MZRjz37+R/gOR2k/nWt9L75JPofj8ZV19N8Xf+A9mVugF7X1eYP37tdYxx6lyl57q449sX2Do5ZzeRYIAnfvETara8SVp2Dpe+76PMWnXeZLsl6EdS91OZphkwTTPXNE1/v7YO0zQvNU1ztmmal5mm2ZlMH+wg9tyfTgd9AIFuYo/9BlMfXnlvrPQdfJS+A/+kfxqHGQvQ+tyIi6Bj5tDm7wwK+gC0qJ+9r30BKyu+7V17BgR9ALoe5sU3P5uwzZNEtCCPHPzxkMdqu7by+KFfWL7HC+07BgV9APWhFr57cHg10UR4vrWWvx7dTdTQCeoxfl27id3+loTt/dvm0dVH37Ph5YTtP9DQNGzQB/CFbQeGFMcZD7/a3822zriqZKRfcNYTM/jW9g7CeuJZ7IdbdJ7fp50pKsnmeoPtDdZEjXZtiA0T9MXRY7DpufErIw5F5+vaqaAPwIxB09+t2Y4+0TV00AfQqxP9ewdmyJqCgNHQjfZi3WAFoJYAsUf3W7I9nUjFPvKrD+8eV9AHEIjofOCeTUnyyCa2/QG23gtGDMLdsOfvYxM4q38FXv1psr2zTL2/nnv23HNKoKwj3MGnnv8UhmnwhZe/wJGe+BhmS8sW/mvTf02mq2Om67778f/zn6BpmOEwZjQKmjZAxMUMh+m+/370zk7QdXoefZTOe+4dwerk89Rvdo076APo7Yiw+Yl62/2xkzf+/hdqNm8A06Svs4PHf/5DIsHgZLsl6EdqJ9KkCGbzkcGNoV7MnsRLCZwk0j605L4Rsqev7+scfpAVDbWia+Pr4PvT2T207UCoacj28dAaOII5gqrasV7rg8d9vUeHPba/t8Gy/YH22sfUNlaCo9UTANqj4YTt7/f3jXjcAPwxaxMfB/zDBzABzeR4MHH7x7qGD1xGOjYWulpHv7673Z4t9KGjg++l92FpwmbYoO8kMROjzVrJBaOpd/j7j3BMMPnsODr8hM9I1Hek+OCucVvi1x7baJ8fSWJTy+DAu6G3gc5wJ02BgX3yno49E+WWJcK7d0/odRNF+/HEx11H96X2WklL7aEBr2ORMJ2Nw4+1BBOPCPzGgFwxRF59Ri5SpvUkW3fx0AXU1XR7FNKyClcNe8yTXoHqSDwXrDBv2dD3zKhO2OZJitOrkaXht7NVZy+3fI8VWbNGODbbsv3+LM8e+HlKwLKs4oTtZamjq25WehP/bJfnjJxn6pIksseg/DkSS3OG34qT45Sp9CVuf2b+CN+dEY6NhYLy0a/PL7Pn0eqbPdiOI9taDqQ8Y5QcH4+MXGTts5UrsxI6Jph8Lpydl9B1i0vtz023lap1iV9bfal9fiSJdaWD/755OfPI8+QxM3PmgPbVRasnyi1LeM9NzE/vuefa7Im9FM9O/Lcye2Vqb9EtX7BkwGt3egZ5FVWT44xgSETgNwbUS9+FNGsZKGo8IbywCsdb7rJFNjit+gqyln8IyZlBPBwAJa2Iwqv+27JtgOrl/05G7jlntEp40qtYuHborZRjJTN9JssXfor+XyOPO5+Lz/upJbsAquzkXYv/E0U6Q25eUlledA1XVX/U8j3Oy5nP+yqvQOH0QF4CVmfN5ctz32HZfn/Ozy3nE7POo8idRoU3k6/MX091WuI5ivecdxEjhR8K8LtzEx/o3FheyI1lBQwVXkjAb86znn/60XlZXFnqJcMhk+eSccigSFDpU/nuijxLQiwVuTI3LXeQ4Y5XFJAApwKXL1BYWGot8FuwQqVghMDO44MV6+zJL8le6cBbffp9UNKg5BZr4gWOq7ORF3gY8AWSAKeEVOrE+c48JKe1Z5tclI56/TxId57+AFQJaXYujuuEHHkq840bFrJmVu6Qv/3hKM9283/vTnE9niVvh4u/DOklkD8fLvw0uDL6nSCD4o6rbJxqUuGcd8J5H5twd8dLoa+QL63+Eh7Vg4TE7KzZ/Pcl8XHET9b/hNVFq8lyZXHtzGv57Crr6RgTQdbNN5P74Q+j5uejFhai5uej5GQjpaXFhXgkCTU/n/wvfB7X/Pko+XnkfuD9ZL/jtsl2fUSufP8ivFnjn1wrnpXB4vVlSfDIPlbf+HaWXnkd3swsimbN4cbPfgVHgloDguSQdFVPO0gVVU+BQCAQJJezTdXTKqJ/FAgEgrOHlFb1nGjMUBh9yx7MviDK/GrkSvsKyprdrejbXwRDR16yDjmv1Ba7esRP794HiXXHc9oUVwZpc67HlWfPrHhf1wEOvvktAj0NcWWIE3lzvqw5zFn9VdKy51iyX9PwKPtr7kdRPJQVraMveJSMtErmVN2Mqtoj+3/Uv5c3jv+DfW2vEIz5USQHF1fdyeXVH7Bs+8Fjr/Bg06tkqT5uKlnDdn8NmQ4fby9dS64zY3QD46AnFubBY3tpjQS4vLCaFdnWvp/ve+MFDgaGzsW7vWImH52zMGHbEd3gW7sO8XJr16BjLgm+ung2FxXlJmz/JE1BjW9sb+dYQGNmuoNvL8sjy2W/ZPW+Rp29jTp56RLnVau4LBYpN3ST7a9HOHrIPKXLJJ1YJMstlFhzjTXJdCNq0PCHKFp33LgjD/LWO/FV2fPeGE1RtC19SE4JZXU6cpa9XYERiqE9sg+jNQAxHYIxkCXkZSU4r7L2zBEkn9+8XMOPnzlIOHY6x1SRATOu16PKErIESJDudnD5vAI+sn4WVXkprnz5yo/hlR/FFZiq1kH7fuhtAiRQHPH/Z1fCtT+Gg09ANAjL3gUlSyfZ8ZHZ2rKVR2sfJcedwzvmvYO9HXt5tuFZytPLuW3ubaQ57SnvM9EY4TBdf/4Lgddfw9R0lKwsIocOgSShZGYSOXAAE5P0dRdR9NWvoGRlTbbLY8I0TV77ew07n2tgzGsvElx653zmnZ94ishkc2TXNt548M9EQ2EWrr+U5Vddb8vOOcH4mDYrfqZpErv7Icy204mv6s1XoVSXW76/GewhevfXIHxikO1w4bzz60hZBdbsmgaND7+bWOfAZFhkB8U3/A5XrrUBUrDnCFuevG1wJdBTKCy/6k/4ztj/P1YOH/kXb+74zpDHivPP45Lzf5aQ3f4c7dnHLzd9AN0cLPSxtuKdXD/nkwnbvu/o8/y89l9DHit15/LnVV/CabFA/EkM0+Q9mx7icF/8+ykBP1hyJRfkVSRk7zObXmOjf+Qk73dXzeaDsxKbQLjjtR3UB0IjnnPP+YupTk98oOeP6rzthUb6jS3JcEg8cpm9W1m21Gs8uPm0WMmsApn3W9yK+doTEdobhxd5Sc+CS96W+MRHzU9D8XmaMyi93YmnxFrwZ7REifxvC2gnnv1pMu5PlCC57euAwz99DfqGFpGRlxTivGH4MjJixW982L3i98sXDvNfTx0Y93WZHpVnP7Oe/PQU3db18o/g+W+N/zrFBR98Hoqsb29PBpuaN/GBpz9wSs0zz5NHe+i0cNjyguXce3Vqq1wOx7GPf5zeZ54d07mO8nKqn35qStSNe+buPRx8MzFV7+s/cQ4VC6xPuk40dds289D3vjGgbcV1N7H+jvdPjkNTGKt95LQJtc3G1gFBH4Cx0x7ZcOPQ1tNBH0Asgr7vTct2I217Bwd9AEaMwKHHLdtvrX98hKAPQKf1yBMJ299Xc/+wx5raNhAINids+yRbGh8dMugD2Hj8n5ZsP3h8mDp4wPFwB5u7Dlqy35+9Pa2ngj6ILxI90jT+wdVJRgv6AB5sqE3IdlckNmrQB/DLg9aUT19tCQ0I+gB6YiaHe+wphXCSTXUDFVAPtxp0BRJX9tRi5ohBH0Bvd8Lm0ULGkEEfQNdG6yVk9B2B00EfQJ+Bvn/0z3usGB2BYYM+AGNPq233EtjPPa/XJ3SdP6Tx5G7ris5J442fJ3adHoEdf7bXFxt56NBDp4I+YEDQB7C1dSu1/sT6gslE6+yk99nnxnx+7OhRwjt3JtEj+zi8JfFn4Bv/qLHRk4lj1/NPD2rb+Uzi409B4kybwA/XEIIHbptmHl2Di9JKQ7SNF8WZPuwx2TX8sbGiOkdXjlIdid/HOYIiqCyptmz19Izgn1OxZt+rjPz9SLdpqypAmjr4XumqNZGO0fAoia0MuRR5TMIOuRZVPdMcQz9+Mhz2zti6z3BTlsBpYatnsnemjLTIrHpseG+GWNmTPDb+Ua5RVsnV6dPtTEd8FrZaZ3isPROSisuC6qgnyzY37CZjlJQEWZJJs6DePVnILheSc3x9pJxhb3pGslAtPAM9aSn8GxsBl2/wd9DptT6OFoyfadMDy3nZyIv6bY30uFFWLxn+gvHYnrUMqfh0iQIptwR54fmW7TqyKkmbc/2gdjW9lPR5N1m2XzjzOhyu7OHv7y6gaOZbEra/YtGnkYb5Ci2YfQeuMQSeo3F+2c1ku4fe037DnE9bsv2ZWW9F6hfi9A93LspdzOLMGZbs96fKl8W1xae/n1kON++sOFNtdex8cvbwW+VO8tkFidn3qgpXl4xcqkQGPj6vKiH7J1lT4KHYM3CQuTjLQYHNg8dL5jtw9otF1s1R8bksBH6KxJxzRh4cV8xJ/NEqO2Sc+YP9kxyQs8b6e6OuSEPKPf2GyFUu5FnWchL7I6e5kGYOr1irXjZ8GRXB5POtGxLb0ri0PIurFhXZ7I2NXPujsZ+r9As4smfAivfa749N3LHgDvI8p0twnFd83oBA7/b5t1PgtZaWMhnIPh95Hx27enf61VfjmmFfn51Mzrsx8ZJX6++Yb6MnE8eqG96Kwz1wMv2id71vkrw5u5k2OX4nMY63YPYGkGeUIQ21CpggpmFgNuzDNHTkygVIin1iCOHW3Wh9LUiKCwkDd+m5yEOsECWCocdorHmIzmMvY5gS4b56FNVD2YL3UFhxObJi7T0KR7o5UPdXnI50Kksvp7VjO5lplWRn2ifgENPDHOh4kwb/bva1v0q2q5gb53+OHI/1JOeOSA/3H3uBUk8u1xSuZkPXfjJVH8uyrNciHIrd/hZaIwHOzSnDZ3HFr8bfzQc2vcKZuwIr3D5+suJ8Cj3WViy3dvj57aEjHO4LEzEMTOLCLmsLcvnSopk4E1xR7I9hmjx2tI/XW8NcWuLlspLkiEMEIiY1rTp56TIlWfbMd3W16ezeGKW3C7zp4EuTCPaZzF/loKDE+vOhe3sM/zYNxQveKpWs5SqyTauhpmZiHA6BQ0ae4UKyUDpjOLQDbZj1XRhZbsydzeBWcVw9DyVv5FlekeM3PpKh6tnaE+Yb/9zDm/UdhKMaqqJw0Zw8jnaF6AvHyM/w4FEVYrrOjPw0Lp1fyJpZeShJ+B7ZSm8zPP5ZCHbCVd+HPQ/9f/bOO8yq6urD7ym3T++VOvQuiCAiiIC9G02iUWM0MRrTk88U06OmVxNNTKKxxt47oqDSe68DTO/19lO+PwaQYeaW2efOMOh9nydPnLPPWXdz7rln77X3Wr8F5e93CbtkDgVvI5SdDafeDAffh5AXRi4AW+IWRvoDX9jHh9Ufku3KZlreNNqCbayoWUFpaikTssVFvgYDgd27CWzdiqnr2EqH4Fu1CsnpwDZiBJ2vvYap6WRecw0pgjX/ThTNNV6W/28XVbtbuzJyjgyneu/nD5uczaIbJ2B3nryajEGfj+3L3iHQ2c74M88mPW9w1yQcrCRVPY9DLu6fB8lsqUXKKkBOy8ZsbcAwDeTMxHyWM28i5E0k1FJOqGU/Wnslks2FLQFF3GXFhsOZTVredMLBFtLzpiAhEfLVYJim5S1fpyODKWO/dPRvm+ohpPksWu1Oc6CG4rQxpNlzCOkBStMmkOFMzL03MDkjeyJ+PchTVe+TaU/h9KzYu2nx0h4OUhPoYKQnC1WWmZieuOcz3eGk2OWmzu8jSJdgjAyMTUu37PQBjEtPYWJGOoVOB5U+Py2hMOMz0vjW+OEJcfpM06S8I8ycfDdnF3lY1xjgYGeYoQkMZQlpJjtqdEoyZSaXJu51Z5omTbVhNA3sTkhJh9R0iZJRakKcPlM3UVwS9jzQAxCo1/CWg2d4gpw/BaQMFSlFQZIlzLCBvieAlK2i5FtfMDMaOjHbgkhTClBbAnDROCQTpNT+DW9OkhjS3TZOH5XN0GwX5U1eypt8fOWsMl7dWkd7IITLprKlqo1Ul0pDR4Ch2e7B7/QBpOTDtOvh0ErorIfhZ4KhQ0YpZJXBgfehfgd88OeuH96Uzwx6pw/AbXOzcOjCo3+nO9I5d9i5Pc7b07KHdEf6SbUD6Bw9Gufo0QT27MH7wYc4xo9DzcjE8Hop+NGP0KqrsRUlTsF9oMgq9OBwK7jSVBwulZaaANBVRtLUujSFnCl2UtIceNtDZBV7Tiqnr7WuFtPQySz8SAHf4XYz7dwLT2CvksDHcMcv0ZjhIOHn/oxZsQuQID0H2hoAkEdMQb34ywnZ/at9/esEqlZ2O+YpO5+cM+8UVqnS9RArnz8HI4ojNmb2z8kbsljI/rEEQ+289M6VBENtAKS4i7lowVPIsriDENL9/Gfjt9jXsq5HmywpfHXmQxSljhK2/9f9L/JoxTsc/wuQkLh/6u1MFlQ7PcLL1bv47e4PCBk6+Y4U/jD1XIZ5Iofe9oWfbVnLm3XRhRTenH8eblXs2Xytqp67tkUWBPj62KFcMUR8x7UpqPPtNQ3s7whzWCX+6PcwPdvBb07NRbGozra5QuOJ1eGjctmTSxQ+M8u649HWZPDu88GI7TY7LLraic0u1v9gvUHFI8HeV35lKL7KjqtU/HdldugE/1uPWRcGGeRJbowtPjisDyGPcGC/Lk94FzDw+CbYF0F8yK5gu2QcypjIocTJHb++kejxcdX+Jj79j5U93ouxOGtMDv/5/GkJ60fCaa+Be2dCsL1v1024HD71n/7p0wDRGmjllrdvYVvTNmRJ5oYJN/CN6dZSJQaSgzd+Ad+HH0ZslxwOCu78IRlXXjmAvRKns9XPQ3esELr25j+diT1WHvUJxDB0Xvnzb9m9YjkAI2ecxkXf+B6K4FwkSU+Sqp79jL552WGnD8A86vQBGPs3YexaY/kzAnVbejh9AN69rxKoElcP3bv2V1GdPoA9a+4Stn8sa7f87qjTB9Dpq2LbXmsS0qurXuzV6QMwTJ3/bROQ5j7MPm8Nj/Ti9AGYmPx456PCtgH8epg/7llByOiavdcFO/n7PuvPyhFiOX0AX1kTWbU0Fr/ZXh61/c87DwrbBnhsXzv7O7qCVA3o9j2sawqyoj5gyT7Ac+vD3Wokba7UqWkVV/M8wpp3Ijt9AOEQbF8TQZYzDurfiuD0ARhQ/5a4bYDw8vYup++wPWPTR04fgLE/iLFX7P7r1e2RnT6AkE749d2cDAuOn1S++viGPjt9AEt3NdLUGf23cUJZ8tO+O33QFQ7aeXIr0T6842G2NW0DwDAN/r313+xrPTnUIf2bN0d1+gDMYJC6u+7G8HoHqFfWePxn4nOBl/+8MXEd6Qf2rV111Ok78veuY/5OcuJJOn6xOMbR6w2zNXp7PIRbIu+shDuqhe362mK/2A0tMQN1h7eix7G2DmsS0s3+quifGWqM2h6NKn9T9M8+xokVoTUUwKd3n6DXBDos2ewrlX7xQTAcY2Ju1X2q9kcvS1Dts1a2QDdMAr34R81e6w5HMI7KBx0WHMxwa/R2rc3av8FsiX1v4zmn1+vq43jmOkL0qOORZNDQ4hNfWKhtt75g02809lI6KV7ao49Fg53Kjsoex6o6T45/k3/79rjOM3w+tJaWfu5NYggHxMe3lrrEld7pD9rqepbxaqu3XtorSeJIOn4xkEdNh0ji9pKMXDbN8me4h58FUi8S64oDd+npwnZLxl0f+7MthjMeYdSwniqkY4ZfbcnmxLyzuqluHs+E3HnCtqdnlJGuRhYSOTN7krBtgEJXKmNTc7odOys3cYpj8fxwvzRSrHg7QKk7urhQnt1a2Ma8gsgCHzJwep61vBpFlhiS1f3ZUSQYmWf9lVcwJLaN4ePE70/ahOhhnCljreVXKhOOy/883pwE8hixHFFlfG7E1+UR5JFZSHbrOaJJ+oczR4sVh5YlGFcwiOX0p10rdp1ih4LEKISfKBYP7Z7OkenIZEb+yRFNnX7JJXHV0HGOH4+9pGQAemSd4VOjq2ZH47RLEzNn6y9GTD+tW1inrCiUzZh1AnuU5HiSOX5xoO9Zj77pPSS7A2noeMz9W8A0UE5ZiDwsMYpZ/up1NL1/N7q/EcnmwZ4zjowp1+HMtzbg7N/4V6p2PQ70XGFypY3klMUPISuJEdPYtPMf7DnwDJKkMHn0TYwafrllm9vq32NF5TMENC/VHbvQzDASMlMLFvOZiT+1ZHtvZzV/L3+Zre0H8Wp+NAxkZM7IHs8vxt+APVpBtThoDPr4d/k6yr2tnJEzhE8PmYTSi4MvQnswyAXL34wYkjXC7eG/py8Qth/Uda77cDPV/p47wumqwuNzp5Fqs3Z/Xq7o5K1qHxl2mY6Qwe72EOl2mW9MyGRGjnVxmkDY5PFVIQ41GaQ6JT41w0ZpdmIcjhWvB6iv6nn3ZRlGTVYZO138N2UaJvVvhujYanD8F5wyUSZvod2ywIu2rhN9kxcpTUGZk4r2XjvG/gCSW8F2YSZKmfj91w+0EH5he1cRd1nq+p8iQ6oDZVgm6pnDkKKU7Ejm+PWNRI+PQU3niw+tZdneRuKdHthViZduO4MxhYPY8QNYeg+8/zvQQ4AMkgRmpLhqwJ0D170IBSe3MibAS/te4oW9L5DlzOLmyTczKlM8P36g6VyxgurvfBe9uRkkCclmQ7LbsRUVITkdOEeNJucrX8GWf/KI1vz3+x/Q0dy3iKuSsRlc8vVT+qlHiaNi+xbWvvwcpmFwyvmXMGyy9Q2SJB9hdYxMOn5JkiRJkmTQkHT8+kZyfEySJEmSTw7Jcg6HMU0TffVmjD0HkTLTUOfOQEpLiX1hvPbDQfQVL2FU7kYuGIZy+qVIzuj1qPpCoH4rjct+hu5rxJEzntyzf4nisF4AvaHiHfas+SV6uLNHmydjLFPOvh9FFQ+rW7HhlxyofBXDNFBVF7rmR5btTBh9A5NGWyt6a5gGr+z5M6sqn0czw6Tb8+gIN6IZIVTZwfWTf8OYHHEVuaAR5t8H3+S12jW0Hr4/kiThku1cU7qAzw0521L/+xPNMFi49FW0CAs3FxeW8t0JU4Xt+3Wdzy3fRF0o1Gv7BUU53DHRWiHuZw908M/dbfh0E4muCEFVhpk5Tn4+LRs5jvCeaLT7Td7aFmZ3nY4vCHYVzh6ncvoo6zvcmz8MUr6j9zy1lAxYcLlTWI3X1E2aV4bp2GKg+82uDQkTUCF1jEzOAjuKU3zHzwwbaEvb0fb5kTQT7DJSugI+A1wytjPTkIut1RHV9zUTfmkHeEPgVFHPG406Plmz6WRgZ00bF/7lfbQ+pGF67DKP3jyLqaWJUS3uNxp2w7t3wb6lEGj96LjihLRikExoOdi1CygpcM5dMOuWE9bdeDFNk0d3PMqbB9+kKKWI26bcRmla6dH2A20H+Numv1HnreOcYefw2XGfPYG9jR/TNKn40i14ly/regcqCtjtqFlZuE+ZRvhQBY7Ro8n92ldRc3Ji2hsshEIaD/7f+4T9fct1Vh1w8x/OQh7kpVNq9uxi1fNPEvL7mbLoPMbMnnuiu5TkGD42O37ayo3o732klCRlZ2D7wpXCk6/jCb/xIMbWj1QS5ZFTsV36lYTYNkJeDj16LhgfJdXbs8dQdKk1VUxfxyHWvfqpqOekZk1k6qJ/Cdnftue/bNxxb8T2M6b/kqHFCyO2x+Lt/f/izf3/iHKGxF0LlqPKYhP5X+95imerP4jY/tuJN3PGIC1+u+idV/EbUUKUgN9OncmsHLHJ9nXvb6TcF12o4Z4po5iTL5YP9HqVl7s3R1Z/PDPfxc9PsTaQ37skQGVLz/fbF+fZGZ4rHvLZXK+x/KXoAhj5pRKzFostqDQuC9O6KnLyv2u4RPGV4os1oRea0NdFEWFxSDi/UYTkFrtHRquf0L0re4Sp2m+agVyQGvP65I5f30jkjl8grDPuzteFVD0VWWLHz87Frg5S6QAtCH+aAh2xFZG78ZW1kDO4wyIf3fEo96y+5+jfJSklvHzZyyiyQtgIc8GzF1Dj/ejf/aPZP+JTo6PPDQYD1T/4IW3PPBPzPNcppzDsMWtK3APJf/7vfXxtvS+qxiKjwM01Pxm8OXO+tlYeuP0mwsGP5g9X/vAXDJ009cR16mNGspzDYYzdB7r9bTa1YjZbU2bsZn/v+u5/79uEqVtTHjxCoGZdN6cPINS0C0OzppDWcPDNmOd0tOwQtr/34AtR28srXxW2DbCh9o0YZ5hsqV8qbP/dhs1R26M5hSeaWE4fwCPle4Xtx3L6AP6xt6dSXLwsr42uTLauydqz3+Yze3X6AFbss/a73bYm9vW95f/Fi3d39O/WX25iaOL29e0xVOGCJvo+8ftv7G3u4fQBaDtObkn8TwJrDjQLOX3QpaS7ujxKKY8TTeWavjt9AGvEFkYHkiWHlnT7u7Kzkl0tXWWotjVu6+b0ASw52P38wUrH22/HdZ5//Xq0RnGV74FG1OkDaK2NXqLrRHNg84ZuTh/AntViNQuT9A8fG8dPyjguqdymIqUkLhRTSj8uaTg9OyGF2wHUtJ5KVJLNg6RYC7eKR7FTtUVWtoxFWsqQGO3W1Kdy3KUxzylOHS1sv9gVfUdphKdA2PZgYEJ6hvC1jjh2ysemi4dSF8XYTcq0qProdoAzwkZwQZq11152fuzr7RZ+uraM6PdeSe2KQhNFyor93pLjOCei/czedyPlrMS9j5P0D0Msfkcjcgfxd5wxtFf17JgUDX5hitLU7mOlTbZRcHj8KkopQpW6/55LUk8O9UtbfnwRK0pGBkraIBcWOhYLgWiyMrjDPDPye86bMgsKT0BPkkTiY+P4qWfOQMo8/MNXFdQFs5Ec9sTZX/AZcB8OU3K4sS0UlIbuBXvmCDyjLvjogCSTPed7lsNUc0rmk5odXRV09MwfCtufNfUHKHLvkzynI4cJoz4nbBvg4tHfwKVGDg0bkTGNPM8wYfvfLLuMLFvv9gscmdw09Fxh2/3Nt0ZPjNquANePGCNs/weToufv2WWJ74wXL0/x2RFpFEdw/lQJvj85S9g2gE2RuHiaDdtxH5GdIjHfQqkFgHHTbcgxHK/TFonnEWbPt6FEWo9RIG+x3dK7wX5+JqQc9+o/8u+RQJmdainHTx6RhTTquO+vKBVlYjLHb7AzNNvDZVPFJmmXTCmiKGMwO36lsOBO6Itac1oRTL6q//qUIL485cuMTB8JgF22860Z3yLL2fUbzHPn8fXpX8d2OCViVOYovjj5iyesr32h6He/68rr6w171/xOdrsp+NGdSPbEzff6m/mfFV+wvuArg7u0SNHocUw79yKkw4ssQyZOZvLZg3cu9UnkY5PjB12JwGZjC1KqB8lpbbesV/u6htlUg5SZh2RLvH2ts45g005cRTORbdbl7I/gbdtPa+0aAr56DC2AiYknYwSFIy5GVqy9LE3TpLJ2OboeoDh/Lgeq3iQ1ZQgFOYlZJTVMg/LWjbQHGhidfRp+rYNVVS9wauFF5KUMtWxfM3TKfbU0BztwKjZMQJYkJieovmF/ohkGX1v3Aa3BEK2hIAFDJ0VRuW3MBBYXRd+NjYegrvPg3kr2dXoJaWEq/WEmZ6Zxem4mC4vE6xAdy972EBsaA+S5ZVyKQlA3mZPntCzscoRA2KTFa9IZNHDYZIZkJW6tq7o8zN6tGobRtYCraVA4DMadIi7scgTTMAnWG2CA5jfQvODIknHky5ZLOQCYmonZGAaPDF4DKc+G2awhOWSk1MSUvDCafRiHWpGK0lDy4t8dTub49Y3+UPVsaPfzg2e3ENRNLp5aRFg3ONjUycGmAEXpDhw2hSZviM6ARl6aky/MHUFxRuLGrH7F2wSdtVCzGZoPgDMNyhaBGQZXVtex3a/B6HNhmHgd3YHGNE32tu4lz51Hei/CcK2BVhr9jYzMGJkw7YOBwDRNWl94gdC+/aRdeilaZQWOoUOxlZQQ3LcPW3EJSop45NKJIhzSWPrIDg5sakTTTVxuFUMycKc4sXsU/G0hDMPA2xoGE4ZOzOK8L05BGuTCLkfobG4iHAyQWVh8orvysSOp6nkMkiQh5WZhhjX0XeVIDjvS0KKEveQkRUXKix1+KIrmbcB34F18FSvInHoDaor1UEM97Kdy56MEOitwZ4whHGrBNHUwhhxdkbFCWPOi6QH8gQa27fkPmemjyc1MnCCKN9TCxto38IXaKW/dyMG2LUwtWJwQp88wDe7d/yKrWnYR1MPopo4iKVxWdHq/OH5eLcSq5koybE6mZRRafi6fryhnU1trt2NBXeMX2zdR7HQzIcuaOMozB2r438Eajs0+fauuGW9IY15BNjaLztkz5R0sqfVS5FIJmzY0U2dPe4hqX5hPDUtNiPPntEkUZkiATHWLwYZDGmV5CqkWVDGP0Fxv0NrUvQzYgR1QPFwjPcuacqgRhHCLiZomoboUfAdDtK3VcBbJ5C62Wb43kiqhN2voy3zIOSqy4cJs0pDSVZQEOX6SQ8Vo9GHubYbpRSjDre3iJhkYTNPkqXWV1HtD1Lb6ufP5ZgzTxDRMZEXGNIyuyacpkeWxsWhCIbo++BeQAajfAev/C4oDajdDczl01sHSX0JaCWSPhOwR0FoJS34Cc74GYy+IaXYwIEnS0dp8u1t2s7lhM7qhU5ZZxvT86WQ4M8hwZtDga2BV7SrKMsoYmzX2BPc6NpIk4Ro3juDWbbQ/8zT2sjK8q1ahuD1k3/QFZKcT/7ZttD79DO6ZM0k/7+TYXdq9poY9qxuO/u1r78odD7T1nsN3cGszB3c0MGzCyVGrMCVLTPgtSf/zsdrxAzA7fYQefgHaD8vzDyvGdtV5g36Fq2nF7+nY/mS3Y3mLf4e7dI6wzVCghVUvng9m75LBNmcOMy98TnjXr73zIG8sv5lQuLuITqqnlHPPfBC7zVo5jfLWjdy39hbMXuQG0h35/GDui8K2DdPg7PfvwG/0nmRd6MjiuVk/ErZ/PNX+dr607kWaQl3CGmfmDOWeyYuF7X151XK2dLRGPecrI8fx6eFiJRdiqXpKwOsLTsWtijkJ17xXTaUvsohJpl3i+bMTl4fy1rYw7+zoGlhVGT5/hp0ReeIOzmuP+AlFqb07fZ5KSZmY8xesN6h6IogRyb4MI77uQFbEnb/gw/UYe3r/fpUZKdgvtuakGZVthB5a303kRZlaiO3C2BPN5I5f30j0jt9pd71NXXvfCksD/OnTU7lk6iBe3V/9ALz6rb5fN/4SuOq/ie9PP/Hvrf/mD+v+0O3YhSMu5O65d7O6ZjW3LrmVoN71/X55ype5deqtJ6KbcdP034epv+uuXtskt4usz3+epnv/dvSY+7TTGPrQgwPUOzFe/Mt6Kra1Cl074cxC5n92XGI7lOSkIqnqeRz6+u1HnT4A80AV5sHqE9ij2Gi+Jjq2P9XjePPKP1qyu3fdryI6fQDhQCN1B8SVN3fse7SH0wfQ4a2gvPI1YbtHeHn3n3t1+gDagnUcaNkkbPvJqmURnT6AmmAzezqrhO33+LyKbUedPoBljQfZ1iauchjL6QP46z4xxVbDNGOqeprAI/vF7s+u1mBUpw+gJWTyckXP2pMiBMIm7+36SIlTM2DJDnFlz9YmParTB7DhfXH7Lau1yE4fgAGtq2Oruka83KdHdPoA9LWdGM3WlE+198p7KHvqG2swg4lRQk7SPyzZUSfk9AHc9aq4QvSAsOSnYtdtfwHiUFEeDAS0APdtuq/H8Zf3v8zelr38fdPfjzp9AP/a8i86Q4l5z/YXDX/6Y8Q20+en6b77ux3zrVpFqK6un3tlDVGnD2DbMgFl2iRJjuFj5/jRS8FpMygunTsQmJqP3vTPTYvlHLRg7HIW4WCrsP1QOHItsHCUtngJaB1R271aq7DtxmB7zHM6tRiy932gU+v5DPZ2bDBgxBkE0BYWm8S3h+MrWtsa6ltx20iEddCPMxUIi0c6hOL4WVoJpDCCsS/WfRY+IBTHtUFr994MRHg2+lIVPMmA09gp5vQBeAe7U29lPD1JHD/N0Lo5dsfSGe6kM9zdyQsZIQK6tXlGfxNz/mb0fKeYHdHnDkmSfJL52Dl+8qTRcGwIVFoK8oj+y8tLBLa0Uhz5U3scTx13hSW7I6Z9LWq7JKsUjrxU2H7Z0EvoTZdYUZwMKxEPYzzCmUMjK6cqko1xOXOFbd84dHFURWW7pCY0z+/iojEox4QbD3GnMz2zSNieJ5asJDArUyzHT5UlHHEkkF8zQqz/p+Q4ccR48yjAlUOthQofIdUpMb6o+weeNkI8vTm3SI4pxz10jHhoefqU2H3LnCXefzlDhYzIz49UYkcutCb6pJ7aS4maghQkz8mjvPdJ5IpTSrAJysV/bpb1vOt+ZfLVYtdllYF6cjy3KfYUzh3WM8dtTOYYJudO7lG0fUHpAnJilDU60aRfcH7kRknCPat7MXM1Lw9HmViKw0Bhd4lPvbOKEzMuJvnk8rHL8QMw6hoxtuwGux3llPEJrefXXxhhH60b/o133xsgq6RPupa08dYcP4CmqmXsWfsrtFAHis2NaeiAiTu9jFEz/g9PurgkP0B90yb2HnqBjo6DaEaAjNSRTBrzBdISIL4CsK76Vd7Ydz8hw49hGISNADnuEm6a9mfSndaSnHd1VHDHtv9QF2zFoGvVUAKGuPK4f+rtZNgjl5IQYVtbPa/X7iHT7uKy4nFk2q2p4J2z5GW8EX6/k1LS+fusM4Vt66bJ5e+toznUcxVfBu49dTwTM8XrJjUFNL6/rpHyzjA2WaLIpRAyoTWoU+yx8X8TMxmamrjJVlg3Wb1fp77dYEyhwvgiawImfq/Ou8+Het39KxkpMX1+72VO4sV3SKdzp47qkTBMg47NBroPZBcUXGbDXWRNl8sI6oSfb8Y4GERyy8hjXJh+AznThnpqCpLT+pqgtrMB7Z19ENCQR+VgO28UUhw5ockcv76R6By/imYfX/zvWvbUdaDFMT3IT7Pz1QWj+expQwZ3Lr1hwPt/gC1PQrAT/M0QPlZIQwKbB9yZEGgFXYMRZ8JVj5w0jh9AWA/z9J6n+aDqA8JGmOn507l6zNVHlT6XHlrKsqpllGWUceXoK3FYrBfc35iGQePf76P95ZcxDQO1sBC9vh45NZX873wb1/Tp1P/u93S+8w6OsjIKf/ELlLTEjt39wf1ff6fPm9A5JR6u/uFp/dOhJCcNVsfIj6XjlyRJkiRJTk6Sjl/fSI6PSZIkSfLJ4RNfzsE0TfTla9E37UJyOlDmnYoyeliCP8NAW/4sxrq3Por1lxWkwhGoC69FzrGmZBZq2kPTh78m2LgDjI92WJzFs8hbeA+yKr57ULv/RfasuRs4Lg5eUhg7+xfkli4Qtg2gG2E+XP8TKqqXYvJRHoQsqUwYdQOTx94sbLvBe4hHt/yAms69h0VePlqkGJV1Gl+Y9kdkCyUpljVs4Y7t/8boJb8yQ/Vwz4QbmZoxUtg+wBu1e/lX+ToCusbc3KHs6mikwtfOmblD+ebo03EpYsqPtX4fV36wJOo5L81dRKZD7NlZ39jK19bvjNg+LtXNP2aLF5It7whx28p6vMdtKdhlOLfYw1fGZeIQDDkDWHdA4/n14W4pZbIEE0tkLjvFjtNCLTzDMNmwPEzl3t7zfmwOWHilE7tgyQit06TqySDhpp7PpWSHjFNUss5QhXdXjLoQof81YjYeftcocPSn65CwXZCJOlU8nEjbVof2/PaeacsSkO3GfuFY5JKedcaSDA7WHWjmivtW9OkaCfjHddNZNN56CaJ+o3EP/GM+xCVmInH0Ac4dB7et7MeOJYbKjkp+8P4P2NTQJXo2NW8qafY01tatpSyjq6TDI9sfIaAHkJCYmDOR38//PQWeQfydHabut7+l+YF/xT5RlkmZP5/Sv93b/52yQGdrgIfu+FDo2k/fOZPskzzcc+/aVSx/7EECnR1MnL+QMz59HVKCavcmic1Jf6eNLbvRV2wEnx+zuRXthSWYHdaFRbp/xnKMNa93T/A2dMyqPWgv/g0ru6amaVC/5HsE67d0c/oAAlUraV13f4QrY+NrL2fPml/Sw+kDMHV2fvgDzCiqn/GwbfdDHKp+u5vTB2CYGlt2P0B900Zh2w9v/h7VnbsxMTh+FrmneRXLDz0ubDtsaPxfBKcPoFXz8o0t9xM0wr22x8MBbws/276USn87jSEfz1XtYHt7Ax1akFdqdvPP/euEbV+7Ymkc57wrbD+a0wewo8PHG1UNUc+Jan9VQw+nDyBkwIsVXh7ZF1t8JxKdAZOn14Z76IgYJmyuMHh1s/h3CrB/mxbR6QMIB+H9V8RFMmpf6t3pAzBD0LJSo2OLmNiEaZqEHj/G6QO6/XSDJuFnmzHqxISHTM1Ae64Xpw+6jjX6CD25BfN4tZ0kg4Yr++j0QddX+8X/rqNzMAu8/Oe8OJ0+6PYAN+yA5wd3yQOA7y3/Huvr16ObOrqps65uHUsrltIR6mBD/QYe2PLAUSEXE5MtjVv43vLvneBex8a3YWN8Th+AYdD5zjs03v+P/u2URR7+Yd9/Y0d44uerE9iTgaezpZmX/3A3zVUV+NpaWf3C02xZ+uaJ7tYnipPf8as4TtrWMDCqEivla1TsjthmttSBN7Z6ZiR0bwNaR2XEdn+V+I+8rWFjjDMMOlsi/9viobZhTdT2mgax/ge0Tmq9e6Oes63+PSHbABX+hoilIo7gN0Ls94pLJ29qrYv6CRtbxW0HelEyO542zZqDE4tXqsXKUWiGSVsMZc9NzeKOU0VzdNvlDdacjqba2Nd3tokvBgVqYl/rrxD8N3TomHGUajAOit1/szGORTdfGLOp9yLFSU4s3qAW460YGRPYXi2+YNPveMUXqtgXe6HtRKIZGhtjjvc9WV+/PvGdSTCdS/t+7zvffTfxHUkgRjzJsx9TanbvRNe6j0GV27eeoN58MjnpHT+5MLf7AUlCLkisSpVUGEUAJTUL3OIiF4o7G8WdG7HdkS8eTpeaNT7GGRIei8qVudmTorbnZU0RsutUU8h2RVdjLcs6Vcg2QLErJ5YwIzZJZag7X/gzxqVF/l7jaY+GLY4wP49iTcAkFvPzxYp8q7KER43e/7EZ4mIKRZnRX2slWdZeexk5sa93WojEceTG/m4dhYL/hhQF0mI/F3Kx2P2XsuIQ0nIoSJnWhI2S9A8eh7XsjzH5g1hUw5khfm2J+FgzEKiyyrisvhf1Hh9zjnDi8cyeFfuk43CfOrhThKX+HZoHNfkjypCOS9EpGDnqBPXmk8nJ7/hNGYc8ZWxXCQe3E/WcM5AyxB2x3lCmzEeaMKfHcSmrANsFX7QUmyzJKrln/Rw1fUiPNlv2GDJniIeYpGSOYdikyNePnP5dZMWaWtnE0TeSnzO9lxaJsqGXU5gnrkB1zaSfk+7o3fEqShnN2cM/L2zbIdv47qirorb/cvz1uC0ono1OzeZro2aTqjqwywrzcoZR6EhBAuZkD+FLI8QHpwdmxlbs/Oep4uUufjQxuhx2gcPGpaXiuSH3TM/BFuFnc2a+i+tHiv+G010S505Se3XsR+ZKnD9ZLK/yCGWTVLILIztnkgRzzhP/XRVcaEeJ5DhKkDZZIX2K2MxBkiXsV+WAJ8LNl0E9JwO5WOy5l+wKyqIoebEeG7bLJyDZPsEzn0HO36+ZJnTdXZdNIN1t7bfVr1z7LMgC/UsthCv/nfj+JJhfnvFLhh+j0j0ifQRTcrsWXoelDeOSskuQj5nylaaW8su5vxzwfvYVz+zZpF18Udznu6ZOJfdr0UtZnWiu/r74QsKFXxHfDBgMpOXmsfiWr+JOz0BWVCaetZgpiy840d36RPGxUfU0DQMkqV/lpE1Dx9B1JEVBMk0kJbHaOKahgSRjhP3IqgNJTox90zTQwgF0zYeqOjFMCbvDkxDbRzAMDRMTCQnd1FBkG3KClrU0I4yEhGmaBPUADsWJKiiK0hstwQ5SbC4wu3L/ZFnGadEhPhbDNDFME/XwAoFmGEf/2ypNPh87mhoJGhot4RDZdgfTC4pIsydGorvO6yOomxiGgV2GkCFRkuZBjaPOXzx4wzpOVUYzTGyyhGGSMNumaRLUDGQJJElCliSUBNmGLpEXvzcE0uH3jwlOpx3VkZjn3tC6bCKDETaQ7TISElKi7o9mYuomskPGCBuYkoksywmzr3mDSHbl6DtZkiQkJfZzn1T17Bv9pepZ2dxJhtOObppoponLrqLpBpgmsiTR0Okn1+PErxnkpDoHdymHYwl0gGIDPQzhAKhOsDu7yjcgdRV6d2d0tZkG2Ad/OahjCetdIf62w2NkWA8f/W/DNAjpIRRJOXrsZME0DLT2dmRV7VpdkyQUtxu9owPJ4+kq12EYyPaTp/RGR6OPkKbjb/dhGiZebwi7046vNYQz3YaCRE5RGh1tPux2lZzijBPd5YRhmiamYSD3c2TSx5FPvKrnUUwwtu/FbG5FLhuKXGStxls3060NaBuWQEsdlIwGTMz9m5Hyh6GecRmSLTGTbElWMUJeWlb/hXDrATyjziNtzCWWbFbufILyzX8BUwPJjiSpyLJEStZYRkz9OimZoy3ZX7Hh59Q0rMLtzEORHehGEFlWSfWUMmnMF0hxixcp1w2N/237GVvrl2JioEg27IqLMdmzuGTst3Gq1p3X7W0H+cGOh+jU/MzOHEdjuI36YBvzcybz5REXolhQDTVMk6X1+3m/8RANQS92WSXb7qLEncY5BaMosBIPCMx/+yV6zdbavZXbR47j6uHiRWw1w+T2NdvY2tZTDEEC/nzKWKbmZAjbB/BpBk8f6GRjc5BSj0pDQOdAZ5gJmQ6+Pj6DFIu7QpIkoRkyGw5qNHWaNHYY2BSJs8erlGRZs31oT4gNy3oTWAmRWyRx+nnW6vj5K3Wa3g8TrDMxj+isSKBmQP5FNlz51l7d+r4A+j4/Zk0IozGMnG/DdkE2UmbiJu+KJKGtqcI42AohHbkgBXX2EKQ0a/cmSf8S1HQ++8+VrD/YejTfz65IyLKEXZEJhTUChx99RYKy3BQumlbMl+eNTOjCSr9QuwVe/Q7UbgVMcGeDPQWaD4B2JD/1GEXP7NFw42vgGdxFzms6a7hv031Ue6s5q/QsdFPnUPshJEki05FJ2AjjVJ2EjTCptlQuKbuEdOXkUNYNVVbS/tJLhKqrMYIhQnt2o7e0YsoyituNkpODVlOD4fUipabgmT6DvG99EzUz80R3PSov/Xk9h7a39umaCXMLmX9N30N6TwSGrrNt+TvsXfUhrtR0pp17IfkjPpqTVO/aQfnGdWSXlDLm9LnIctIBHCg+Njt+4effxthVfvRv9bKFKKOtFScHMJqqCT/yc4gklJGWg/2muxOy2mkaGhWPX4QRaDl6LHX8p8ie/S0hewe2/oOKbdHVsCbNv5eMfLGFg5ff+QxtnfsjtsuynQvnP0ZqSvRcvUj8+oMrafRX9NqWYsvkh2e+YmlXcXdHJdet/23E9ompQ3nglG8I2//trg94tmp7r22pqp3/nHoZRS6xkMa5b78UU4ThzvFTOadI7N5ftHQNreHoypFPnDGFYrdYrpZhmtz4fi3lnb0LjaSpEi8uLLb0uwqETf70VpBWX8879cV5dobnij07NQc1Vr8dXTjHlQqLrxK7N537NWqfiW6/5Ho7zjyx/murOgi/0tKzQQbH7YXI2dZ3AsygRugfazDbjqtQbFdwfGkmUnpk5y+549c3Er3jN/knr9Me6Ltq7NyyHB6+aRAXl67bDn+f3ffrJBnuOASOwZm/WNVZxaXPX3pUsTMeSlNLeebiZ3CpgzvXNnTgAOVXfgqjM1411i7ktDTK3lmCkjI4yx488uMPaavrY/X2w4yZlc/CGyYkuEeJ55U//4adH3wkwCdJEpfd8ROGT53Ojvff5dW/fDT3mjDvbM69VXyu9UnD6hh50uf4AZjtnd2cPgB97baE2Da2LI/s9AG0N2LWRHZ++oK/anU3pw+gY+cLwvaqdj4a+5zdTwjbj+b0ARhGiH0VLwnZbg82RnT6ADrDLexttjbZ+dO+6Pd2a8dB2sNi6oM+LcyL1ZFLInRoIV6t2SNkG3pXyz+ee7ZvFLLdEgzHdPoAfrpRvP+bm4MRnT6Ads1kZYPYwHiELZV6r04fwDs7xGXnN74fWy3V3yFsnpYVsfvW/IG4Yqv2YQTlRQP09YkphWPsbOjp9AGEdPQttQn5jCSJZ299p5DTB7B8byNt/v5VErbEu3eLXWcasOXpxPYlgTy/9/k+OX0AFR0VvFvxbr/0J5G0Pv10n50+AKO9nY433+qHHiUGUacPYNfKxKrW9wedLc3dnD7oCu3c8NqLAKx7pfvca/uypfjaxdXxk/SNj4XjR2/5UokqBhnP9nOCtqh7y+k7Xv2obwZj75ZIIsnufUCWxELS4inMrgjaPoItju9NNNRTPpxTFt12/4ZFKTF1S3sn3mgtu4Wwrnjy+OwWf8LR0sniSDWLSH+nMsXzyEkWittH/YITFW0T7QYP9nDATzA2C8+VxCD/aq3ktCUw5zvRqILjoJogDYF+RRXvo2Q7Cf59H1O68vZ6vgzkw9+nrHYfaCRZSoZ6DiAfC8dPSnEjTx7z0QFZRj0tMcpHypR50ZO7c4qRC4Yl5LOcRTNQUwq7HUub9Flhe0Mn3RLjDJmSsdcI28/JjF7KwaZ6KBsqlqOYYs+iOHVsxPYsZxEjMk8Rsn2Eb5RdHrV9VuZYPKpYPpJTUfl0aeT7k2N3c2HRmIjtsYjnFfmzKWKRAOl2G4XO2BOdn0wV7/+EDDsT0iN/Rq5DZnqOtTCkicUKeak9Bx8JWDhefBI4/azY16aLVboAIHtubPvZZ4hPatQz03obk8EG6vTEhEbJY3KQcnvJwXXbUCYX9jyeZFAwNNtDXopYzvr5kwpIdQ5iwZAFd4rp6Mt2mBh9rDiRXDbqMlLtfQtDHZM5hnkl8/qpR4kj86qrULL6/jJVcnNIXbiwH3qUGPKGi4cNT1kolr4xkLjT0pmy6Nxux2RFYcaFlwEw85JPdVPDn7r4ApyDNCz348jHJsfPNE2M/ZWYLW3II0qRsxKXuGz62tG3foDZXItUOgZkBXP3OqSikSjTFyIlcKXC1EO0bn6EcPMeUkZfhLv0dEv2GqveZ9fKH2FofhR7GorqAlMjI+9Uhk76Ik6PtUnYll3/5mD1W6SnliFhoBs6siSTmlLK2BGfwenIELZtmiZv7vsHH1Y+g2FoOFQ3DtXD5LwFnD3iRtQE7FZW+5v54fYHaQq3c1H+aRzyN1AVaOL8/FO5ovgMy/bXtVSzsrGCppAfmyyT43CT6/CwIG84aTZrIhdXvPs6dRHCkP8w5TROzRUXODJNk7u37uWNmiaOLxVuAx4/Ywr5gvl9R9AMk9ervKxrClCWYqMhqLGjNcz0bAc3js5IiLpnSDPZUqnT7jepbzewqRLzxypkeaz9Zpvrwyx/Wes15nbYWJkpc6wJPoWadZo/1PBXGug+jqp7Ogsk8i+wY0uztmZn1ITQ9wcwGkKYtWHkYge2BelIFu/LsZghHX1HPUZFK2ZQRylIRTmlCMkV/XebzPHrG4nO8TMMk28/tYmXN1cT0rse8Cy3iiRJuOwq4XCYusNh2qkOhSmlmVw2rZgrppckrA/9RlsVvPlDOLQSTBMySsGZBvU7ob266xzZBkaoK5Jn6Fz4zGODXtmzLdjGw9sfpqKjgnOHnYtP81HVWYWMTKYzE7/mJ8WeQkAL4LF5WDR0EU7BRc2BRmtpoeONN9AaG9FDIUK7dhOur0dSVRSPG6W4BK28HL29HSUrE/fMmeTceCOye3B/Z+8/vZtNb1f26Zozrh7BlLOG9U+HEoxpmhzYuJbdq1fgSc9g4lmLycj/qARUU2UFBzatJ7t0CMMmi5WQ+aRidYz82Dh+JzOmHsIIdSDZPJhaAEmxYxphFEdinNfGyvcJemtQ7akgKciySkrWaFwpxQmxHw53Egi2YBhhOrxVOBxZZKWPQklQeEx1+y4Cmg9FUjCBFHsmDtVNqiM7IfaP0BBsI0V14dODZPdxBTWizYCX1pCfIncaHjXx4UK3rHiXPd4OVCBFUTFNOLuwmNvGWd/xDoQ1niivYltrO4UuB21hnYBhcGFJHnMLxIvPH8EwTXa2BjjUqTExy8GutiBDPXbK0hOjknuEsG7iC5rIsoRpQoqTmGG48VBVHqRit4Gmg80GSDBklELhUOvfs2mYBBo0vOUaslvC5pHRveAeqmBPT4xzZmomZquG6dMhy4YMSCmJD7cJt/lhfwvypHwUNbb9pOPXN/pjfPQGNDZVttDSGaTFH2ZIlptsj4Ot1a0caOzErsi4HCpuu8K4wgxmDMs6Oco5mCbsWwZ1W2H0QqjdDqobfPVd5RtkFcI+cKXB0NPB5oE08XqlA01roJXmYDMj0kfQHGgmoAXIceXQGmwly5l1coR3RqHt7bdR0tKx5eUSqq4GhwNnaSmKx4Ph96M1NmIfMeKkKemw8vndVO5tpa3Zh6LION02Qr4woZCBrhlIEtgcEOqE8XMLmXvlyaHomaR/STp+Jzne/W/R9OFvMILtXck9pgHIIIFn+EJyzrwTSTA3wddRzbpXL4vYrjqymHHe49gs7Mqt2fxbdh94qte2mZP/j1HDxENk2gL1/GbFVYR0f6/tZVmn8sVT/ips/wgHfXXcse0/lPtqu+oFYjIlbQR3T/g8WYIOYEDX+NK6F9jT2Xz02BXF4/nWmDmW+wvw151beKLyQNRzfjdlBqfliu3o3rNtH69UNUQ9580FM3AJ5mBsbQnylZX1vYrUuGSJVxYXJyQHck25xosbwmjHbFumOOHTM+2MFFTF9LbrvP1UKOo5Z1xoI1uw5IK/SqfqiRA9tloPo6TAsC85LdXbC2/uRHu2ucdnyMMd2K/OQXJbdwBN3SB47ypo/0jIQJ5RhP3c6CHCScevbyR6fPz+c5t5bFVkYa3ekIHnbpvDlNKMhPUj4dRuhfvOID5prGMonALXvwTOwV3+4JtLv8lbh7oETRRJQTe7RHqOjGl5rjzunns3MwtnnshuCuHbtp2DV1wR38mSRN73vkf2dZ/r305ZYNVLe1n7yiGha6+/ezYpmYNbjTVJ/5JU9TyJMUJeGpff1eX0wWGnD8AA08C7/00697wibH/zki9GbdeCzezb8Cdh+7UNayM6fQBrtvyGYEhcqem/m++I6PQB7G1ew8Za68pdv9v7LOW+LqVB8/CkYFP7fh44+LqwzYcPbuzm9AE8U7WdDS014h09hlhOH8C3NolNBn2aHtPpA7jhw81C9gHuXN8YcfrlN0zu3tQkbPsIHQGT59d1d/oAOgPw9NowhuCi17KXozt9ACvfFFc3rHs5stMHoHdC8wpx+2bAQHuup9MHYJQH0ZZFUP3sI9r66m5OH4CxtjohtpP0D4eafH12+qDrUbr5v4N8cfbRT9Fnpw+gZhMs/0PCu5NIPqj64KjTBxx1+uCjMa3eX88PP/ghhhnl5TJIOXT99fGfbJrU/+pX6B0WpJX7GVGnD+Ch769IYE+SfBJJOn4nEK2zGlOL7NgAhFr2CtsPB2NPnr0tu4Ttt3ZE75tpGnR4+xbDfiyNvtgTkP0tG4TtH2Gft3dnbF+nuJO2rb13x2mft7nX44OJQ97oz+QR6gOxHaDe0AyT5lD0yceW1qCQ7WNp7DAi+k+tPpOQYEWHUBxK3JrYrcHUTbQ4/K5AtfjkzWzVIIpiv1GXGEl+o6r3f4gRR6mQJCeG3XXik+WmTsGHfqDosFBGpGZT4vrRD2xp3BLXeTXeGjrDfS+PcKIxvX0sM6PrhCvF5x6DmsEfpJdkkJN0/E4gtozhKJ7o+QOuEnFxl5TM2PHg2aVnCdsvzJ1J7/KAXaiKm8z00cL2R2fFDkk5tfhCYftHmJ3Vu3ro7CzxePpFeSN7HJOAUzMTk1cZD6LSN2PSelFj7IUZWWLF51VZYnRa9N5dNsR6jmVJlow7wscMyZJx2sRCJTPiSC31iN0aJEXCWRy7X2kTLcic59rAE/nVr4xKjOiDOqF3cSHZlpTtHqycOixLsAgMjCsanAXOj1JqIcRx3AWJ60c/sGjoorjOm5w7mTS74MvpBKKW9E04SHK7cYwa1U+9SQAWshjcGSdH/mKSwUvS8TuBSLJK/uLf4SqZjeLOQ/HkH/1/W+ZIsk7/riVVzyln349qz4zYnl2ygKHjPy9sPz11BHNn3I3L0VPow2HPYtGcv6NYUN78zKSfUZo6vtc2u+LmvJG3UZrWe3tf+MbIy7ms8HTy7Blk2VIpdmZz/ZBFXDtkgbDNC4pGc3XpRGySjASkqw5+OXEhQz0ZlvsL8OhpZ8Y85/X55wnZliSJu6ZEHzRTZZnfzBC/9/fMyCXf2fvoNznDzqdHWJ+c2BSJz891MCRLwqZ0lZZz2mB8kcRnZok/l3MvckYtCSarMO8ScYGagosdqFEUzFMmSKSOs+D4KRKOG/Ig9xgbEpAqo85PQ5mVmAm8MioHaeoxC1sSqJ9NTJmdJP1DutvG3685BXsfffOidCeP3zyrfzqVKD77BHjy+3aN6oLZt8GML/RPnxLEyIyR3HnanaTZ07DJNopTikm3p+OQHWQ5s8h357No6CJ+N+93J7qrQox88QXktAhjgiQhZWZ21fyTZdSiIoY8+CCShRqA/c3Vd4qnMH/+Hutq40k+2STFXZIkSZIkyaAhKe7SN5LjY5IkSZJ8crA6Rg7eJZE+YrZ3oq/ejOn1I08chTJySOJsmyb6mjfQNy2FoA9kFSkzD/X0S5GHWpfXbd/6BC2bH8UMtNAVwC2huLJIn3I9aePjVLKKwP5N91K187+9tg2ZdBtDx19nyf66rX9k1/7/YWIACnZbKrruR1XdTJ/wNYaXiu06AQQ0L0vLH2L5oSfQzI9yvmQUTi2+mEvHfBslAfLU/yh/lYcOvYWOiYzEnKzxfGf0p8izoHYK8F59Of8sX0d9oJOgroMEWXYX1wyZwuUl4y2VFAgbBme9E1n4xw68s/AiYfvNgSBXLttAb9leDkni51NHMTvXQpVyYHWDn8f2d3CgI0TYhBSbzMJCN9eVpeFQrAcjlDforC7XafMZNHeahAzIdEvMGKZy2kjF0v3ftSnEzrW956rllcDsc8RV10zTpO71IJ1be1+Uy5glkzNXfEfR1Ey0lR1o233QEIaQ+VHeiA3Uy7KxTYwv3Lc3DH+Y8HPbMCvaQDcBEyQJFBlpZBb2c0cjeZLhSoOVLZVtXH3/Cny95GIqdE8PlYFUl8qckdl899xxDMsRf24GhLd+Ah/+Bcw4E3xlFaZeCxeLi6ANBNWd1Ty47UFaAi2MyBjB/tb9ZDmzuGHCDWxu3Mx/tv6HzlAnZxSfwa3Tbj2pwj2NUIimf/+blsceR29sBFlGzszEaG0FTUOy2zFdTqRgCNnpJPWcxeR/5zvInsH7LPo7Q/z72+8LXXvbfeKRSAPFiqcfZ9Nbr6FpIZwpaXjSMxg5fSbpefnsXvkBqdnZpObkUbVjG1nFJcy48PJkAfcB5GOx42dqOqF/PgntHyUt2z51LvKI0oR8fnjVKxjvP9dLi4Tt6u8il4jHkrfveJbmD38dsT177g9JHS2Wx1a563+Ub/x91HNmXvwKDleOkP1d5U+zdstvop5z9uy/UZA7Xcj+vzZ8nV1NkRWspuQv5JpJvxSyfYT/HlrC38pf6nG8wJHF06f9AFUSy0d6v/Eg3938ZsT264dO5UsjTxWyDXDG2z37fDx5dgfPnrlYyP68N1dGE5YE4D+zJ1GWKja4rmsM8M01vQvgLCh08+Op1mo0VjQb3Lc0iBHh9TZ/rMo5E8XCPVubNd57LroAyphpMmNPEXPOGt4N0rYm+t0v/JQNzzCxRY/QC03o66KLJTi+XoicJXZ/An/5ENqiiPNku3DcclrEum/JHb++kcgdv86gxsQfvyF0babbxrLvnkWqUzyMul9Z/gdY8hOxa2fdBufeldDuJIqgHuSCZy+gzlfXoy3dkU5bsLuy9vS86Tx43oMD1DvrVN/xPdqef75P13hOP50h//5X/3QoAdx7yzviF8tw298Gr/O38rn/8cETD/fpmuKx4/n0TyPPg5N0J1nOATAraro5fQD6tj0Js29sXhbpk9F3rLRku2P701Hb27dHLpcQi+rdj8c8Z8cH3xe2v233f2Lb39e3F8ARvKHWqE4fwJb6pUK2j+W56t5X3WqDzWxuKxe2+3pt9OcvVnsiqA+JKWM2BEIxnT6AlyrrhewDvFkd2fF4t8ZHULe2ILWpQovo9AFsOCiuLLnhvdiql3s2iatudsRxbcPb4sqb+iZfzHPCS8XKsJi+UHSnD6DJj1l38ikLfhJ4dr24EmKLL8x7u2OXgTlhrLpf/NoNjySuHwlmdc3qXp0+oIfTB7Cufh01FhSrBxJT12l7+eU+X+f98EP09sSUpRl0DPJqHFvfibzgHYmqndtpq7egupukT3wsHD88PcOqJI87gfYzIjZJHmtFXRV39J0N1d1TOCVe7M7YoXieTHHVTacj9q6M29XHZPrD2BUnDiX6d+hSrYtQZNgi28gWLN4OkGWP3vdsRwKfzwTjUePb5cxziofrZTsif0aaTcZm8c2UGkE45ggpFoQrU9Jjh4iq4pGYSHH0zRZHHyLaT4l9c+VcwRBqmxKXYl0y1HNwUppl7b2Ul5oYRdh+wSMW2QKAO7JI2okmp48ROw7ZQaqFsW0gkRQFNavvKQWSy4XsHMTP4scYZ2rfw4gVmw2HJxnqOVB8LBw/OS8becoxkvwZqSinTkqYfdtZV4PSy0QoPRdlqng5BICs2d9GUnqfBEmKg6zTvipse/TMO2OeM2r6t4Xtz50RPcxSVVxMHf8VIds2xcl5ZbdFPeeSMd8Ssn0s3x99da/Hryw6g6FuMacV4LNDJpNh633gscsKXx5pQVocKLDH9ixuLeu9TEUs3KrC+BglHdJsKpeWit+fK4alUuTq6fxJwK3jMizl3wHMHK5SEME5silw3iTxcLTp82M7LXMvEHdsCuK4tvBScc/Sdm5mV7JWJOwS6hyxBS3JpiCfEr1kiTJnKFKqBc84Sb9x1pg88gW/mwsmFTJzuLW8337lsvsQ1tG/9O8J7UoiGZc9jstHXX70b1X6aK5yzrBzyHR0d1pvP+V2UuwnzyQ7/47/A7lvU9X873wbyT54F5dUl/j4NmyKtTSI/mbRzV9BVnoOMLKi4Ez5aMFBsXV9P5Ikc/qnrsGZdPwGjI9Fjt8RjIZm8PmRSgqREiAOcSxmKICxczVmKACygpSZjzx0PFIfX0i9YWhBOne/TLizBjPUiWRzY08fgqfsPGQrWweArofYu+63tNWtQ9fDaMEGkCSyCucxYe7dlvuu6yFWb/41za27Kco/naz00TS0bCLVXcLo4VdGzOOJl9ZAHTsalrOq6kUkScImOylNn8D8odeS6kjMJCOgh/hH+ausbtnN5LQRfKrkDIbHqK8YD2FD5/2Gg1QHOgjoYTq0EBPS8piVXUqqzfrE942qA/x8R++Fe58//Wxy3NZW71c1tPCDDbs4NnAvW5W5efRQzivOs+ycaYbJxuYAVV4Nv26SYVc4NcdJtjMxdd4M0+Rgo4EqQ127iT9kkpMqMSxHwWW31neA9csC1Bw00TSOht+kZcG8S5zIsjX7Rsik7o0gwQYTNR10H6CBI18m/zy75d+V2amjVwcxWzT06hCmX4dOE2WiG/vp1oUfjLoOtG31mEEN3HZk0wAklMkFyDF2lZI5fn2jP1Q9n19fwb3v7mNsfiq6YbCjtgObInP7WWU8srqC5s4ALrvKtNIMhmR7mDUymwlF1qJfBoSQD975OZS/D4408DdCazXoAbC5we4BQwd3NqQVQ3oxnPMLcAz+Semelj20BFqYlDuJzQ2byXZmU5ZZRlAPsqJ6BS2BFmYWzqQ4ZeBqySYKrbER78pVdCx7D9nuIP2Si+lctpzQwYO4pk1FTklBb2hEdjpIO/98bAXWx+/+Zt0b+1n53IE+XfOp751C3tCMfulPIgkHg2x681WQIKOgEFlWKBg5CrvbQ9XObaRm55CalUPVru1kFhaTnie+iPxJZFCrekqSlAE8AEykSzfuRmAX8D9gGHAAuMo0zZZEfJ5sUWUwGpLdiTxuFmbNflAUMAwwDaxumpqmgffAUnwV76O4cnAWTMGWVgqmgSRbnwBLSAQ6K9G0DhTFg+rIISN/OkVll2GaBpJk3XFN8RQjSQrBUAuHapaQn30KI4ZcYHlyCqDKNnI8Qzmv7FY21b3NgdZNVLZuQysRz3E6loO+Ol6pXU19sJVT0kfQoQd5s24d1w45G49qLVTEJiucmTeMrW31pNucDEtQDb8jzM0rRtmxheOz1RyAkoAFiY1NbRyfrdWkGSyprOOCEusv6mpfmPdqfexqDSFh0BE2eapc4Ren5FDosSYQYZom26sMqlt1RufLmJJJR9DAkaDi4bpm4Os00UJdwn/GYccvp7BLwNIqIb9GoMrEBPROUNxddmUbGLqBEmc4biRMv47ZoCEV2bHl2dFrgpgHgsgTxNVIu5HuRPbYIdOJlOsBzUTOdCGlJ8OvjjDQ42NfGF+UztxROdS2BgibcP6kQtYfauXpdZV4gxphw+T6GSVoJgzL9pwcTh+AFoCG3WBPhWAnBNohpQByR8HBD6CzFuzp0LwfvPWg2sDiODBQjMocxfbG7by07yUUSaE0tUvcrsnfxMH2g8wqmEWDrwF/2E9ZZtkJ7m38aE1NdCxZgm3oUIp/9Sv8GzbS9tJLpF9+Oe5JEwlXV+Pfvh3T78c5evRJ4fQBjJiaz5pXD6D3IRXfnjJ4dzGPxeZwMOOiy/C1tbJ/wxr8HZ14MjLJT89g6KSpADQcOoBpmrTUVmN3u3GlnBzhxx8H+nXHT5Kkh4Dlpmk+IEmSHXAD3weaTdO8R5KkO4BM0zT/L5qdwVCnyKg/RPjpP4C/46ODaTnYr/4OUprY1rse7KDqqSsxeknABlBTiyg4/2+oKWIvsvamHWx6+4aI7e70kUxecB82QWnn9s5DvLz0akyzZ7axJNk498x/k5UunkO4ofYNntz2c3Szdyfv3BFfZsGIG4Tt/3HvczxR9V7E9r9Ouo0ZWeKKrc0hP19Z/zIHfK0AXFw0ljvGzhW2dyxLqiv48faNUc/5ysixfHq4WP/jUfVcsnAmdkEH87dbm3mpIrLAy2eGebhlnNhCTjBs8vs3ArQHem+XJbjudBtjCsXWvVobdd57IRT1nPM/58QmuKtYvzRA+9ro7+WSz9lxFog5f6FXm9FXRhZXUealYT87Q8g2gL63ifATm3ttUxeMQD19aNTrPyk7foN1fPzaExt4YWN1n64ZlZfC618/E8XiTne/sv4ReDF6+kBEbnkfChKXPpJowkaY296+jRU13QXRTi88nQ9rPuxx/oUjLuTuBET89DetL7xAzR3fgyPzVKcTAh+92O0jRxLav/+jdsAxdizDn/zfoA71XProDrYvFxPYGTe3kAXXWC8j1t/s/OA9XvnLb7t9N8Onncql372TV/70a3av/EhYT7HZuegb/8fI6aediK6edAxaVU9JktKBM4F/AZimGTJNsxW4BHjo8GkPAZf2Vx8Sif7B892dPoD2RrTVrwrb7NjxdESnD0DrqKZts5gqJsC25dFz4Hxt+6jd+6yw/RUbftqr0wdgmmHWbxOvfWSYOi/t/kNEpw/gzf3/ELbfofn4X1UktdYufr7rUWH7AE9WbD3q9AG8WL2TXR2NlmweIZbTB/DXfTuFbFd6fXEJh/10k5gyaXlHOKrTB/D4gejt0Xh/jxbR6QMwTHhhQ5x1vHph7bvRnT6AHetinxOJWE4fQO2LYvZNv4G+Krqipr7Mmhpe+LXdEdu098ox/YnZrT+ZGazj4/bq9j47fQB76jt5eVPfrxtQXvmm+LWPWKun298sPbS0h9MH9Or0Aby8/2XW163v725ZwtR16n7+i26Ow7FOH0Bo377u7UBw507a3+i7suRAIur0AeywcO1AYRoG7/zn/h7fTfmGNax96dluTh+AHg7x7kMPDGQXP9H0p7jLcKAB+I8kSRskSXpAkiQPkG+a5pEntxboNWZMkqQvSpK0VpKktQ0NJ14i2uxs7b2hI8LxONA6Y8vX6j5xR0ELdcQ8J+gXt+/zR/9efH5xuX/dCOMNRZeUN3oEOcZPe9iHSfQJdrsm7nwANAZ7Xt/bscHGvo7Ycv8A5d74zjuexqD49xYPzZ2xHafOoHikQ9Af+xxvW//mTutRHNtomH6dGI997PZYBKI4drqJ6Us6fgzS8bGuQ/DBAg40DfJ3m2HhuQuIlTcZKBpijMW9UW9hfB4IzFAIwyv2TGn1g/vf9nFH13UCnb3PP1tre18g6mxu6s8uJTmG/nT8VOAU4O+maU4DvMAdx55gdsWZ9jrNME3zH6ZpzjBNc0ZurnhJg0Qhj5vV+/HxvR+Ph5RRsQuze0aeI2y/cOQlMc6QyBsqVuAbYOyIT0dtLxsa6/MjY1OcTMybH/WcHFepsP1iVw75joyo5yzOEys8f4RF+d3zKHLsbqZnJiaxfrg7duH0PEEBmXkF8cmD/2DCSCH7UzIdZNiih4RlWYjSmV0WOwRy6hDxHLkR42OHiI45RTx9Op5yDmkTxfovZ9kgPca1GdbyB+UxkZ8fqSgVOXvwljIZQAbl+Dh7RDapzr4/u7IEn5k5JGH96BeKThG/dtr1ietHP7CgdAEOpef7vrdjABmODOYUzenvbllCdrnwnHlm9JN6S6hWFFIXL+qfTiUIm1N86i33qzJHYlBtNspmnt7juM3hZPqFl+Pw9Jy/jJs7fwB6lgT6McdPkqQCYKVpmsMO/z2XroGtDJhvmmaNJEmFwLumaY6JZmsw5PgB6JuXoe9aAwEveNJRJsxBGWMtFcVbvpTG5b/ADB9e2VLd2FILUFMKSRl1AZ7hCyzZ37T0Ntrre947V+owRp7yLTILrJUVWL/tr+wqfxLD+ChDWVVcTBz1eSaMtjZYhnQ/7x54hH0t66j3HsAb/kjjIMc1lG+f/gSyBXGa1lAnP9jxIBtb96MfE9yoonB+/qn835irUCyK33zQeIhXanaTYXPw2SFTKHFbV0w8wsK3XyLS+rxbknnz7AuEba+pa+abmyKH7F1WnMs3BR0/gBqfxi82NbG1tWfIYrZN4skFxagW8oW2Vmm8vDGMLwROG4Q1COngUGH6MIVzJ9ks5SOtXuKn5kDvbRNPkxk5UVy11dAMyu8NYvYWzSlByjiZggss2O/UCD/ThFETBrvUpQbUoHcpk+aoOL9SiGQxVyv86i707V2r7lKaAxwqcnEa6uwhMWv4fRJy/Abz+HioycfXntjA5spW9CjTAwlIc6rkpTn52SUTmT1ycMvMY5rwj7OgZkPfritbDNc+1T99SiDbm7bzp/V/YlvjNhRZYU7RHG6deiu/WfsbNtVvIsuZRVFKETmuHK6fcD3D04ef6C7HxPD5qPvVr+l87z2UzAyyPv95Gv96L+GaGuwlJRT94fe0PfscHW+/jdHRga2khII7f4j7FAtO/gCg6wb/+Pq7QpvQX/7bfOQEiLf1N+FggPefeJidH7yHFgqRP3wkC268hZzSoTRWHGTNS89Sv38vNqeTkdNPY/qFl6HarIm6fVKwOkb2t7jLcuAm0zR3SZL0E+CIm990TPJ6lmma341mZ7A4fkmSJEmSpH/5JDh+kBwfkyRJkiRJ3xnU5RyA24FHDyuW7Qc+T1d46ZOSJH0BOAhcZeUDTH8AbekqzKo6pJIC1PkzkVyJk182avajffA8eNuQR03H7GjGrNqLVDQSdd6nkFyJqe/j3f8WbVseR/c3YQQ7wNRx5E8hZ96PUd3iK6l71/6Gmn1PH3dUwpk6lOLRV1FUJp60Hgy18fLSzxII9swTtKkpnDrp2wwvPU/Y/vKDT/LSnt9FbJ9VdDmXj48qeBeVoBHmj3ue5bnanknx2bZU/nXKNylwZvZyZd9Y0VTBQwc2EDJ0PlUygfMKxZVOj1Dr83Llh+9EPeeNeefiEVxBW9/YwtfW74rYPjc3k7umRd2IiMqKej8/39SEV+taeJI5WgoPtwJ/mJnH2AzxXa11BzRW7NOQJWjzmrQfI5md5YFbFzjwOMRXTV952I8WQV9FscGF11kri3Dw337CEVIe1CwY9gVx+0ZTmOAj9dB8XL6fW8ZxXR5yUWLU8AJ//AA6u98kaXgm9qsmISWorMZJTr+PjyJsrWrjrld3sLmqlWBIJxyH0pNdkfjFZRO5asYgDvdsq4Z/LYT2qr5dN/5yuPIBSEB5pf7iYPtB7lp5F2vq1qAZGqqskuvKpTXYil/z98hnz3Jmcc/ce5hdNPsE9Th+Dlx/A/5Vq2KfKMtgt5Nx+eUU/ujO/u+YBTqa/fz3+z3nHfHwhd+dgTNG1MSJZuvSt9jwxsvYHA5mXXY1w6ZOp7Wulmfv+QktNVXIssyo0+Zw3m3fQFGTu3wDzUlfwD38zJsYew8e/VsePQzbZYmJ7zZDAUL/+C4EexexkEdOxXbpVyx/TrB+KzUv3Uxv6RyO/CkUXni/kF1v237Wv/6ZqOeMm/MrckrmC9l/7q1L8PmjC9ScO/c/ZGeO77PtkB7gh0vnxTzv66c9TFGqmCMVq5xDpi2F107/hZDtI1T62vnMqifRj/md/WXaBUzPLLJk94y3X4rrvPcXXiRkf+6bK2Oe8+NJZSwsjC8f8Fj8msH5b1VFVQ61SfD2uWI5nPvqdR5YFl31Mj9N4uuLxRaIPngtQGN19PdmwRA4bZGYc1b/Voj2jdEFcFLGyRRcKOYY+39dCZ0R7r4KzjtKkOzWQokCD62Hit4FMeSJ+dgvjfxO+KTs+CWKRO74BcI6c+55hyavmGrs2h8sJCdVfMGmX/nTFGg5IHbtgjvhzG8ntDuJwjRNLn7+Yg60H+jTdTIyS65aQo6r7+/wgaLm57+g9dG+q2vn/fAHZF97bT/0KDHce0v0RdtY3HaftRSg/uTg5o08/csfHv1bVlRu/OP9PP6j7+Jt6b6aOf2CS5l/3U0D3cWTnkFbzmGgMPYf6v73vkMRzuw7ZvXeiE4fgFG+JSGf46tcQSQpvWDdJgxNTGmtctcTMc9prv5AyDaAz18X85yq+t7lpGOxrjq+MhnvlD8oZB/gw+btUdtbwp2EDXHZf4DVzZXdnD7o2gEczNT443veHisXk29f1xiIWS4ibHblAYqwqyb2FkV9h/iCV1NN7GvrLHzFnTtjq55698VTcKMnZtiM7PQBaGBUipeiOEpVZBVEY29SvW2wsqmiVdjpA3h2Q2UCe5NgWg7GPicSW8XLHvU3hzoO9dnpAzAwWFUTx07aCaTjLbGyDO0vv5LgniSJl/0b1nT729A1dn7wXg+nD2DParFdzyTWOOkdPym7eyielGM9NO+orazC3lWjjn62tV2bI9gzR0RsU9x5SBGUuWKRURBbcdSTHvmzY6EqsXc0MlLFEsjLsuJbzBibI65MNtxTGLXdJqnYLEpoDff0fB57OzaYyHHEF0ZySpaYUE1ZWuzQDgnIcoiFVuWlxxYmcVuILrHHsZHntBABbs+O3X9bHP/G3pBsUswAfzknARkA7ijPUFLVc9AyPNdjSVTptOGDWODFYeFHWTg5cf1IMHnuPFJtqULXlmWUxT7pBGIfLjY/cY4f/AXOP65kl/QM9y4cNRbF1nNMyBkydCC6lOQ4TnrHTz13LqQdfqGnpaCeMzdhtqW0bJT5V8NhWXypYDikHp60p2ahLvpcQj7HPXQ+KaMvguMUJCWbm5z5P0aK4nxGI6/0LOzOyFLf2cVnUjDyMiHbAHOmRw+DLC1cQGnhWUK2cz1DKE4ZG/WcVFs2M4rElSu/OuJistXeB0wJ+MGY6OUq4mFaZiHXDJmMKslIwOL8kZyTb32wvaggdlmI20dGv3+RsMkyZ+VlRD3HpUh8abRYPk+B28ZlQ6KXo7h+ZCoORey5nzZEYUqpgkTvLzgJuGqmeI7Egstie41zLxC3X3hZ7GuLrhb3XNULs7puQi8o56YjpVl3/NQbIqjq2WTsFycnZYOVvFQnP71kAk6171ODBWNymVKakfhOJYpL/iZ2nTMDFv0soV1JJC7VxU9O/wmu4xZipUg/8sNcN/46xmSJ52kPBCV/+D2Sq28h87ahQ8n75rf6qUeJYdbl4oqqCz43uL+zCfMWMOb0M0GSUFSVUy+5kiETJ3POl7+GdIwaqTs9g7Nv/PIJ7Oknl5M+xw/ANAzo9EGqR9hJioYZDkLQj5SScfizWiAls9tDnAj0QBtIEqYexgi2Y0svRUpA0RZf60HqK9/GNCWcnlyyiuYgYWJ3Wl+dNU2T6roPQVJQFRc21UlY85GRNgKHPd2y/VZ/A+8eeAiXkkaGq4h67z5U2cYphReQn5qY1aK6QAtPVy0nz57BpPQRNIfbmZk1BlVKXDJ/RziIZhpkxrNd1Acuefsljg2gkIAxDg8PzLWeA+DXdX66cTfVXi/VAQ0HMCrdxa1jRjI6w7qoUUdIZ2dbkDSbTKHbRnlHmLaQzmm5LhwCE8/j6QyaKFJXOYe9tWH2NOiMLrAxMldJyHvi4K4gdZUGpgHtrWCYMG6axJBRiRGX6igP0rbeADvYPGBLlXBkK3hGWE+GNzQDszqEaZcwW3QkGZThTsu5fccT3laHIYEiS0iZTuS81Jj3Ppnj1zf6Q9XTH9Jp9YcIaQaabrKpooVNh5pZNLGQNKeNuvYg7+yoZfKQLDJdKqcOzyY7ZZDm9h2LYcD+92DHS9BSAe5sKJ4Criyo3wnhTgiHwQxB5lAYdzHknxwLFSE9RL2vniZ/EwWeAlw2F6ZpUt5WTqYzkyZfE5qpYZftlGWWkWJPjDDdQODbvJlQXT2m34eSlo6amQEOJx1L30Gy2UidNQslLQ1ME/vQk2MXydANnvrVKhoP+XttV52ghYHDkf+lU7O4+JapA9Y/q/ja21BUFccxNYe1cJi68n04PR6yi8XrMH/SGeyqngOCJMsf7fr1B34v4T1rMTcvB28b0phTsZ19TcLMh1oP0rzqj4TbDqF48smc+nlcxacmxLa3/QBb3ruNcKAFSXXhSimlo3ELrrQh5A1ZhMOdb8m+pvs5UPU2tQ0rcbsKkGQ7bR178LgKmTvjF6QLhnoe4VDbFrY3LUfXw+h6GJ/RiU2ygwTnpd5qyTbAExXv8VjlUgxDx6+H0NCZlTWemZljIu6KxItuGjxfuYONbbVMyyhgWeMhNEPnq6NmMTrVekL97auWcXzUvAnsDHq5ZcV73Dc7tjhOND69bD3N4Y/yzYLAujY/X1m7jcfmTCXHZW2it745wGP7O0hVJer8Oi0hg3SbRGvY4OIhYqFLx2IYJm9uD1PfbuIPmbT5YEdNmM+eJlFosUh5e0uYTR92OX3HsmGZScDnZ/QUaw5+sCNMw2sGxuHyngFASTPJmGbiHmIiqdYeTkkDfV8AvSmMnK4i5dojpRkLoVe2EV66Dxq9YICW40I9u6xfFuaSJB6XXeHptXXc9eoOgrqBQwETiWc2VJPusqMqEnXtQZ5eX4XTpvDVs8u4+czBHTYIwGv/B2v+CUhdKp1GGLY+Hvn8Zb+DTz8Kowd3QXC/5uf18tfZ3LiZcZnjKMssw2PrmnBPzp3MA1seYE/LHj4z9jNMzZ96YjvbR7yrVxPYtZvAjh10vP46pqEjp6RiahqmzweSRNN/HgSfD4JBbGPGMPw//0HJsL7w3J8889u1EZ0+gOOlHSo2NvPyfRu48JZp/dyzxOBOS6e1rpZVzz1JOBhgwryFFIwcRfHojyKRKrdvpeFQOUMmTU06ggPIx2LHrz8xavYTfvK39NBu96TjuCVyqYF48Vevoe6123sczzjli2RMu9GS7Y6W3Wx8M3I4qqw4mHzWfaRm9111EyAYaue5Ny9EP6Z4+/GcNeuPFOWJSUa/uvuvvHvo4YjtBZ6RfHP2Y0K2Ab62+T5Wtezstc0p23h37m+EbQN8Yc3z7Oho6LXtrokLmZ8n7hRf/N7rNIejV39NkxVeXXC+kP14VD1fmncKGXHmAx7Pn7e38MzBzojtp+c6uXtG5DDlWNS1GfzprWBEX+bGuTZG5YutezXXGyx/KfIzDzBkNEybK+b8aV6TA3+LLLCjZkgMvdGBJBgKa3boBP5SDYHud0fKVnF8qQDJaW3XT1tTifbGnl7b1PNGo06PHqac3PHrG/0xPn7xobW8uSO2eNexzBuVy0NfmJnQfiSUv82B+q1i1y7+JZxuXcG7P/CFfXz6lU9T3lZ+9FiBp4CnLnyKDGcG5z97PhUdH6lNfW/m9/jsuM+eiK72mfrf/Y6mfz4gdO2olStQMzIS26EE8c9vvEvILybQlVHo5Jofn57gHiWeg5s38szdP+qKkjvMghtvYdo5FwKw/PGHWP38U0DX5s1F37iDUTMH/79rMPCJV/Xsb/S1b/Z0+gC8bRh11hVEm1f/pdfjbVv6LmF8PDtX/DBqu6EHqdwl/jn7Dr0U1ekDWLf1z8L2lx2KshIL1Hr34Q21C9uP5PQBBIwwK5qiq35GY19nc0SnD+BPe6ypWcVy+gDajdjqkL3RGoxP1e+Hm3qf3MfDC4ciO30AHzYECOhiAyPA29vDUTewnl8f+/5FYv170Z95gEO7hc1T+3J0VVWt1cS7X/zeaOs7ezh9AGaThr7FK2z3qP1l5ZHblu63bD9J/2KaZp+dPoD39kR+3w0KRJ0+gCU/T1w/EsxbB9/q5vQB1HpreXHfi2yo29DN6QO4f7NYeaiBRu/00vzgQ8LXN/zhDwnsTWIRdfoAWmvEVN4HmtUvPNXN6QNY8VTXQn0o4GfdK88fPW4aBquee2ogu/eJJun4xUKPIimvi08eY9owxSbt3U3EnsCbhvi/IZbTB2BYKIdgxhT9B8O0Vm4hGn5DXNY8HMPpChviL/7+Ro8zCCCoiz+j8XyEYSEYQYtxey34lPT3VxfPT9KM90vqjWjXagmIAIlmYhA/90m6OAmCgE4Ag/e5DUUYp0JGiIDe00nQBRcEBxxD7+E49OnyQOz5SZL+Q9d6DmT64QVr0zAwjps/9HZ+kv4h6fjFQJl6Fr0me9kcSIXipRCOkDHtC70eTxklrlZ5hLIZ34t+giRTWHaluP0hFxPrEZo8pvd/XzxMzV8ctT3NkUuqI0vY/ihP5JAzBZkFuVOFbY9Ny6XIGTlP7cZhEVQP48QeR66UaAJvtjO+8M0fTx4t+AkwNz+6AMrYdBtuCwIvZ42NLoByzkTx9ObJs2NfmxNbdDUihRdFz52UXeAZKZ6jqExN6f3h8Mgok6KrrcZlf0aU39UsMSXYJAOHLEtMFVDnHFc4yMVCUqKX74nKqV9MXD8SzOKhi3sUYU+zp3HhiAuZXTSbTEf38kFXj7l6ILsnjJKWRvollwhfn/f1ryWwNwnGwszb5jk58qSnnXtxj2OnXHApAA63hwnzFh53/kUD0a0kJHP84sKoO0B40zLYtQbCQSgYhv3KbyLZE6Pe5z30IS2r/4TubUByZJAx+bOkjRd3yI6l4dA77Fr1Y0wjBEio9kxcaaV40kdQOOJSUrLEJP+P0OmrYfnqO2jt3I9NScHEJBRux2bzMGvKnQwpOtOS/Vf23MuKiqfQTQ3d1OlaeZUYnTWTz0/9PYpF1dMfb3+Y95q2oBs62mH5rCGuPO6f9jUybNYmwQFd4969q9jZ0chQVzpb2+vQMbl5+AwWF1gXQlj49ktECvpwAEsWir9Iw7rO2UvWRNy8+f20MZyaa60e4b/3tPFqRScSJp1hk6ABdgUWF3n42oRMFItCIJXNOq9tDtPkNQmEIaSBQ4XLZ9iYVGLtuancH2Td0t5Xo7OL4YxzrYm7eA+EqHlG77bRINkgZbRMzll2FJe1e2O0aISXtGI0a8ipCnKRHXWaJyGlHAC0TTVdIZ+doa4dQLeKMm8Etmmxa58mc/z6Rn+Mj6Zp8q2nNvLc+uqj7wDp8P8ctq5nLxA2j7ZdMKmQe6+xtpg1IPz9TKjb1Ldr5t0BZ8VYRD3BNPobeWzHY2xt3MrozNFcO/5aCjwFALSH2rln1T0cbD/IFaOv4PJRl5/g3saPqWm0v/oqge3b6Vy5itDu3WAaoNpA17u2p00TFKUrmsA0kdLSGPrwf3GNGdxlD/522zt9Duyyp8jc/Nv5/dKf/qBq53bWvvI8WjDAxAWLGTPrjKNthqGz64NlNBw6wLAppzBk4pQT2NOTC6tjZNLxixPTNDEM46gqnSRJCVeoMwwdkDAMDUWxJcy+YRh0zb4kTNNEURRM00xo/w1DR5JkDMNAURJXBgFA0zUUWUE3dGRJPvpvSBRH7EpS1/0BEnZvjtxn0zQxTRM5wSVAvH4/rR0deDs6yExPp9Pvp6SgAJvNuuQ/QKfXiz8UwqGq2FQVfyBAVmbiCtAf+V0d+T41XUdN8POjGwayJGEYBrIsJ+y71TSN8JHQlcPzD4fDhqomxnkKh8Pouo6qqkffPYqiJOwZMgwD0zTRNR3VpmIaJoqauHt/5H4f+Zx4f7NJx69v9Nf4qGkaiqKgaRqSJKOqCrre9Z43TQPThFBIw+m0I1so+j7g6PpHKRyqreu/TSAcAoez64csy+D3QYp1deGB5Phx5vjx7MhvMZHvwYHg+PkXdP2bjhw78p48mf5NAD6fj87WTuyqnUA4gGmYqDYVSZFwe9x0tHRgs9vw+X1kZ2fj8iS2HFR/Y+g60nHP2rFzopPt+xosJMs5DADB1/4F23uKccijTsF2sfWSAmFvA9XPX48ZaO5u351H4YX3YUuNvUreG6ahsebVTxH0VvdslGSKyq5kxNSvI8nik71NO//B1t3/4fgciGEl5zHnlJ8I2wUIaJ3c/f6l+LWOXtvH55zJDVPFlTf3e2u4ZeNfaNd8ANhQCdM1IShyZnH3+BsZk1oiZDtk6Px65/u8WbcXGQgd1v23STLfHzePcyzu+L1WeYhf7oywcr2r6/9enruYDIdYyYXvr9/B8sa2iO0SsGzxLCHbAI0BnS99WEtjsOeumSLBT6dmMbfA2o5rRbPOP98LET5uVXXaEJkrZthRBCerfq/Om09Eyv8MA2HmXmgjS1A1tHN/mNpnjs1dPTb3QUP2wLBbHMIOoF4XIvSP2m5mj71Fyrw07GdnCNkG0FZXoC3Z1yOXMCxL2L4xB8WVmEWJJP3DSxur+OoTG/tU3cNjl1nx/YWkOQfxd7vzVXjiM32/Ln0IfGNL4vuTYK5++Wq2HxYk86genKqT5kAzJibp9nTaQt3f50NSh3DP3HuYlDvpRHQ3LsK1tZRfdTV6fX1c58u5uZS99CLKIFXzPMKetbW8+YCYeNwl35pCySjrNZj7E197O//97lfwtnTNadNy85h27kWsefEZQn4f7vQM2hvqySouZfEXb6d4rJiyfBIxkjl+MdD3rO/V6QMw9qxH32ZNnRGg4a3v9HD6AAxfPY3viauJ7V59V+9OH4BpUL3nSWrLXxK27/XXsnX3v+gt8f1A5Wu0d1pTPf3n+q9GdPoAtjcuY0fDB8L2v7Xln0edPuCo0wdQHWjmBzseRHRH/IlDW3i1djeaaRx1+gDCpsHPti+lMeiLcnVsIjp9x3Dx8jeFbGuGEdXpg64F8j9tF1do/OnGxl6dPujyF368sdmSqifAg+/3dPoANhwyWF0uLnCw5JnYoj/LXxZPVO/u9PXE8ELD6+L2w480dPclj0N/rx0jwncTC6OuE+3Nvb0LyBgm4X+uFrKbZGAwTZOv/a9vTh+AN2Tw7f9t6Jc+JYz/XSt2Xdsh2Pp8QruSaP6z9T9HnT4Ar+alKdDEkWDc450+gEMdh/jOsu9gHF+MdBBR9a1vx+30ARgNDVR+81v92KPEIOr0Abzwuz6GKp8AXvr9XUedPoD2hnree/hf+Npa0UIh2hu6vtPmqgpe/uM9PYRekvQvSccvBkZVdMl6o3yz5c8It0d2kIKN4i+ItsbYA3FH0zZh+1W10Z2u8so3hG0D1Hkjy8IfYXvjcnH7wZao7ZX+Rjr1yAVWo7G1PfJgZQK7opR6SBSiw/nejvgk/d+sPb58fPzsaY/uuOgmHOoUV2zVDRNfFP+soll8spMIMd9ImHFKmforxftvtsUeZI0KMUU8oypGeZUOcaXcJP1PbXtAWE13RXnPxctBg65ZU8pe96/E9aUfWHJoidB1VZ1VNPobE9ybxBHY1vf5SWCrhbIdSRJCw6EDcZ/b2dJMe+MgLwXzMSPp+MVALo0ufiKPsp7Qbs+IrA7qzBdPeM3Mj11MN92CcmVJQXThlpGl1pRJi1JHxTxnct4CcfvO6OESw9z5pKpuIdtTMwoitsnAuLQ8Ibt9QTToanRqfCGWFxWL/xvGZ0RXDlUlGJoiHjamyBKeKFGuw3PEX32qWM36uJDiDD91DxPvv5QZO7RbHiIWIiyXpkc/IT0xglhJ+ofCdJdwCPRZo3Nin3SiUFSwIgQ2+/bE9aUfOH/4+ULXDUkdQq4rN8G9SRzOqX2f/7innwQiQx9z8oePjPvc1Jxc0nIH7zP4cSTp+MVAGTkFaWrvzoU84XSUMada/oy8xb9F8fSUmlbSSsk5M3oR9miUzfg/XGm9O5WSbKN03PXkDRMbMADcrlymjv8KktRzgj562JWkeMRyE49w07Q/kWqP7JxNKziPUdmxndtI/HHyLeTY047+7ZbsyEhISAx3F3D3+M8L276qZCJXlownRbXjVj6acDhllbsmLiLLbi1J+9eTY+f1vjzvHCHbsixzQVF0p1gBbhkzVMg+wI+mZFPs7t0Bsctwz/RsHIq1xO+bzrTTW8rRrBEy04eJ57UuujK25zfvEnGntfiz0a9V0yFvsZhjBmD/XB5E8b+Uc9KR7WJDg5zrQb1gTJc8aw/DErabk5otg51/fm4GffX9Ml027r5iar/0J2Fc+6zYdTnjYHT00kInms+O+ywz8j/6bWXYMyhOKUaVVFRJ7dW5G5c5jt/P//2gFtgo+e1vsQ2JvwSMWlJC0W/E8/4Higu/Oln42qt+aH3O2d9c/K3vk5730eJ3VnEpC2+6jfS8fJwpqWQVl6LaHRSMHMXF3/w+sgWdiSR9J6nqmSRJkiRJBg1JVc++kRwfkyRJkuSTQ1LVcwAwDQNj+4ouoRdDA9WB2VqHnJaDsuhzyCkZwrZ1fwtNK35LuPUgtswRIEkYgTbsmSNJHXc5tjQLlaCBmv0vsnfNL3scV2wpFIy8nBFTbrNkv7p2BWu2/gafvx7D1ODwjpmqepgx6VuMKD3Xkv1NdW/zxt77afR/lAcpITM8Yxqfn/pbHIKhmEd44MDrPF+zgvaQl9BhcRcZme+MuoLLiuZYsg3wTv1+Xq3Zzfb2BjBNUmwOXIrKeQWj+fQQa2pqZ7wdWZhnqMvNo3POtmT/vLdX0Rkh4efioiy+M1G8gLtpmrxT42dZrZcNzUE6wiayBAUuhYuHpHDF0FRUixLxQc1k9X6NQ40GB5sNAmHIS5X41Kl28tOtBTusf89Pxd7e23JL4PRzrO3oVj7pJ3Cw97b0mTK588R3/ADMTh1tTSdGUwijPABeE5wy6rw01FmplnYBDF+I8Ku7MCsOC0rYFVBl5MI0bPOHI6Ulwz0HMwcaO7ntsQ3sre9Aous5UGQJVZHwBjR0k6PiL7IEdkVmSmkGv7tqCiWZ1t7H/c4bP4RV94HRh0Td2bfDOb/ovz4liO1N27l34720BFqYmD2RzQ2baQo2MSFrAkPShvBa+Ws0B5pRZZUxmWO4fdrtnFo4+HePan75S1r/9ySEQiBJXaU2joiBHPnbNJHcbkxNQ83KoujXv8IzY3CvHd375Xfoq4qSI1Xhpt/M658OJZCgz8urf/kdlTu3oTrsKIqNkM9L3ogyLv/eT1DVQaz++wkgueMXB+Elj2FsfKf3RrsT+21/EiqJYOohKh6/ECPYuyCCbE+j6PJHUD1iuVSNle+x44PvRj0nb9iFjDntTiH71fUrWbrya1HPOWPG3QwtEsvDW7L/37yx//6I7Sm2TH4073Uh2wA/2fEIr9dHfq5+Pu46FuWJ5wv898BG7tu/JmL7VSUT+fro2UK2ozl9RyjzpPLg7PlC9s9fspqOGKqat5aV8JkRYuUu/rW7jf/uiywEck6xm+9PtiZZff/SIAeaev4bJOBrixzCzt+ujUF2rot+b3IKYM4FYs7foYf8hGII2WXOVsg+QyzZ0AwZBP9ag9nau9iFckYa9sUZYrYNg+DvP4BABGEep4rjtllIUUo6JHf8+kYix0d/SGPij9/oVZQ1FnZVYs33F5HuHqSTuic/D9sFwz3PuRtmWy/d1F9satjEda9d12eFzj+d9ScWDBHPk+9vqu+8k7annha6duQ7S7AXWUs36S/uvSXCfDIOUrMdXPdL64vS/YVpmtx3y+fwtbb22u7OyOTL9z88sJ36mGF1jEzm+MXANHSMLcsinxAKYOxeL2TbX7U6otMHYITa8e5/S8g2wP6Nf4p5TsMhceXNbbsfjHnOph33Cdv/sPKZqO2d4Za4lD8jsbQxuizyX/a9IGwb4Lmq6IqsL9fssmQ/Fnu9kUthxCKW0wdw/95KYfsvHOqM2v5Wlc9SOYfaNqNXpw+6FlnXHRBX+Ivl9AE01gqbj+n0AbSsEe+/sScQ0ekD0FeJPzf6gZbITh9AQEPfmVRwG6w8+OEBIacPIKSZvLwlQvmgwcCOF8WvXfKzxPWjH3h2z7NCZRme3P1kP/QmcbQ9Lz4G191zTwJ7MnjoaBJTXB4o6vbtiej0AfhaW9A1ccXuJNZJOn6xkCSwxVhZd4kVmpZtscNi4jknEkocYZCSBaUzmy32v9tmIRQznjBOuyIeUqdK0Xdp3Yq1cDqXEn3l236SJzSrFt4eLjV6KKFNBsVCuKE9xmNtt7ApIQ2Ct2aMRzc69hj31SZ+36VYNx6QHMkMg8FKptuaZG3qYP5uY7yPo9KfUr4JwC04znpUsbnLQCGp4s+TkpmZwJ4kiRebK/acTJYHwSD6CSZ592MgSTLq6ZdGPiEjD2XoeCHbjoJp2DLLIrbbMobjGSGuJjZ29k9jnjN04i3C9qeNv41Yj9BpU74nbH/xiC9GbS9Nm0imM3LZhFhcP2Rh1Pafjb9O2DbATSOmIxN5En3LiP7Nr7ioUCwME2BSWuwJwW+njRO2/4VR6VHuDNxQlobNQo5flkfm1OG9e0cOFU4bIT6hmLUottdVNkm87ykTYl+bu1i8//JIJ/KwyIsatnMyhG0rJelIeVGenVw38mCW/f+E8+mZQ8gQDNXMT3VwzkTx93G/M/fb4tde/Vji+tEPXDPuGlJsKX26xi7buXHSjf3Uo8SQ+93viF2oquR/N3qay4lEdYhPvYdNzUpgTxJPdnEphaPGRGwvGj0WKen4nVCSOX5xYjRWYRzc1pVUnJqFWbkLKacYZeoCS0IIpmnQufsVgg3bcJWcjhFoQQ91Yksrwl06B0mxttIY9Dey8a2bCPlrAJAUFzZbKs60EkZMvp3UbDGn9QiBYCsbd9xLU+sOwqFOkCQkZNJSS5k19U5cMWrlxaLRV8HqypdYUfksQaMTm2QnxZ7NWcM/x6ySyy3ZBtjWdoDHKt+lzt/MoUAjPj3AcFc+v5/yJXIdGZbtV/raWdFUwdrmKjRTZ5gnA7+ucUXJBEamWHuBX7P8TQ4Gew/7+OnEqZxdUGrJ/oO7DvKvgzW9tj02exKlcdb7i0SFN8z6pgAbmgJsaw2RpsqMz3RwUamH0enWdluPUN6gU99hcrBRo64dxhXJnDnahj3GjmMs2ltCLH2293DJmYsUCodY+9227QrR+LqOeaTeuQwoIHug6DIbzhxrOyumYWLsDaB7NYyDQcyDIaRcFdvCDJQ8a303TRN9Qw36vkZMSUL2dNmTS9JRxuchKdEH/WSOX99I9Pio6wZ/WrKHN7fXkuKwEdYNHIpMTqqdXXUd+EI6Yc3ANE1SXTbS3TYumFTE5+cMxxbjuz3hHFoNr3wL6rYBcYRLO7PgpiWQE7nW7mChI9TBc3ueo85Xx4LSBSyrXEZVZxWnFZ5GWWYZT+16ir2te/GoHmYVzeLK0VeS7bI2Pg8Evs2bqfnBDzE6OjAA2e2GYBCtpQU1OxvJ4cAMBnFMmIBeUYF9VBmFP/4Jsmtwi0i99LcNHNrc0qdrzvxsGZPOjL+8xYnCNE22vvsW25a+TUp2Dp70DGr372XcGfOZuli8hFiSLpKqngOElJ6LPGwiUmZ+l5DLuNMSY1eSsWWOQA+04cifiKn5CbdV4So6xVIY5hEcrhxGnvJ1wsE2TFPB27aL9NxTyC6ajaJafzE6HRmMGXYVrZ37UBQPbR37cNmzSUsdatnpA3CqKTT5KhiTNZsUVwbeQDv+cCvD0qZZtg2Q78hkWvpIFo26ki0dB9nbUcWZuZMT4vQBZNmd2CSJr446jWJ3jOLWfeSfp83n/GVvcHy0vAIsyBff7TvCouI8nqmoocPoEkTRD9u+razUstMHUOBSybQpqJLJWfkuhqeqeDXIFKwhdzymaSLLIGOQkyKR4zFx2SW6svysOX5pmXayC/00N4B5zBcwZBQUlFgXt0gZruAdpuM7CNi7ak/LdkgdI1l2+gCMVg39gB9DBXWCG/n0dEzDRE6xHn4sSRLyyCyMcBjJlJByPdDqh3wP6AYMdufgE46iyNw8dwSj8lKoaPWxt7qdYXkpuOwK500sRJUl9tR1UNfup7zRC0jMHp41+J0+gKwRgAxqCpgm2B2QORyGzYGWA4AOtTvBWweuLJj37ZPC6QNo8DdQ6CmkI9TBzqadzCqaxZ7mPcwumk1JagnT8qbRHmxnY8NGpuVOI9WReqK7HBeuiRMp/s2vMYJBAtu245o8iXBdHVpDA4Ht27ENHYp76lT8m7fgwyTn1lsHvdMHsPgLk3jqrpW01YVinwxINhh/ujWV94EkLTePRbd8leyi7nMRf0c7gc4OMguLaW+sR5YVUrIG/wLEx4nkjl8cGAe2En7lnxDwQkomtktuQy4YZtmuaehU/O8yDF8vag6KnYLz7sWZLy75Hwq0sPqlizGN3l8s4874NTnF4tLAwVA7ry27Aa+vqtd2hyOLS85+RjjP7/EtP2FD3WsR2wtTRvONWeLqUD/b+Siv1vWuujnGXcxDpwqGmRzmkYOb+Nu+1Uf/nplZzB+nJWa16zvrVrCipTHqOZcXlvLNCVOF7F/93jqqg9Elz99bdBqy4G731pYgt6+sJ5IcwYJCFz+eKh4S2NxpcO87QXwRxtQLp6jMGSXmoNUeCrLqrehCCqefZyO3SMxBa14VonlZ9N2IYbfaUT1iTlrw4XqMPYHeG2VQ56djmy++SBF8cgvm7gjPpgK2i8ejTMiPeH1yx69vJHp8/Ofy/fzylR19vi4vxcbK7y9CtliGpd947GrYLaICLcE3tkH64Jx0B/UgN7x2A1ubtkY8Z3bRbGbkz+CvG/6KiYmExDenf5MbJt4wcB0VILh/Pwdv+Dx6fRyKV8fgnDyZ4U/+r596ZZ0Pn9vLhjcOxT6xF8bOzuPs6ycmuEeJo6Wumoe/+zXCAT8AJeMncfWP7wZg5bP/Y8XTj2PoGs6UFAKdXVFik85axKIv3m4peu6TRFLVs58xTZPwWw93OX0AnS1oSx9PiO32bU/27vQB6CEal8XO0YvGjg/uiOj0Aexe9XNMASWwo/b3PRrR6QMIBptZt/WPQrZ1Q4vq9AHUdO6moVPs5RnQQxGdPoBdvirerhdTawUIGzr37etuf3VLFfs7m4VtHksspw/g2ZoKIdsBTY/p9AHcszVCIbs4+MXGpohOH8A7NX6ag+LKXy9vDkd0+gBe3axhCC56xXL6AFa80Yc6YccRy+kDqH4qvlXi4zHatMhOH4AB2jttGE1i/dcbvZGdPgAdwq/txtTEVUmT9B+abvCr13YKXVvfGeb1rb2Hhg8KhJw+ABOevTmhXUkkz+95PqrTB7CiesVRpw/AxOSP6/9IZyi6uvKJpv7Xv+mz0wcQ2LyZ0CGxucFAIOr0Aexc0ff7MZC8fu8fjjp9AJXbt7B37Spaa2v44MlHMPSucT3QefjZM022vPMmBzeJz7eS9I2k4xcLXYP2pm6HzJa6hJgONUYfYHVf7Ml9NALeyE4ZgB7uwNDFpYHbOyNUmD6Gtg6xcgt+LT5J+YPtm4XsNwbbYp6zrSP2vy8S7eEgRi/VWbe1D+6XNkBdIL5nYlOz+KShIRh74r+/Q9x5amiP7tQZJoT70fcQXU+JNwIjHPvx7RWjNj6H0WwSc7rNmjh+twENvOLfbZL+oyOgoRniUUAbKwUfzMFO074T3YOI7G/bH9d55nHjkW7q1PkSM5fpL0IHxcfg4H7xUk9JxGlv6DnHqdu3h9ba6q7w6gg01wziUjAfM5KOXwwk1YY0rPu2ulyWmPyylPFXRG13FlpTfcwbel70z88ci6KKl0MYUnhWzHPKhlwsZDvFnkk8eVhT888Rsl/izkWNoct/edFcIdsA2Q43qWp3gRIJWJg/UtjmQDE0Jb7Q3K+OFRePmZUbPQdDlmB6tniexpTS6GGQHgc4BAVebHHozngEIyUlSUKKI0I0VVA1VCmL4/fulqOqfka1PzY35jlSQQpS+uDPwfkkkumxk5siLu5z1QxrglKDlslXnegeRGTR0EVxnXe86memI5MR6YM7fzF14dnC13pm9q9qtiU+xjPvkTNm9Tg26ezFFI+dgDM1rddrFFVlxLRkdP9A8TF+/BKH7fybkCfPQ8ofijLjHNSzPp0Qu678yaRPv+VoUS5JdSI7M5FUF67SM8hd8HNL9odPuY2sCDl8KVkTmTgvdoH3aAwrOYep425DkXubxKmMG3ktI4deJGz/G6c9hhTlEf3MhJ+jWqjNdP+Ur5KqupCQsPGRo2CTFH4w+tOUuqzJzv935uXkOTxIgFuxcc+kRTFr+8XL82dEL0UB8O5Z4vmEv506Omr7hDQ3c/LF788PpmQzI7v3CaZHgT/OzLEU779gvMrpI5VedUTSXfDVReKqoedfG915khVYcJm4YzPkZnvUN7MtF/IWiNmXFAnbtblwvF9sl8AjI41y4rg+D0lQYEeyKaifmdRViPF4FAkm5GG/SjxvOUn/8+ytcxiR03fxpjvPH0tZXt9KCgwot3wodt2QM2CxtbG4P5lRMIOfnP4T0my9T6rdqpu/nPUXHj3/UUZnjsaluhibOZZHzn9k0OdU5d5+O1k33YSSlQVHSgDE6rMkUXL//V3qn4OU6345W/jaG39/RgJ7knjOvvEWxp4xH5vThScjk/Nv/zZpOXnYnE4+9cNfUHbqLApHj2XywnMpHT+JoZOncdkdPyGjoPBEd/0TQ5/EXSRJcpum6evH/vTKiRZ3SZIkSZIkA8PJKu6SHB+TJEmSJEl/MyDlHCRJOh14AEgBhkiSNAX4kmmat4p+cCIxqurQV28BQ4f8bIwte8DrA5cD9Zy5KGVDxW3rGvqLf8eo2t0Vn2wYXStO+UOwzbkcuWSUpb6bpknruvvp2PU8phZAdmVjS+kqgussnkn6pGsslXWo3PkY5Zv+DMfG90sKqZljmXL2P7tKU1ggEGzl9WWfx+evRZIUcrKmMGXszeRlT7VkF6A1UMe9a26iLdg9ZlxCZlLuWVw98cfYFPGdm/awl5s2/JFKfyM2WaHQmU2n5ieghxmfNoSfj7uOdJu1sgW7Ohr5695VlHtbyLa5KHCl4tVCnJ4zhKtLJ6LECDeNRDAU4uxlb0Q9Z/nZFwqv6FZ4/Xz2g00R2zNkiZcWWitpYpomj+3v4PF9bXQck2/nUeDPs/IpSxMPOdtZo/Pc+hCdgY/SCkzAZYOrZ9oZUyj+3JumydLnAnREKcF08Y1O4Xvvrw1T9XDkHLusRRJZU8V3FM2wiba8DX1/ALNDB5/RlfQoS0i5NuyXZyPniO9M6+XNhJ/eCsfmcdplyPWgTilCPaVI2PZgZLCPjyLc8O9VvLe7sZcs5Z5ke+zceMZwvnjmiMFd0iEcgD9OAm8f86yHzIYbRYVhBo57N97Lo9sfxa/5MTFxKA6yXdk0B5oJ62EM08DEpCyjjPsW3UeOxYiWgSCwaxeHbroZvaEh7mvUkhKGPfoItvzIysEnms7WAA/dIbYD/YXfn4HTba3Wan9imiYb33iZvWtWkFFQxOwrPnO0XMOmt15l3SsvEPL7cadnYHM4yB9ZxuwrPoMrQhhoksQT146fJEmrgCuBF03TnHb42FbTNAdEUzbaiqbZ1kHogacgikqc7SvXIHvEtv1DT/0W81AEERZFxX7Dz5Ay8oRsA7RufJDWdfdFbE+bdC1ZM78iZNvXXsG6166M2J6SOY5pix8Usn2Ep15fTCjUPaFflu1cOP8xUlPE8z1M0+Qn756DX48sFjA2ew43Tvu98Gec/+GdNIcji1EMdxfw+Kl3CNtvDvn51Ion8Ou9T+JvGj6dG4efImT7jLdfinmODCxbKBZqO/fNlTHPuWFYIV8YLb6o8vj+du7b1fv3qwBvnlOCKiAN3xkwuOvlYNRJ6/cucJDmEpukrngjQH1ljPemBJfcKJY/u/c3/pjnDP+qA8Uh1v/Qi83oa6MI8zgknN8tRuotXDMGRouf0L3Rnx31vNGo0yNL459sO36DeXwU4YfPb+aRlX1XBP7SmSP43vnjEtaPhPP3M6Bui9i102+Ai6ylRvQnT+56kp+vjD8cNdeVyztXvdOPPbKO4fOx67RZEO67EJSan0/Zu0sHbSjrvbdYu/e33bcgQT1JPGtffo73Hv7X0b9zhwzjut/8lY1vvsqSf/2t12tKJ0zmqh/dNVBdPOkZsHIOpmkePxIMCj1uY++hqE4fgL5um7B9syqKZL2uoe/bKGwboHPPq1HbfeVLhG0f2vqP6J/dulvY9hGOd/oADCNEZe0yS3brvPujOn0Ae5pXCdv368GoTh9Aua+W1rC4cuXKpoqITh/Akvr41NhEES3UUemNIvd/DA8esCbdvqTGG7FNBzY2x9eP41m5T4u5U7H2gPjrq74qjn0QQWFEU4/vwpZV4qqY+tbI9x2AoIlxUEzt14hWyuHIOTsGv7JtXxms46MIz60XU9d7efMgLuUA4k4fwKbBWxMO4OndT/fp/AZ/AxUdYuV+BgrvqlVCTh+AVldHaH//jq9Jemf3ive7/d1w6ABNVRXsXrE84jUV2zbja/+YKgIPQuJ1/CoOh7OYkiTZJEn6NtD3Cq/9QXrsZHI5L1vcviP6qr2UZi1cQk2NHvakpoonvKZkT4jarlgIk/yI3lfUPG5ribqp9tj31W0TLzJtl23IMVRD7ZKKRxEPqSt0psZoH5xCCFmO+ML8MhRrq6mFzughzMVusRDnwozYr7WCNPG+2/oxykaK8546i8RD6qSM2Pc1nnN6vy7270VKF1cSHqQM3vFRgGxBVc+SzEH+vcoWhLXcgzsssiilb+HTMjJZzqx+6k1isBVHjgqIiSSh5gzu7+zjSmpu9wg41WbHk55JWm7kyDhnSiqOQSzG83Ej3tnDLcBtQDFQBUw9/PcJRx45BHnsMZLEtuMmLPnZKGPFJYvVs6+NqCIlj5qOPHKqsG2A7FnfQIqQRyY7M8k8VSzME6B49NVISuTBeNSM7wvbPsK4kdf0OFZaOJ+SgjMt2fXY0zl72BeinnPFOPH+K5LMDUMWR2yXgNtHXoLNQn7ltMxCLijsro555EnKsbu5ZaS43HSBGnsSc92Q4UK23arChLTYuY1PzpsuZP8IN43JID1COOG8fCeFbrGJ2oRileLMyA5UYRqMLxb/XmeeHbtfZRaEK9VY61QypJSJT2Jt52VClDBXZUaKcI6fPCoHiiMveEiZLpS54uHBg5RBOz6K8ODnZ8ZRSKc76S6V7w/mME+AK/8tfu11zyesG/3BnbPu7FGuIRq3Tr0Vj8X89f7GOXo0qeeKlWvK/eY3UdLFF4b7G0+2+Ps7s3hwL7DMuerao06erKjMvebzOFNSmH3lZ0jN6VnuR7XZOeuGL6LEMadJkhj6pOp5oognh8FobgPDQM7JRK9rxKysRS7IRS62nuBrhAIYu9ci5ZZiNlUj2V1IWQXIWQWWbQOYhoa/YiWmEUTxFKKmFqJ3VGHPHo2kWN9eqCt/nao9/8OZOozswlkEOisoGXstipqYWlpefz17yp8hK2McGWnDSUtJ3MSuI9jEy7v/TEeoGbvsQpJgQt6ZTM5fiN3CbtwRGoNtPFP9AdPTR+JUHbgVBzs6KpiTNY4Me/Qdu3ip8rdzwNtCkSuNLLuLKn87o1KysVkU1jnQ0sK1697vcVwB3ph3Lk6btRfp/vZOvrJ6Gx3HFXQudag8Ni8xKViaYbK5OcDmZh9LagIUu1S+PC6LoanWB4FDTTqVzTqqKmFXTKpaYHKJQmm2tfsOoOsG65cHqasA/Zia6IoK53zWhu34Bag+4q0IUf+Gju6na7XgcNxu1jzImmJ94DdDBmZdGDNVxiwPQpYMrQbyEAdypvV7r9d2EF55CNoCSEMyUUdnd9UoLEhFipG3ebLl+J1o+kPVUzdM/vLObpo6gmR67IQ1gw0VrTgUhXljcwhpJnUdQXJS7Mwekc34onScNuu/q34n6IVHr4ZDH4JiB2cGGBo4UiHYDjnjICUL2iqhoxrGXgTn/eqjUgKDnLcPvk17qB1FUki1pzIqYxT72/bTHmrHo3rY27qXK0ZfQbbLQhTUABM8cICmhx9Ga2zCfco0ZJuNUF09wV070dvakZwOnBMm4PvgQxxjxlDwnW+jZg/+f1/toRaeuWtDn6759I9mkF00+EVQDF2nvnwfabl5uNMzPjpu6NTu20Ows5Ps0qF4W5vJKCjClZKYudYnhYFS9fxzL4fbgLWmab4g+uGJRM5Kx6hpIPzOSuRRQ1GnJy6vXpIVkBXM8i3gTMU4uB0KRiClZiLFU805BlpnHaYRwlRdtG58AK2zDiSFzKk34hk+35JtXQvQ3rSFcLAFT3oZ/s4K6va/SFPVcsbNuRtXH0NEjqfTW83mXf+kvfMQDS1bcDnyCOsduBw5TB1/K067tVW3yvbdNPgO4gu3U+gZhU118d7Bx2j0VrF45M3IFgfkHEc6p6SP5PmaFezorKQl2MbIlGLOiBEmGy/NIT+7O5pIU+z87+AWdnU2UuxK45aRp1LitnZv/lXee46mDrxfW8PC0iGW7L9Z09DD6QOoCmq0+INkuqw9+00Bjft3tbG9NYA3bJDntjE8zUGHJpqd2J2iTJmOgMneOo3KFhNNh4Z2g/MnQ166tUlqQ02Q6n09j+satNYb5FqIUgKwuRUMTYfj0hxbVkLGJMPycy/ZZaRSB9rBAOEV7aDIqLNTkFKtOaxH0Pc3waFWME3MzhDhrbXII7JQTy1BGsy13gQ4GcbHvrKpooX39zRS0ewjL81FXqqdqUMzWbG3kb8u3Uemy4bboVKU4WLDoVY+Nb2UcyYmZiG0X2k5CE27AR10P3gPCyn5D6tGVhyXh7TxcTj7TnAO/sl2dWc1hmmQ7khnT8se1tet5/Edj9PkbyLDmcGcojm4bW52Ne9iZuFMVAvRLAOJGQjgW72GcHk53mXLcEydgrOkFMlux/B2YjY04G1uQe/oQFu+nDpJouiXv0Aa5M76vvW1fb5m5+oq5lw6+J/FjqZG2psaSMnKJhTws3vlB/jaWhl12ukUjfp/9s47PI7q6sPvzGzXSqtebcty773ghgummd5LQgk9kAAhH2mkh1RCGiGUUEIoIRB6BwPGmOLee5Mtyepd23dmvj9kg8s23dmV12bf7/me4J25Z69mZ+bec+85vzMM6HYCd65Yyu41q5i44GysjtTegT6eiFfV82FgGPD8/o8uAHYDecAuXddvT1YHIb4VzdCHS1GXrfvi3/KowZjPmGP4u3V3O4F//wI8HUceNNuwXPkzpOwjt6/jpXPLSzR/8gciqUFYSyZRsuDvQrZ97lqWv34+0WQ+hk79OYX9Txeyv6vqLT5b/fOo55w8858U5o4Rsv/Ymu+ypenIHa0DmCQrv5z7PiYDuRu3r3uQz1vDq7Y+NO5WxrrEw4SXtVTzvXXvEtDC6zz835AZnN9nhJDt2Qtfi6keMdaVzf2TZwnZP/OD5bTHEE3664ShTMjPEbL/Wb2XH6yKLARySqmDu8aKr9q6/Tr3v++n1RP+uTpzrIkZg8Xum+WLvGGdvoPpMxAmzhHbmWtdFaD5/ejXvuLbFhSbMefV/0oz2srDhF5cCrZvFiM5xG37/rQEPJFFGZSZ5ZjnRH6ujrUdv2NhfOwJP3l5PU9+vrfH7aYNyOU/N4gXpk46H90DH94t1vamT6C4V0RahXh156v89JOfourxaQoNyx3Gv077V8qHezb85a80PxhZ9TwiksSwdWuRDEa9JIt/fvcDAjE0tiJhcUhc/6e5ie1QAln/4bu899Df0XUNWVGQTWZC/i9XMOddcxOj5sznn7dcg7eze14tKwpX/O6v5Pfrf5R6fWzRW6qeY4C5uq7fp+v6fcB8uge684DIiVK9hK5pqCsOVezSNmxHD4gr3x1AXfNheKcPIOgjtOJdYdu6FqJ1+QNEkwD0165ANBx315r7iKXtuH3F74VsA6xY/8eY5yxb8zsh295gV1SnDyCk+1lU+W8h+wAbOiojOn0Av9zytLBtgId2rojo9AHctyN2yYRIxDO8r21vE7Yfy+kD+L9VW4Xt/3VzlCJ4wLv7POztEn9+l+0KRXT6AN7ZEFltNRaxnD6A6jjOiUTzotjXvub5QMxzoqFr+pFOH0C7SihaqYcYqJvqozp9AOqne9E9xvqfYqT0+NgTgqrGUwJOH8Bnu1po7hJTg+0VFv1WvO1TFySuH0ngzyv/HLfTB7ClZQuv7YxdEuhoovn9Yk4fgK5T91sDv3eSEXX6AAJRxrWjja7rfPzME+h697xTU9VDnD6Aj595guWvvvCF03fgvA8ef6hX+/pVJl7HL4fu4rQHyABydV1XgaP/ptf17gLEhxPH5DWmaW/0J1T3Ri8JELWtpqIFY78BdE1Q0tgffXJtxDZASI0ttx8IiV2fgOqJ67wOf2z5+Ihtg9G/ozMUu55aVPuh6I9GQFOFnfpkEm+fjCyruOMI5+wIiod8ugPR/4YEvBqSRxx/dsjAxCHmd3jEr7veEcdwoOno/lT+AXpMao+PPSCoaqKVSABo9xpfbE0aPXCMjsAfYfE3BdB0jQ6B/rX52xLfmQSiB4wtDgWrqhPUkzTxomsafnf0wSno89HV2nLE594u8bl0mp4Rr+P3B2CNJEmPS5L0L2A1cI8kSRnAwmR1Ll4kRUEqOSzcMteF5DAu/qGMnEakkgUAptFioXQAsslKxsDoqlWyJQtZUOClz7ArY56T1/ckIdsAA/rGDhEdNuAyIdsuWyFOc2y56bn9rxKyDzApZwg5UZTQruo3X9g2wFklQ6Men1NQkdQCs6IZDvH26dwy8RDnM/tGz/MqdSiMyBYXNprQz0Q0DZEhxeL5H/Gk9caoAhMVe0Xs6198hrEQJskkQW6YcE4JlHHi4V/yhNg5w3J5NnKqS//3jJQeH3uCw2JiSJFYDmaW3cSAghTO3+wzRbztyfEXR+9tZEnm3EHn9qiNTbGxoGJBcjqUIJTMTOzjxwu3L/rlLxLYmzTxICsKI2dHLy4/dPosppx70RFq+ZPOPC+ZXUtzEHGrekqSVApcQXd9IidQreu6sSrdcRJPDoOuqoTeWoxWXY9UnI9pwWxkS2Liu9WaHagfv4jubgNNBZ8HMnMwzbkEpb8xERBdDdKx+QX8jZsItu0m2La7W2UMMGUPoOTsR1DM4vVNGva8x/bld6OpPpDMSJIJXeveycrvezLDpwvmPACarrJm0/1sq3wRdf/un4QJ0DGZ7YwceAUjh4g7Zt5gJ4+svpWqjs10h8NKKJKCpqvYTVl8fczvGJQ7Qdg+QKO/nXu2Pc/nrVsI6KH9fwN8vc88bhl4tiHbAG/VbmdZSzVNPjebOhvxaSHMksIZJUP4zpDpmAwkoM9cGD1UZ8n8s4Rte4IhTv0w8jM30mnnweljhe0D/Ht7G0/t6sR/0AaTywQzihzcODSbbKuxHLaqFo33NwXY3agT2L/YLwNj+8lcONmCbMDpfv0JL2qEaFGrHU673JhjU/M/H97d4d/NrqlQcKJxx0kLafgfa4Dq/SvrxSas5+QhlxkT7dHqOwk8vQY8h10gk4w8uQzzzP5I1sjCEsdajh+k/vjYE3zBEDc9uZLF25q+2BhWJLCaJDzBQ+9JRQKTIjO8JIvHrp5EbkYiasMmCV2Hx06Dqh6G2I+4CC5+JDl9ShAhLcRzW59jed1yWnwt1LnraPW14lf9aGjIkkyuNZccWw7Dcodx1cirGJobfWEyFdD8fqq/+13cC98/5HPJbkcPBiEU5iVstVD6+9/jOu20Xuplz9FUjQduWSTU9pYHoztWRxs1FGLte29Rt3MbfYaPIjMvj6UvPY/f3cXgE2Yw5ZyLMJnNVG/eyKJ//5Og38ekM89n9LxjKir+qGJ0jIxX3OU64DagD7AGOAH4TNf1XrkDkyFXnSZNmjRpUo9jzfFLj49p0qRJk6a36JVyDnQPapOBz3VdnytJ0jDgN6JfmmjUHXtQP16J7vOjDB+ItnMvenMbmE2Y5k1FGSteWFYPBQl99Bzaps8h4OMLIRZJQuozBPPZtyDZxHfkPPtW0vDO7XBYrp2kWMib80uc/ecI2wZY+8E36WhcFfZYRs4wxs9/FMmArPOOPa+yYv0fUbWDU1lk+pacyLRxP8Hcg6Kyh9Pua+DxNd9lX9eRZQv6u8Zy06QHkCXxXaHH97zLQ5Vvhj2Wodj465hvMipLvCbhJ017uGvDQgLakTlTxVYnj04+lxyL2M5Ns8/LOUuiR5G9Mm0eeRliYXtvVtfx202VEY/LwEennCBkG+Afm1v5b2VkEZErB2Zy7ZBsYfsvrAiwco9KuHWtvjlw0RQrBZliu60ed5D3no0uDnPGlVZMEYrTxyLk0ah80B9RwUfOggE3iu/4Bd5vRV3cGV5TqtSM7RtFSFZjUuhaSCXw8HJoOSxP1mHGctMUZIfx+qQpREqPjz1lfXU7P35pPRvrOgipsReGMywKb946k/L8FA7zBGivhT8P63m7rFL4zqYjQtNSiVd3vMpPP42t6ikhoe9/8K2ylUdOfYRxheN6oYdi+LZto/LSy9A98eX8A6Ao5FzxdYp/8IPkdcwgVVtbePXPa4TaXvenWVgdqalWejDtDfU8/6u7aG+oQ1YULHYHfUeOZt+2LbgPy/FzZGdz3X2PYrakcMTAcUS8o7tP13UfgCRJVl3XtwApESegd7oJvbwQvaEZOrpQl65Fb2rtDusIBAm9vQStpU3Yvvr5a2hrPoSAl0NmSrqOXrWV4LtPiPdd12l4+7YjnD4AXQ3Q9P4PUf3iCa812/8X0ekDcLduYc/Gx4Ttt7ZvZ+naXx/m9AFoVNUuYuXGcOWt4uff634Q1ukDqGxfy7s7Hxa23eBvi+j0AbhVH99ee7+wfa8a5Afr3gvr9AHU+bu4ffVbwvZjOX0A53z2gbD9aE4fdGuD3LZ8g5DtBm8oqtMH8O+dnTT6xJQ3V1aGWFEZ3ukDqGqFpz4V19yI5fQBvPFvcft7H4vs9AFoHdCwUMy+2hVC/SiC0wewL0jgf81Ctg8m+L8NRzp9AJ4gwafWGLafYqTs+NhTgqrGdf9eztqa9ricPgB3QOWcf3ya5J4lgL8JhqZ37IN370psXxJIR6CDuz65Ky5VT/2gB9+v+bn2nWtTUmDsAHuuuKJnTh+AqtL6ryfoXPRRcjqVAESdPoDHvxdd7TxVeP7ubqcPulU7fV2dbF/66RFOH4CnrY1X//jr3u7iV5Z4Hb9qSZKygZeB9yRJegXYk6xO9QStqg7U6Cp0+t5acft7I8v9A+hVm4Vtq54m0KNNInUCjRuF7dfvejXmOY173xG337wy6vG6xqXCtjVdo6oj+t++vuFDYfufNm+KeY5XC9AZ6uGgs59tnc2oMfTxdnuOfAGmAvW++JyKVa1isv8v74lvMWPhPrFrv64q9gSooRO6fKk54dHiEJN1bxVT3tTiKNWg7TUuRKlXtUc+1mhUkjTlSNnxsafsaOiiPh5l1sNoi1HCIyVQDdzX656Pfc5RYkWteJhvQAvQ4GlIYG8Sh9rVhdYurqba8cbrCexN6qCGUnPcOpz2+voenV+zRXyum6ZnxOX46bp+nq7rbbqu/xz4CfAocG4S+xU3UlHsIs9SUb64/cJ+0Y8X9BW2rdhziPUTmHMGCtvPKYldTNdVMFHYfq4r+qJ2Tozj0ZAlmXx79GtfkS0uLhJPYXaTpOBUxELq+mdkxzynwJqaxXMLrPGF4ZXaxML15pbEFxo9NV9MlbeiIPZrLcsGjhSNKpHiiOKxloqFnckjYl97uUA89PsAUn6UezvzuArzTOnxsaeU5znIjCK8Ewm7YFhzryIZ6GP5jMT1I8GMKhAvLC9LMnn22HOoo4GckYFkFX9JZ5wQe/5zLGLkNu5NHC5Xj87PLilLUk/SHE6PbyFd1z/Sdf1VXddTogKvnJeNaf40sFq68+4G9oUDap4SyJNGIR9e6qEHmGacC/0i5Ahm5WI+9Wph25JsImfaHRGPZ0+4AVOGeN/LR12PxV4Y8bjJks2A8bcJ2y/MG8/wgV8Le8yVOYBJo78rbBvg62N+jV3JDHssy5LPWUO+I2y7IqOY2XmjIx6XkfjJ0MuFyy24zDZuHTQ14nGrrHDPmOilPKLxh1GxZa5/P0rMqZcliTNLY08Gnp0lJrU92GVlUl70yf8J+VYGZIk5CLOHmijPi/xqc5jh0qniqp5TT42dVzrvfHHnqeySGH+3DMVni10bpdCCPCyKQ+2QsFwkvlB2APOFo8AS5jeQwXKZMTXYVCbVxsee4rCY+NMl48jNiD+HSJbgn1ceA1o8V8SOgAmLbIHzU7e4dKGjkKtG9Fw9W0Lil9N/iclAjn8ykSSJsj//SSi3MmPmTFznp255gBkXii/on/998cX63uTsO36E2XboWJPftxzZdOT9JismLrwrdUumHG/EXc7haBJfOQcNNA3J3H1TaW4Pks2KpBiThP/CfsDXHbinaei6jqTryI7EJLPruk6gtRLZ4kBx5BHqrMWcWWJIdOVgAt42fJ5anK4KgsFO/O5GbM5iLLbYdfLiQVUD+ANthFQfFlMWsmLCYkDU5XC6Aq20eOowyxZkWcFpySHD0rPVpEgE1RAbOyrJUGxkmuy4rE5a/J2U2vMSUmNP1TXqvJ34VZVcqx3QCWgqhbbwDm1PeWDjGt6orcINWAAvcE1ZBVcPF18FPoCmabyxt5YP9zVgkqHVH6DYauPSwf0YmZdj2L43pLKjLUC2RWJ5s4/+GWZCus7YPAdWk/FlTW9QIxjUkGUZf1DF49fJzzJhM0sJ+W13bfWybzcUlICuQXszlA6AvgMSU6POUx/A16oSrAVrGUga2MvMWDKNvxfUgAqdKlKWiVCzH5AwOc3IzsS8L7/4ng4fIW8A3RfE5HJgyo59bY41Vc+jTTJUPVVNxxsIEdJ0PIEQtS0ecpxWXHYLAU3FH9SwKBLeoMbAwsS8y3qNXYuheh24+oC/rXsLRTZB41bIKAXJDxlF4HfDsFMh+9jYiQiqQao6qyiwFyBJEoFQgHpPPS6rC7vJjiRLWBUrgVCAZl8zFa7k1pFNFLquE9i7l0B9PbIsYykvJ1hfj5yZicnlwrNlK5quYcnJwZSbi5KRgSIoatbbrP5gF8vfqgQzBH1gNkOwCyQr6DI4naAGwOo0Mf2cYVSMjLyQn6p0tTbjyHQRCgaw2B3omoa7rRV7VhY1WzbhKirGVVB0tLt5TNEr5RyONj0d2LSWdrRtu5GcGcjDBiCZjE1mtKqtaNXbkAr7orc1ou1ciy5JKIMnooyeiaQYm4ip3ma6dryDt24NwZbtSIoV5+AFZA0/H9lizIHydlaxc9Wfaa1fAXqA7m1QGyUDz2bQBPEds4Npbt3MJ6t+Rqd7LyCRldGf0UOvpl/pScgGndc2bz2PrL6VJk8VOjoSkGHO5ZSBNzC57ExDqp7ukI+/7HiJ9xpW4deDSEiYJYX+jiJuG3QeE7IHGeo7QJWnnaf2rKXS3UqpLZP+zhx0YFpeX4ZmGttZiVbHzwx8aKCOn6ppLHh/GZ4Ir4e7Rw1gdqmxQejXa5p4r9Z7RCZkvwyZB6eVkGEgfKylS+VvCwP4D0uhtZng+tkWSnOMvRNWLPJSszP8saxcmHueMedvz5NegnXhj+XNk8iZKBYGC6BrOsGXmlF3+iCoA3p38UqzgjLdiXlaFpJsbEKo7usg+PQa8O/Pt1QAqwllUhmmGf2RlMi/bdrx6xnJKufQ4g7w2zc38emOJpq6Avj3i73IEiiShN0io2k6kiRx0vAifnH2KFyprjZ4zzBw9zDn/4y/wORvJKU7iULVVB5a9xAvb3+ZVn8rdsVOSUYJ29q2ISNT5Cii2d+MSTaRZ8sj157L+YPO56yBZ6W88+deuZK9114LB3LPzWYIHpRTKklgtYKmITud5Fx6CfnXXouc4s7fP275gDj0eA4hq9DEFb88MTkdSgJBn48tny6moXInLTVVhIJBnHn5eNpa8bvdZBeXUNh/IENOmElu6bGxwJIKpB2/w9Bq6gn+5w1Qu58oqbwMy6ULhL87tGoh6ofPRj6hzxCsl3xP3L67gX0vX4Xmaz3imJJZRtl5TyGbxSaRno69rHz7ku7tiDBk5o5k3Mniqp4AdY0ref+zm8Me61M8i9lT/ihsu81Xz2+WnEMkCcIxhSfx9TFiqukBLcQ5n/2c1lBksYsfDL6Yc0unC9kHWN9ez82rXkMN84xJwK9GncS8wti5huGIVbz9AKJF3Ge9G7vI8WNTRzHYJbYwccXifex1Rx/1PjpdLH/W49f41WvRhRxuP9lCkUvM+Vu60EtdDOkOmwNOvUzsud35Ny96DB2KnFkKeSeIhXt676mGzsjiMPIwG9bLxZ16dXMDwRciJ+pLfbKwXh05XCnt+PWMZDh+Le4As37/Ae5A/DNTp9XEpz+cR5YtRZ2/X+aHVdCOi9k/hLmpWx7gijevYE3jmh63O3fQufxqRuqG2HV+/DHV19/Q43bmfv0Y+MbrSObUvBfvv0lccduRo/CN385OYG+Sg6aqPH3XHTTsjrBCehCK2cxFP/kNZUPFS699lTA6Rh4jaaLxo67c+IXTB6DvqUGrbxK3t/zt6CdUb0Or3ytsv2v7G2GdPgC1swbPnkXCtvduejSi0wfQ2bIRPcrxeFiz5R8Rj1XXfUxHl7i43eI9TxNZdx7WNbxPu79RyPanLZuiOn3QXefPCM9XbQzr9EH3X/WfvesN2U8WdV5fXOd9a7m4Clcspw/g3Rox1dBX18Se3L20SlyFMJbTB+ATEyRF1/SYTh9A6yc9XCrej9Yeiur0AWhbfOgeMfsAoY8rox7XqzvQmo47Zc/jilfW1PTI6QPo8od4c524gnbSEXX6AD4WX8BMNnXuOiGnD+DVna/SFRB7z/YG9b8WW9gN7t1L15Jjo+xBT/G0ir+be5O969fE5fQBqMEgq98SzMFN02OOO8cvPEkOZTBkPlZjI8aTH8IR+xtSs//xWJYMfn+KR9AYJtl/nujL6Zi+7sdy33vCMf0jpYnE8fuzHrd/2PHL8XszHhv09Pqnf69e47hz/JRJo+CgnD6pfxlyHCUfImGafHr0E/oOQ45R8iEazsFnINvDi6woWX1xlItv6ZePug6i5MBl5o1GMqgNPG7EtyIe61M8myyn+LU5sfxyog24Ywvn47KKqZ5Oyx1BbgwBmm/0P0XI9gEu7jMKJcLLTEbia/3GGLIfC9HXaLE9vvyxv08ZKfgN0D8jeu6nBMwvEwsjPWtc7PCe8yaIhwCVVMQ+xyaYXiJJElIclz9npliYquwyQVb0Z14ebkNyiOdAmk6MfoGkvi7kvPhKeqQ5Opw7rgyntWf3QJbNxILRJUnqUQKQDYT9nXhn4vqRYIoziplQMEGo7bmDzsVpUEcgmRT/5MdC7czl5ThnpG4JDiNk5CVWgCtZ9Bs9lqIBg+M612S2MOH0s5PcozQHOO5y/AD01g7UbbuRMjOQh1YYVvbUqrej1WxDKuiD3t50qLjLyOkJEHdpoWvnu93iLs3bkU02nIMXkDnsXGSLsQRlb9c+dq3+My11y0DzAzKSYqN04LkMGH+rIdsHaGnbwqerfkF7VyUg4XJWMHroN+hbMse4uIuvgcdW306jew8aGhISTmsepw28kQklpxsSd/Gofu7b8QpvN6zApwWRAItkYkBGMbcNOi+uWn+xqPZ08J+9a9ntbqPE5qTCmYum65yQ15chmcbqJ5248DUiBe1ZgA8MiLvous6C95fSFeELfj92INOLxEuNAPxuXTNv13iOCOatcCr8Y1oxDgPKnq1ulfveC+A9TNzFboYbZlsozjb2Tli52Ev19vDHsvNh9jnGxF2qnvbi3xf+WN58iZzxBsVdXm1G3e6DkA663r3aapG7xV1OyDIs+KDW7hd38R0k7mIzo0zug2l6PyQ5Le6SKJIl7tLmCfC7tzazZEcTTZ1+fKEvxV1MkoTDqqDqOrIkMX94ET89ayQue2rmVH3Bn0dDew9TM87+O0y4Ijn9SRCqpvLo+kd5cfuLtPpbsSk2ypxlbG7ZjCIplGSU0ORrwiSZyLfnd4u7DD6fBRULUl/cZfVq9l5zLXi93R9YLeA/qFqKJIHN1i3ukplJ7uWXk3f1VciO1F5ceuDbH/Q4+ji71MLXfjozOR1KAkG/j62fLaGxchfN+8VdsvLycbe14nN3kVNcSmH/AQw+YQY5xaVHu7vHDCkt7iJJUiXQCahASNf1SZIk5QL/BfoDlcDFuq6HT3LbT7IGtp6ghYLg7kB2JafYaaCjBl0LISs2ZFsWaAEUa2JKFng6a/B7GzGZ7AR8HUgmC5nZFZgtWQmxHwh2IssWdC1IMORD11Uc9gLDu4kAmq5R2bqOLn8bNpODUtdgNF3FLNuwJ6hkxKb2PYR0jQyTjUZfG8W2HMozihIyIHpCQUyyjCcUQEYiyyI+YQ/HLZ8uYq2n85DP5mfm8POpxgcHbzDID1dsRNJUqtxBFMBpU7h1xCDG5hsv5wCwpzNAhz9Ea1DDZZLw6zoTCzIi7pT2hDZ3kMrGEBkWCYtZ7p4fWGQKsxJTJmXLOi+7N4MsQ8ADmgYDx8CoiYkp59C40ktnFeADR1H3LqitFFxDjdvXdZ3gDi9qSENxKKCA3qVhqrCh9HCnJxyqP4Ra3YaUn4HU6Uc3K0iKjClaYff9fJUcv0SMkckYH/2h7pINSJBhMdHlD+ELqNR1eMl3WinNtlPV4iHLZsZskjEpElaD6tm9xroXYc+nEAqCMw92fATZ/cCWBe6m7v8tHtX93+Mvg8IhR7vHcdEZ6GTR3kWcUHwCstJdmL3d306LtwWTbCLDnEGOLQdVV9nWuo3hucNT3uk7QLC1DbWlGSU3F/+OHWCzEdyzF8lmxZSfj7WkBC0YwrNiBa4FpyNbxISvepvn//AJDbviSOoGCgdmcNGdkWsDpxp+jxs1GMLhchEM+PG0t6KpGpl5BXjaWnG4sulsacbhcmG1p7aTnmocC47fJF3Xmw767A9Ai67rv5Mk6QdAjq7r349m52g7fqElL6Mue6N7Zdxiw3zxnchF5QmxHWjbRe3LV6OrR9b7NecMpGDe3Viy44gtC4Pf08iy188DPfyykjWjD2Pm3o8to1jIvs/fwscr7qKhedURx2TZypwpf6SkcIqQbYC1de/z9IYfRTw+PH8m3xh3r7D9pS1buW39A2GPyUjcP/YWxguWdAhqKr/ZvJj36neio3+xqzUwI5c/jTuNAquxndw7li1hWUfU9RLuGTWJacVioVcLFi6lU4v+bvhw/hRMUXZuolHVFeSqj+uIlKb+jYGZXD0kW8i2puvc/aoPb4TVVFnq3vUrzxebqDbWBvj0zegJ9hPnyvQZYBWy37HNT8Mr0QVYyr9pxuwUc2CDSzsIvdEW8bjU14LterF3AoDv8RVQ0xn+oCJhuW4yckHk+/8r6PgZGiMTPT4+umQ397y9BV+o+x40yRKhGO8Cu1nhu6cM4bpZxqMkksamN+C5ywUaynBXLZgTu2iXSM5+6Wx2d+w+5DMZGe2wmBC7Yserdu+cSUj8eOqPuXjYxb3Wz56i+f3svvAiAtsjhFdEwD5jBv0ffSRJvTLOu0+uY/snYqKD5aNzOPOW8QnuUeLwdnbw0u9/Qe32rQCYrFZC/ujObcX4yZzzf3ehhCnunuZIjkVVz3OAJ/b/9xPAuUehD3Gjd7WhLn292+kDCPgIvhreWRCh4b3vh3X6AIKtO2le8nth2xsX3x7R6QPwu6vZtfrPwvbXbH4wrNMHoGl+Pl7xQzQtFPZ4LDRd5ZkN0eP7NzctYUP9IiH7AHdu+Gfk70fnzg2PILow8sq+LbxTvwPtIKcPYKe7hfu2LxWyeTCxnD6AOzeITQbdwVBMpw/gyk/WCtkH+L8VjRGdPoDHd3biU8UUZz/YFIjo9AFoOjz5WfhnLh5iOX0AKz8UV8uN5fQB7HlIXKEwmtMHoFcFUCvjU3Y9wvbe1shOH4CqE3h2nZDtrxBHbYzc0dDJr17f9IXTB8R0+gC8QZW739jMtvoov/3RRsjpA9Dg3+cmsicJZUvzliOcPuAIpw/4wukD0NH59bJfJ7VvRml++OEeO30A3k8+IVjfkIQeJQZRpw9gz/rYY//R5NPnn/7C6QNiOn0Au1cvZ+OihcnsVpqDSLbjpwPvSpK0UpKkA8VYinRdP6D5XAcUhWsoSdINkiStkCRpRWOjmGR/ItAawuQDdCXuwQt1Rpe/DrRsE7btc0dIEjoId5u4/db2rVGPB0Nd+PwtQrY9wXb0iBlsX7KtRdyJCujRndIu1YdHjS8M43C2dUZ+sW/rEn/p9warmtvjOq/GK3ZtABp9sZ2nWsGSAhtrYt83bvGupwaCfmW8CxlatdgF0nfG8W7sPNYvfkIRGiOTNT5u3NdhqP0mg+1TlrrULL0D8MbuN4TbarqGN+SNfeJRwr0y/MJyPPg2bUpgT9LES8PuXULt6naJz0XT9IxkO34zdV2fAJwO3CJJ0okHH9S7ZyFhZyK6rj+s6/okXdcnFRQYE5Ewglw2GA7LVZPyyxJm35I/NOpxe+lkYduZebFVF7OLxO0XF0QP43TYi3DYxQpBOy25mOTYoXITS88Qsg+QqUTPlSqyZpNhEgvvmZQT+R6Zkpu4+ycZzCgKrzJ7OJNyM4W/Y2AcYYp9Yyh/RuLEobFfa/lG0kNTIC1GEkyJkCQprre+MkQsj1AZEztEVCoyFuZ8nCE0RiZrfJxakYdZFrvBzYrE1AHxvTuOCgaEwBgmPs4kmyuHXync1iJbsJsSk5OcDFyniitrOyZNTGBP0sRL+ZhxQu0qxn4lovtTgqQ6frqu1+z/3wbgJWAKUC9JUgnA/v9N3f14QLLaMZ15A1gdIElIeaWYLvhOwuwXnfoXFOdhakaSjGR2kjHgZPJm/lDY9ohZf8LqiJzjlVc2h4pxtwnbHzP0OoZUXITNkoNJyUCSvpyoOx19OGnafcK2AW6b8gQy4Sf/JsnCSRXXUu4aJWz/XxO/izWC/UyTnQfGfVvY9inFg/jmwMkU25xkKGYUJCyywqlFg/jmQPG8xwP8ZPi4mOe8c+KpQrZlSWJGbnThHxm4d5J4OYe/TC0k3xr59fP7iXmYBCeg48ut9I2iPeO0wvWzxfLvAE67LLZy4fyLxNUN+90QW5hgwM3i+UaWa6MvxijTM5ELxcQR5DwH0pQ+kU/ItGC5fJyQ7eORVBsji102Hr5yEoMKnFhNMg6LQlGW9Yhn0bT/nxJgNUkMLXby0BUTKXGlrhPBbYK7drZcuODhxPYlgRRkFHD2gCOl8HNtuYfUopWQGJQ9CPP+shY2xcbjpz7ea/0UIfvSS8k884we13jL/+4dKJniC5PJ5tzbxgq3PfXG4QnsSeKZet7FjD7pVEwWC7LJRG5pH0yWg8bbA7/l/v+VTSamnncxg6dOPwq9/WqSNHEXSZIyAFnX9c79//0e8EvgJKD5oMT1XF3XvxfN1tEWd0mTJk2aNL3DV0XcJVFjZHp8TJMmTZqvDkbHyGRK6BQBL+2XCzYBz+i6/rYkScuB5yRJuhbYAxiSlNJDKurKjej1TcjlpchjhiZFoljvbEVdtRDd24kyYjpyv2EJs9225l90rH8aXZLIHHIe/sZ1hLrqyaiYR+6UyAXS42H7ij9Qt/OFIz4vGXABgyZH9bfjYseeV1m29rcH5ePJKLKZsqKZnDD+Lswm8bCuDn8Tf116FZ2Bg3PiJAodFdw86UEcFmPlLqq8jfxqy39Y1/FlTLqCzMisck7IHc4lZScKh3oCVLrbeHT3SrZ3NhHUdPxaCJtiYkRWPueUjWBijnjdGk3TOPGD6LkdSwzU8av3eLhwSWQRjknZTv48RXy3dWdHgDuXN9IcODJZzWmCJ08sJddAWYFASGfRlhCf7AgROCiVM9MKX5smruh5gDee8hKKkqp29jU24feQFtLY9YAfIuirZAyHkjPFd1Y0v0bgqUb0Kn93EKFO99aNDNhkTGflYB4h/txqdZ0E39yK3uQBVeuWUQ3u/53tJszXTUZxpa5CYi/SK2OkCD94YR0vrKpG03QcFhOKDKqm4w9pSJJEjsNMsztAUO1eOO7jsvLYNVMZUpS6uywAPHUJ7Hi7Z22Gnw+XpPbOGMCj6x7lsY2P4Ql60NFRJAW7yU5noBMNDXn//6moyJLM9NLp/HXeX7/YAUxFfDt3svvc8yAYp5iVJGEdMoTyp59CcaZuYXpd1/nHNz8UanvLg/MS3JvE0tHYwNKXn2ffts3Ys1zYM7No2luJp70NWZGxOjPpampCDYXIzM+noF8FfUeMYuwpZ6RVPXuJY76Ae/DVD9A27/zi38qMCZhmJja2Ww8FCTz+E+jY74BIEuYLv5sQ56994/O0fh65JIFzyFnkz7pLyPaeDY+xd+NDEY/3G3E95aOvE7INUFP/CYuW3hHxeI5rCAtmPylkW9M1fvTBLLQIAixWxcmv5r4vZBugPejm3M9/iVeLPHuflD2Ev4+9Wch+S8DDJZ89h1sNP2BJwF/HLWCSYL7fzIWvxTxHAj4WdP5mvft5zHO+M7Sc88t7Xi7Cr2qc+m5N+OTe/SjAe6f1Ea7n98QnfrbURlZAuessK84ooabRWPyal9YYwXeyAmddLeac7fizF2KI4eaeKJM7VSxc1XtvDbRHF86x3liEXNZz+1ogROCPS7qlUyMhge2uuZEPf0V2/BJFonf8fvHKBh7/bE+P25lkiXU/PwWHJUUnb89dDZteEms7/26YKR76n2ye3vw0v1v2ux63G5E7gv+e9d8k9Mg4uqaxZYRYOoGSk82Qzz5LcI8Sx/03fWCofao6f0Gfj0dvvwF3a89F/UbPO4VTbrw1Cb06/jgWyzkkDD0YQttyqIKQuj7xykB61dYvnT4AXUfd9GlCbHesi+4YuXeLvyBqtj0V9Xj1tv8I2wbYsDX6Kmhr+zY8XrH0lKqOjRGdPgC/2kWrt07INsDipvVRnT6AFW3bqPeJKbguaqiM6PRB9ybLm3XJVbESXdJpC8S3uvq3rT2fHAK8urcrZt9UYEOrWMkFt1+P6vQBLNkmphgKxHT6ADRx8zGdPoDWz8RkPfWgHtPpAwgsik/Z9XC01fuiO30AOqjHq/rjccB/V1QLtQtpOq+sqUlwbxLIltiLZRH58O7E9SMJ/GvDv4TabWrZJFyyKNl0vPOOcFu1tY1AdQrfi8cplWtXCTl9AJsWf4BmaOBMEy/HtOOHIoP1UBECyZ6EECL7kSEDki0xYQSyNYaIhgHFLSVGmKXJYuxvsNliKbhJmE1i8oMZ5uzY328gjNRljv23WyQTDpPYrkq2JfZ96ErRgsC2OIuyOxSx10eRPb4dAZdFzL5Z6f7/qLZTWIMiHmQx7ZXurdQ4kLLEQmGlrPjuacmRuuFlX3Xsgs8dQFGcv/9RQRF9aACDY2WyybZmC7VTJCUpqTGJwFxmTP1acabVg3sbe2b0+Ww0bM5MZNlYCkaa+DimHT9JljHNnvylSpBJwXRi4iOE5OL+yMOmfvlBZi7KxPkJsZ0/+2dE04fPmSq+9T1s2m+iHh869efCtgEmjfou0fo+fNDXMcfhYIUj39GXQkdFxOODcqdgN4vnk0zPG864rIFRz/lG+SlkCjquJ+b3Z4wrbIlKAIqsGVzad7SQbYivosCgMAsW8WAzxffyfWiqWI7ficUOimzR/4IBGQr9nWLOgcUkcfLIyM5lhgVOGCgejjZmRuxz8mJXNYiINY7Uz5KLxSaxkiwhj4lxTytgPjmKLGq0psMLISeGV51tQ84+xj3v45h7Lxon1K4iP4N5wyK/8446Z/5VvO01PcwL7GV+OeOXhyh4xss1o65JQm8Sg2PMGGSXWB6/c95clOzsxHYogZgMrEHIKRpJDdBnxCgGTZ7W43aSLHPi176RhB6lCccxn+MHoLd1oDW0IPcpQnIkb0Kh1VWiezqQ+w1HMiVuxVoLemhddj/IMjmTbsZbs5xA02acw8/DnCFWB+8AwUAHa9//Jt6OXUiyAyQdR1Z/Rs/+C+YYu43xEFIDLF3za2rqPyUrswKnvXvGO3LwleS4Bhm2v2Lfm3y4+98osoxJtiBLZub1v5oRhXHMvmOg6zqrWrfz4O432eHZh0Uyc1rRJEa7+jPYWUq5w9gkRtd1VrXtY0tHE9lmO3s8rZTYMymyOpmYU4pVMfYG//XqpbzVHD7u8CfDxnBqn3JD9n+yYgOLWrqO+NwKvDFvElaDidhvVnXy7K5Omn0qbq07NNUmw/dGZ3NSqXGRiKYujXVVIVbuVunyg8sB0wYpTBtoYNTdj6crxHv/DR8SO2kelFUYew91bQtS93YIDo9GdkDF9VYUA7syAGqll+CnnaBr4NXRS8zInTpSvgnTXBey4G7uAUIb6lD3dYI7gOS0oLV5od6NPK0flonRV/LTOX49Ixmqnk1dPr7/v/WYZBhWkklABXSNhs4AZlmib54DsyLxjw93kmU3ccfJQzl3fJQyHqlCey08cjJ0VhNXMLyjCG5fC5bUX6joCnRx3+r76PB3oGoqKionlp3IG7vfwBP04LK5KM8sZ1PzJuwmO7dPvJ2hudHrCKcC9f94gJaHHwbfQWpXdjtKcRFqczNIMqbsbOSsLBSrlbxbbiZzWs+dj97m4xc3s+7d2h61GXVSMbMvGpGkHiWOfdu2UL9zO5n5BTjz8mjYtYP2pgZ0Tads6Ah2r1mBp62NISfMQLFYKKoYRFb+0avXfayRyqqevYaUnYVsNqO3doDFghTnjkW86JqGXl+JlJGNXNwftWY7dLYh9x+JZBOspHwQstlB5ogL8FR9Steu97HmDSKj/4mxG8aB2ZJFv5FX0d64Hk0Noake8vrMoanqffL7nYzZYAiLIpsZOuBiclxDyMkagiRBe+duQqo3If2fVLqALn8T6+o/QMaM0+SiwVNJdmchpZmDDdmWJIkSex5DnX2p9bdQZs0loAfpCnkpteUZ7rskSUzMKSPP4kDVdQptDtqDfqbm9UGRjG+2n1baP6LjN6fYeJH4XKsVONLxK8+wGXb6AMbm2lja6GdApkZI19ndEaQ9qMfOEYsTSdfYUa+iKDCsCPZ1wLKdKgPyghRlG1u4sTki/37ZecZ/W0spYOYIxy9rLIadPgC50IJcZkbd4gUzSFYZ03gnSqlxpxhAHpCL3uxBL8pF21gPXX7kkYWYJ4gr2abpPfKdNh65ahLvb27go22N2M0Sqg5j+7ioafPy5vpachxmXrllJk1uPyNKjCks9xpBT/f/I4NiBtVPVAfQmmEwYbf3aPO3MSR7CAE9gDvgJqgFqeyo5IyKM3DZXGxr2campk2UZZQxJG8I/bP6H+0ux0X2aafiWbYMtbUVuagIPG4kxUSwrg5zQSFqIECorQ1ZUXCddeYx4fQBVIws7LHjN/3c1HfUAUqHDKOtrobW2n0UDRyMz+3GVVBEwOfF73EzfOZcFLOFXauWkdenb9rp62WOix0/dc1mQgs/7ZYOdzowX3w6ckGs/LP40DtbCT5/L3rrfiERmxN8+yfDkozpzBtRhhhTEW344Ed4DhNxseSPoHjB/chm8ZVGXdf5/OVTCQUiCTVIDJ36Cwr7ixX6DgQ7eWfJ9XR07g57PCdrKKfOegRFMLciqPr4yaKTIoq8DMubwTXj/yRkG+CP21/gf/s+DnvMhMyjE77D0My+wvZDmsaPNyxkcdOhIig22cSTUy6gzCG+43r2ordoCUVXAbmq30CuHyK2OhiPqudzM8dSIrjD/sf1zbxW7Yl4PFOB108Rv/YvrvSzfHdkAZQRZXDFNLG+V+3wsuqj6OcU9YUTThGzX/+ej8410d/LA79rQxIscB9a4yb4YnPYY/IgG9YrDUYZrKhGfXt7xOOW26YjZ0bOnU3v+PWMZOz4tXuDzPvjIprd8QksZTvMPHLlJCb1T8y4mxSevRK2vCLW9uz7YcLXE9ufBHL353fz3609U+eUkHj8tMeZWJRYFfREUnPnnXS89nrPGplMDP5kCSbBMNHe4PEffIynLc4SFYcx85KBjJ1rLJonmXg62nnkW9cS9EeoRxQGe2YW19//GGZrCucIpxBfaVVPAD0QJPTh0m6nD6DLg/rR8oTZDy1780unD750+gB0jdDCJ9F1MYU9gEDr7iOcPoBA0ya6thlQIQP2bvpXFKcPQGfn6j8K29+6+/mITh9Aa8dW9uxbKGz/1W1/jarsuaX5E2o7dwjZ3tpZHdHpAwihcffWZ4VsH2BJ054jnD4Anxbinm1LDNmO5fQBPLF3Z8xzwlHdFdkhO5gbP18vZD+g6lGdPoBOFZr9cchbRiCa0wewqaa71p8IsZw+gPoqIdMAMZ0+gNaVYpMGPaQTfC280weg7fChVsc/YIdDfS/6Mxn83wZD9tMkn/ve3x630wfQ5gny6zc3J7FHCUDU6QN41Vg93WRS3VndY6cPQEfnJ0t+koQeJQbV4+m50wcQClH749T9uwBhpw9gyX/FxvXe4sN/Pdwjpw/A29nByjdeTVKP0hzOMe/44fPDYfLzeseR4WnCdMSQpvV2gSoeChJyRy5JEHLXC9sFcLfFLheghuKb5IfDE0c5hS5Pz0IZDqa+K/YLrtkrJtlc749dpqEl2Clk+8vviHwf1vvchmwnk03t8fWtIyS24OFR42u3zy3m+Klxhop6Aqkf7RCJQL1g3wMaxJhz6G0GQ9vU6H3TO4w5lmmSz+6mnr+f9rUlJrw/KRiObErdd0VdlDlELFrjGAePFmpz5AWqWAT2iJUaSmOc9gaxeWtTVWViO5ImIse84ydlOZFKDw1NkocPSJh9ediU6N9fMdqQ0IuteDySEi7sSSKjwliRzvLRN8Y8JzNPXFmyvPTkGGdIlJdGLtQci1MG3hD1uCKZGZI3Neo5kZiYPZgsJXoo3kkF44RsH2BmfjmWCPLEZ5Wkbqz+KWXxxduf3UdM/CbbomCPIw13VI5YKQ1FlmKWc5AlyI6SpxfVfrIrEcRxbXJniOVYSg4F+kUJvZZBGWRQyKIget6zMk08hDdN73Dl9J6Hkp05JoXzNyUJQ9OdrNS9Z8cWjsVlEQtrnNc3NQuBA1j69gWr2BiQf8P1Ce5N6qBYUrP8xgHGnXqGULuJZ5yb2I6kicgx7/gBmC84BWXiSKT+ZSgnTUM5YVzCbCvDp2I6/Vqk/qOQR89COelrkFMMjizkkTMwnxnbuYqGbLJRcvZjmLMrunV6ZTPm3EEUnfpnrAUjDdnOyOrPwAnfQ5IPj5uWkU0Z5JbOYvTsvwnbLy6YzImT/4DTUYosWzArTizmLBTZSoajjLlT/4wrU9wJH5Q7iTnlV4c9VuDoxy2TH8GiiMWEZ5hsPDT+NgY7jpysmCWF84unc8eg84VsH6DMnsV9489gXmEFwzPzyTXbyTXbubr/OC4vH2PI9juzTol5zpL5Zwnbv3Vg9ElcH6uZO0ZELrcRi2dmlZATRaTkTxPzDNWX+t4CK9YIDpoiwZ2ni4uYnHllbMforG+ITVgABnw7+j3tmgGWHHEBK9vXCmFwmP7lyFiuK0SyGRsWLNdMhNLMbu/6MKRRRZin9DNkP03ymT2kkN+cN4oMFo85GwABAABJREFU66H32eG/qMMsc8KAHO48dSg/OH1Y73VQhO+JpQVgzoA7Ujc82Syb+c+Z/2Fc4TisihVZkg8p7WCSTFjlQ593RVI4tfxUfj3r173d3R4x8I3XkZw9E6DLve5aXGeemaQeJYar/jBduO1NfxNfTO8NRsyay4xLrsBssyErJuxZLmSTCUmWu0uwmS1k5hd2f64oWOx25l9/CyWDhhztrn9lOC7EXdKkSZMmzfFBWtylZ6THxzRp0qT56pAu59BL6AEf6pKX0Kq3IZUMwDTrfCRbhmG7LSsfoWPtv+AQERMJ55AzyZ91l2H7HU3r2fjxd8OKvDhzhjFm3kMoJnElpZa2LSxZ+RM63Xv3fyJhtWQzbvg3GVR+jrBdgHr3bh5f811avfvQD8mxkBhXfDKXjvwFsoGyCF1BL1evupdqX9MRx0ySwtvT78ZpEg9729Bez+OVq2nxe+kK+WkKeMm32PnZiLmMyjZWI7C6s4NLl0ZXGfn4pDOFd83erq7j15sqo9s/5QQh2wAPb2nl6d3hcyBnFlj46fhCrIr4jt+K3SFeWxPsrj92GHYz3HGaFadV7N5RQyqvPxFd+GLO+QquHLFdRc2vses+f9S0okF3GgvHVJuDBP5ZC2FSfJVzsrFMFFec1T0BAi9tQt8dJn/IInerekbajk1z1FlR2cJ9H+ygstlNfYcPX7A7J1eiexNXkrorrkhIaLqOLMH0Qfk88Y0pyIJKs71Cy2742zixtj9tBTl1A6Te2/MeP/vkZ3TGmZc+tXgqD5/ysKHxszcINTez65JLUaur428ky/S5/+9kzk3dnbGqbU28+qd1Qm2v/8ssLLbUfX8GvB4WPfkI25d+RjDg7y6HpmkoJjO6rqEGv0wylySZiWecw+wrrj2KPU4Muq7TtaQGz9pGFJcV1ynlmIuM+wjJILWf+hQitPBJ1NXvozdWoa37iNDbjxu26an+jI41jxzm9AHodG17jY6Nzxmyr6kB1n14c0Rlz67WLWxa8n1h+8GQm/c+uekgpw9Axx9oZena31Bdt1jYNsA/ll9Pi7fmMKev+zvW1L3L+7seM2T/5jX3hXX6AEK6ylmf/UzYdnvQx+1r3uKz5iq2djVR4+vEr4Wo8XXyrTVv4FXFVb2AmE4fwKz3BRTR9hPL6QM494NlQrb3dgYiOn0ASxoD/GOzuOhAY6fKCyvDO30A3iD8feHhldHjJ5bTB7DoRXGBlN0PRnf6AHb+Q1xIQ9d1Ag/VhXX6ANRX2tA6xBVVAy9uDO/0AQQ0Ag+I3Tdpkk9jp58rHl3GR9sa2dPs+cLpg+5bUtUhpHU7fqquf/HZx9ub+MGLYiq/vYao0wdwt7ESJ8mk2dvMHYvuiNvpA1hat5SffvLTJPYqMVReelnPnD4ATaP6mzfj2xpb3O5oIer0Afzz9shq5KnAwkf+wfr338XX1YkaCKCFQuiaRijgP8TpA9B1jRWvv8Se9WuOTmcTiHtpLe1v7CZY3YVvYzONj25AFxTASzZpxy9OtB1rDv33rrWGyjgAdG6JLl/budWYvG1ny0Z0Lfokta1hpbD9hua1UQu1G3H8ugIteEPRB7KVdW8K2wfY5tkX9bg3xrWLxoqWGjwRnLuAprK2TVyJLdlsau2I67xmwZfaYzti219UJ642G6uUA0C7F7QUDXPX47jtdAOisHpzCHzR/3Z1hZgysh5U0Svbop/UJf5cpUkun+xowhsUW7R4d2PqvtMMoxlbqEsmr+8SW+D7sOrDBPcksWhuN8Eq8bo4XR/FUXcnTcLZsSJ2DeDDWfqysU2OVMC76dAKAFpHgEC1MWX4ZJF2/OJEyi0+9N/ZhUgGwySsBdGT4S25gwzZtzn7xDzHbBMvuJuVEV3pLDNDXMTBbspCinF7Fmb0F7YP4IwhDGMkaKmfIzvq8b6O1C0u29+Z3PCEKfmxhU/6ZoiHsvTNjf3LKTLIBsRjjmWkzNjCMFI/QXEakwyZMUJcv5qX/ZhgQIH4s98nx6AabBohRueLKXOXZJQkuCeJRbLbhVU9ASwV/RPXmTRxk1NS1uM2ZUNHJKEnvYs5/7D3nyxhyk3Nd2La8YsT00lfA2d29z8cmZhOvsKwTdeoy1Cc4V++kiWT3GnfMWTfai+gdPAlUc6QGDFdXNUr09mXMUPDl1woyB3HkIoLhW0rsolTBkZWTLUoDi4Y/kNh+wC/Gn5l1OPfH3SRsO3BmXlcVT4OU5jFgYv6jKTMLp5DBdA3jpoCN/YfLGTbYVZwxfFm+M/0sUL2F/TNxGWOPPtXgO+OEl+QGN3HRHledO/iwknijuXQCbHPyY6vIkZY8k+L7ZgVXySeni1ZZUynZkc+odCESbCkgyRJmM8aHlbR8wDKBcbUitMkjzF9srlp9kBMPczVsygyf798fJJ6lSCGnSve9ux/JKwbiWZC0QRm95ndozZm2czf5oorevcGkixT8tvfCLV1nnwymSedlOAeJQ5L9Io3Uek/Ljth/UgG86+7GZszM+7zHdk5TL/w8iT2qHfInNcXc59uBVrJLOM6owIlS1w9PJmkVT17gK6p6G2NSK58JCVxujj+xq0EWreh6Tqquwl76QTsxeMSZj/gb6O5+mP8viYk2UbQ14ArbzT5fWYjRagz1xP8gQ4am9ehaUFkk5XszAqcjsSsJnqDnexsXYVFttPma6Ar0EJ59igG5sYx+46DkKbyZt0y9noaKbHlsMOzj5Cq8f1hF2OSjF+b9qAPTyhIrsXOurZ6Bmfmkm1JzCqQNxjk5I/ePuJzGVhsoJTDAfZ2urnis/UcHjhZYoLn5okLuxxgQ4uPB7e04Anq5FtlvBpcM8TF2Dx7Qnbjmrs09jap1HWE2NfSfV36F8rMHGLGbDK25qXrOq896UM/LAJMkuD0r5kwGxQv0TSN2lf9eKuAAGAG/GAuh/KLE3P/aD6V4LoutDVucEhgU7DMzUHJMy4coIc01OpW9AYPmlVB39OKlGXHcmJ/pBgiGWlVz56RjPGxxR3AG1TRNZ1Ve1txWBSy7GbMiky+08LGmg4GFDhp6vLjC6rMG25MrKrX8HXB/dPB2wSOAujYnz9mtoMaAs0PJgeY9u805Q6AGxYevf72gH2d+1jTuIYtTVswm8wUO4qpcFXw8b6Psct2KrIryDBnENJCzOk352h3N240v5+2N96g/a23UVtasI8bh3/HDtSODiyDBiIDajBEcNs27NNOoOjGGzEXpm5O5gHcrV7+9cPPetTm5gfmGipz1FtoqkpzzV5AQjGbaKmpoaC8gpDfT+u+atztrQR8fkqHDqNsyPCj3d2EEmr2ImeYkW3J085Mq3oehN7WgbqrGgIBpOws5IH9kMzG/0Qt4Ed9/yn0zhakyafB8nfQ3a3IY+agDBxr6EHUdZ1gZxXuyo8Jtu5AUiyE2nfTsfE5MgefgaPfDEN9D/ha2Pr5z/F7G8nIHkZr7adoITct1e9jyyglM89Y7SW3p47NO/9DQ/NqOt3V6GhkOvoysPxshvQ/D1k2dv3t5kw6/E0sr3mVoOrDE+pgZW0m40pOZV7/q1AM2PeG/Ny5/lE2dlWCDjo6GbKNkdnlrGzdzpScoYZfsq0BH+va61B1jQ3tDbQF+3Jy8UBDNg9w5Ufvhf1cA57dtY1LBxiri/O1z8KLNdSGYFVdCxOKxXflABo8Ada3d+cT7fR0u5ffWd7M7cOyOLfCWChslz/EY4uDtByWKri9SUPTA5w0UlzJFmDr2iOdPgBdh8/fDzFrgTHnqWOnH+/2gz7Yr0UT3AO+liC2XGP2vW80wtLD8nPlIEFrB/KZuYbv+9DGOtTFlRDUwGmBTj+6WUEtysB0rDgJX2HWVrXy5Od7qGv3YVEkXA4Lki7R5g1Q7LJR3+5DMcncOm8QnqDKW+trmTe8EKvJ+GJZUvn8Qejc0/3fHQclyh4sjBLq6v5/gH3NsOUdGHZq7/VRAF3XeWDNA7y5+02QINeeS6unFVnurulnkk2MyBtBu7+dne07ybHl8PSCpynKSP1nce/Nt+D95JMv/h3cuPGL/w5t3nzIuZ27d+Nbuoz+z/4HUw/r//U2rz+wqsdt/nP3Ui7/ifFF12QS8HpY/vpL1GzeSPHgIUhIVG3aQMDjJqe0D7klpXS2NOPt6qRh9w5Cfj/lo8cd7W4nDFNeaoZ3Hsxxs+Onbq8k9NJ7h6jhSbnZmK88B8kqvt2qBf0E/34raBES3geMw3ret4Tt1731bXz7lkc87hx8Jvkn/ljItrt9F6vevizqOUOm/pyi/qcL2a9rXM77n32bSBKEmRl9OXPus4acvwdXfJNdbeFfkFnWAn408xVkgZ05vxZk9sd3Rj3nlIIJ/HJE9HDQaLxVu527Ny864urMzOvHH8Yam0jMXPhazHNOLSrjJ6PFdkZnvRs7QfuesYM4oShfyP6fNzTzclVkAZdJuWbunVoc8Xg0Orwav30jumpncRbcdorYC3rpB17qdkc/R5Lh7G+I2W9e7qd1UXSBmrKvmbGXij1X3j/VQFsUAY8MGfv3Y+cHR8L/3Dr0bc0Rj8vD87FcEDkvKb3j1zMSveN3x3NreHFVTY/bDS/J4sVvTsduSVHn7/GzYI+g4Nj8u2HmtxPbnwRywjMn4A72XPHp9XNfp9xVnoQeJYbNo8dAUExYZ8ia1Sg2Ywt8yeKBb38grhekwC33z0tofxJFV2sLj3/nRgLenqlOTzj9bOZeHT5tKM2RGB0jj5scP/WTVUf4H3pLG9qmHcbsLnk5stMHsGsNWlPPB0mAQOuuqE4fQNeON9FCPiH7O1f9MeY5O1beI2QbYN3WfxJNd77TXcW+hp6FMhxOJKcPoMPfyObGTyIej8Z9O2Mrpr7buIpKT72QfYBHd68Me3WWNO/Fr4rL5cfLO/Vi9+W29viUqO5cK/5sRXP6AFa0BAmoYotS/10WWzWyrgM8ATFV0lhOH4ARwd9YTh9A7Utiswbdp0V3+gDcGlqDuIphNKcPQNvchO5OK3umIo2dfl4ScPoANtd28Ob62gT3KIGIOn0AC8UWX3uDVQ2rhJw+gG9/kLrObNfy5cJOH0DNd+5IYG8SiyGRWPFKQUln3cK3euz0Aax55w1CBn7rND3juHH8CIafSOsBYxNs3R+HrHxQrCaYHorjAdG16I5nFELB2Pb1I2oI9sB+HA5ptHIPiSCgidnvCMU3UPpU8QmqN4pzF9RSs74LQLvBZyZRqILRCL44x49QCg+gsdBEf6J4nelgku9PNXXv/68y/pAaq4RkVDyCpSDSiNPuC1+nNx48IfGyOclGbWmJfVIUtI74yhKlSRxBv9hcWNM1dDX97ugtjhvHTx4fRg7WZkUZYSyfyjTz/Ogn5JciFVcI2bbkj8CUFT2kylo0DtkiJrFdMeabMc8pG3KpkG2AYQOiKYaCScmgrGimsH2AHFtkkRizbGVkQc/UzA7wnYHnxTxnZGY5wzKjl6yIxgV9wksUV2Tk4DQnX+2pn1VMOmxyQU5c511RLhaKCTA6O/rfX2KTsAsKsJw/MXYIpN0MWXYx+474BcvE7A+NfU7BfLFwOilD6ZZNjYYCUqmB+7Mgxn1X5ETKSs0QrK86fXIcTCyP7/k/nHynhTNGp3CJACPlC4bHmAccReb2m4ssWFrq59N+ntjOJBDXqcbSIUr/KB7NlEaMUXPmC+WHV4ydgDlFw3KPR46bHD8AdccetG270T1+pIIcTOOGI7mMz9LUukpCbz0CPg9UjIL6PeBzIw2ehHnGOUhW8WROLeCmdcUDdFV+iO5rB0lGsmYim2xklM8mZ/LNSAZy5Jqql7B9+a/QVB+yYiMUaNt/RKHv8CvpP+YmYdsANXWfsnbrQ7S170Kne3dMliyUFE5j6tjvY7flGbKv6zqPr/kuu1vXENT9aLqKgony7NFcPvqXZFnFdfM3duzhtnUP0KV+uXMpAXnmLM4uOYGv9Z1HhsnYy+iDhl2saatjn7eDep+bkVmFfHfIdMyK8TyYaHl+WUi8Of9MYdsNHg8XLFkX8fgoh40HZo4Ttg9w66e1rG0/cutqWKbC/dNLeiwpfzCbqkM8+Xn4rb+iLLjlJCtmRXzd65V/eaOG3JxzrbEE773PeAlEiLjLnimRP038vtRDOr57qyDcprdLwvatMiSrsTVB/3/Xoe9s/jISXKf74RpdiHXBMKQoIiDpHL+ekegcP19Q5a8Lt/HCqho6fEEUwGpWuoXINB2bScYX1FAUmXPGlpBpN6PIMpdN6UuJK8WFDe4dCZ3VPWvTdyZc+0Zy+pMgmj3NXPL6JdR7u1MTJCT0w/ZuM5QMAlqAoB5EkRTumnIXFw0TL1nUGwTq6tl5xhng7kEoq9lMn3/cT+asWcnrWAK4/6YPhNrd8mBq5vcdoLm6ivce+TstNTVk5uUhyQqt+6pRQyFsTifOnFz8Hjd+jwerw8Gw6bOZdtFlyAlQmP+qYHSMPK4cvzRp0qRJc2yTdvx6Rnp8TJMmTZqvDulyDklG3bEG9aPn0Dtbu4t0hQIgK8gT52OadaFh2XNdC1H31rfw163p3u0zOdCD+6WkkSg55wms+WKy/JoaZNMn36e1NpwAikLfEVfRf3TkIukx7Wshlq+/l517X0HXD9/+kBg/4hZGDBIvdN/kruKezy5GP6KSHLgsRZw3/HuMKBAPJf3bzpd5pnpR2GODMkr53chr6GMXU60EaPR1ceFnzxI8aHEl12wjoGucXTqMmwdOEa5X90l9Ld9fH32y988JMxieK1Zy4ddrtvB2Q1vUcz6aPwU5Rk22SPxlQzMvRRF4mZZv4XeTxaXGH1vsY3tD5EWts8fJTBtkFbLd2Rbggxei5yNMOFGm72Ax+y1rvLSEr9QBgGSBAbfahN89Wm0A/+P14AtzfUxgvigf03DxCsOBd7ejLYu8q6KcPhjzRHHV0DTJ5d+fVvKzVzf2ONfv8il9+c35Y5LSp4Tw2p2w8mGxtt9aBfmJKcOTDH639Hc8veXpIz43S2aC4erOAHbFzovnvEifzNR9FqvvuovOF17scTvnKafQ929/TUKPEsP7T2xky2diwnEnXjaY0bPFU1B6g251z5sIeA8a4yUJk6U7hSC0Pxewz8jRXPLT3x6NLn6lOW5y/JKB7ukk9MZD6G0NoAa7nT4ATUVb/g7almWGv6Nl2d+7nT4AXTvI6QPQqX3tGmHbNdueieD0AahUbXqM9sbVwva3Vf6PHXteDOP0Aeis3vR33J46Yft/XXZlWKcPoD1Qz9Prf4QnKJbY3hzoiOj0Aexw7+PnW54Ssn2Aa1a8fIjTB9AS9NEVCvDM3nW8WbtN2HYspw/g+lViiqe6rsd0+gAWfCB2/+/tCkZ1+gA+awrQ4RdL9l5bFYrq9AG8ukZDE4x2iOX0AaxaLC5eEs3pA9AD0L5WXHTI/1RDeKcPIATB55rQNbFro9V2RnX6ANS3tqMdy8o6xzHtniA/FXD6AJ5ZVsXKPa0J71PCEHX6AP6euhvQaxvWhnX6gIhOH4BX9XLN2+Lzi2QT2LtXyOkD6Hr3XToWLkxwjxKHqNMHsPg/22OfdJT578++f6jTB6DrhPz+L5w+gOqN61m38J1e7l2atOMXBb1+D4Qivzi1GuMPoG9fjAm8sHwftDXELhDa0RQ5jysWjc1rY5/TIm7fr0Z3DoKan+qOLUK2lzRtiHnOho5KjIRCtwSiK46ubRd3ipNJoz8+p8It6Nssro9PSe7zJjHF1tV74ntmGjpST1ky3vutY62BvnfGaKuCHqvkQ6SmmxviOk+vTivupSIb94krRAIs2x29lMdRw3D5nNR7VxzgnUrxiXOdgYXZZNP+zruG2nelsON3vNPRFN84ALD5kw+T2JM04Ug7flGQispBiRwNK5caD/2wlcQosG1A2MVVMC7mOZl5kQspxyI/N3ZYT36uuH2LHF0owCRbKcuMQwIxDNPzRsY8Z0RmP0OhvDnm6P0flSUeyphMCqzxKTraBS/NrKL4wgin5IsJRYzrF98zU5CZeq+/eO+3zNEG+u6M0VYBySWWaK8Mi09sSSrLErKfJrmMKDX2u0zuLxZannSijOPxkXrvigOcXH6ycNsCh7g4WrJxnTzfUHvnnDmJ6UiaHpOZF3+KzNBpqS3CczySum+zFEByZGI643rIygNZBsW8/4CMPP4k5OEnGP6O3Km3Yi0YdeAbkUyHToqLz/insO0+Q79GdtGUCEdlyoZeQXZhDMczCkMrLmJA37OIdBuNGXYjToe4hPatU/6FFMG205TH5aN+RYYlW8h2gdXFRSWR8wP7O4r4+TDx/ESARyafe4RyfpbJgk02cVGfkZxZKpa7CfDz4WNjnnP/OLH7U5IkTsyLPQF8+6RI91Z0yp1mziiN7tRNzjWTbRVzPsb1M1GRH92BOn20jCKoGjrnvNj9GjdL/NWaE6tCiQmyx4uXW7B+rQCsEf52BcwX5CEpYtdGLs1CnlQW/ZxTBiKb0wpuqUi2w8KPzxgu1PbCCWVMSlXHD2Dc18XbfvPTxPUjwYwvGs9FQ8Krc5qkyA6vVbHy+KmPJ6tbhrH074/zLDFlasfcuWSddlqCe5Q4Bk0S1w6YfqFY+bDe5JKf/z5MeQYJxWRCOaiUVenQ4Yw75Yze7VyatKpnmjRp0qRJHdKqnj0jPT6mSZMmzVeHtKpnL6HuWkdo7WJo2NO94zf2RMxTja9UqN4WOre9TqhzH2gqgdYdhLrqseRUkD/nV5gcxlZQNS1E7c6XqdnyJH5PI93FxyQUs5OKcbdSMuBsYdu6rrNn30K2V75El6cGs8mB1ZKLpvlxZVYwYtAVZDn7Geo/QE3HVp5adxfNvqr9n0gUOMq5euwfKMgoF7a7z9vMd9Y9yF5f4xdlxvLMWVxQOoNv9DdWPPYA7UEfd659hy0djYTQUZAotDm5acAkTi4eZMh2tDp+AEvmnyVsu83n46zFayIeL1DgxZPEd7x9IZWbP21gp/vI3BuLBP+dU0KuTfz1tLM+yCMfh8/rKc6Cb823Ce/4Abz+Ly9qEuv47bjfCxFSIXPnQu4kY/b9zzWgbfAdeSATrN/pg2wS37HU2n0Enl8PdV3dD5VVAV2HTBvmeQNQhqRueFmaboGXv76/jTVVbSiyxJ5mD7kZZs4eW0aLO8DYvi4+39XMhpoOSlw2SrPtzBlayInHwu/6+DmwZ1HP2gw6Gb7+v6R0J1Gsb1zPTz/5KZUdlQCMyBvBrD6zeHrT03QEOtD25yhKSFgVK+WZ5Vw35jpOq0jdXTGAUGcn2+fM7VkdP6DP00+ROXFiknqVGI7XOn7ezg42fPge+7ZvZd/WTYRCQfqNHIOroIi2uloc2Tlk5uayc+VyfF2dDJp8ArOvuNawQn6a+Env+MVBaOW7qIueO+Jzefg0zAuuFbarBT3UvHg5alf4BGtJsdLvqg+RJPFJ2JbPfkLj3shJ0hVjv02fYWIhMKs2/pXNO5+JeFyRrSyY85Qh56+qfRP3Lf9GxOM/n/0uDrOrx3YDapATl9wZ8fi8gnH8ZsTVPbZ7MH41xGkf/xu/Ft5D+ObAyVxRPk7Idiyn7wCizt+sdz+Pec4El4O/ThWTbz/1nSp8MfQSFp3WR2gwaHVr/OEtf9Rz7Gb46TliztMbT3q/EPiNhqjzt+MvXoisKQVAycUmMsrNQva9D9RCbZQvkMH+c7FnVveH8N/7cVQtDNM5wzGNLo54PL3j1zMSOT4GVY3Z93zIvrYwiwIx+M15o7l8qvGFvqTx9KWw/S2xtgPnwxUvJLY/CWJD4wYue/MyobY/mvIjLhsu1jbZ6JrGlhGxc/EjMXTVSmSHeFmaZCLq9B0gVZ2/UCDAE3feQltdbY/alQwZzuW/uidJvTr+MDpGpnP84kBdFf4h1bYuN2TXs/fjiE4fgK76ce94W9h+wNcS1ekDqI4gAx0LTVfZVhl9IFQ1Pzv3xuegRGLJ3v9GPb6o8kkhu89URVeS+siA2ukBPm+pjuj0ATyzx/h3JINVTW3xndcenzrn4ezpCsR0+gA+2Cdm/3/LY3tl3iB0+cUWveJx+gwRw+kDqH3ZgEphNKcPQAPdLajquaY2pgCi+skeIdtpks+SHU1CTh/Avz7dneDeJBhRpw9gZ+oqRD68XrxMxeMbUzfHz7NipaH21bffnpiOpImb3WtW9NjpA6jdttmQgnqanpF2/OJAMkVYWRcsXv2FXSV2gWfJnCFuXzYR6yeWZLFdAwkJRY4tMGGK42+MhjlGe5vJKWQ3w3x44vGhKAl4NKxydAELi5KaAhdOc3JfC5Y4QyydZrHQD2uct7SgfklKYEDsN84vELw4ljjuaQNhpGmSi80k/k6ypQV7jgp2k3jYt1kRG/97A8kefYyOhezKTkxH0sSNySI435OkdKhnL5IegeNAmRY+XE6ZKC6jDODoOwNLfmQFNdmWTUb/WBJ/kTFbsigbGj2Mo2Lst4RsS5LMqCHRw1xtlhwGlp8jZP8As/t/HekIbcxuTJKZmf0uFbJ7QelMLFEUzy4si6z4GS+Tc8vIieJg3jRgsrDteIZr0WFziCs+SfdL+ogpk5U4zORaor96ZGBqoViYzgWTYg8++Rlgt4gNNM7s2OcYccyUOOyXXSKu6ikNi3FnWEGyiw0Nyuji7py+KJhOMl4GJ01yOGFALqMFSm0ossS35hrLWU46028Tbzvlm4nrR4K5ZdwtKJKY033HhDsS3JvE4Rg9Ggwsjpb+/ncJ7E3qIPhT9wrlY8ZROqTnqsBDps5IQm/SRCKd4xcnWvM+1K0r0PbtQNJ1lMmnofQXjz8/gK4G8OxdguppQkMn1LaHQPNWrEXjyJn0TWTD9YegrX4VVVuepKtlC6rqRULHnjWAIZN/iDNHvKQAQHPbZiqr36GtYydWSzYOWyGBUAfZmYMY0O8MLGaxHbmDcQfaeGXrn9jU+BEhPYRFsjMsbzoXjbor5o5gNPxakF9tfoZPWzYR0kPYJCuDM8v4Wt+5TM8bYbjfACFN4x87l/Je3U78agiTLDPaVcR1AyYxODPPkO2vffQOe4Lh4w6H2DJ4bKaxPIBoeX439C/iiiHistK6rvPnjS28VuU5IjJwSIbEQ7PKkA2sAHb5QvzxrSD+/RGLEqDTvZE1YyAsGGdMHGXZh15qd4U/5sqDOecas7/vDS+eTWEOSFD6DRlHnrGd9ODyDkLvtx0hICONsGO71JhIhx7SCCzcjr6+DiQZChzgV5HyHJjnDkDOje7Qp3P8ekaix8eQqvHS6ho+39VMUZaNpbub6ZNj56JJfdnd5GFy/xxWVrayYk8rQ4udZFjNzByUT0W+eHRKr7HqSXi1h4udZ90PEw2UgugFWrwt/HHFH/l036fo6Jze/3Tml8/n3hX3UtVZhTvoBr17h68oo4iReSO5dvS1DM4ZfLS7HhVdVdn19a8TWL0m/kYuF4M//ABTiub3HeCfd3xAoIfZDK4iK1//RWo7SWooxK6Vy2itr2XXiqX4PG5Gzz0ZiyOD9vpaHK5sXEXF7Fz+OZ3NzQw/cS4jZs452t0+pjA6RqYdvzjRdQ06msGZ0x3iuf+/pQQ4ZroWwrP3E3QthK10InrIh+7vwpzTf3+4pjHcbTsBHV1TMdlyUf3tyGYHdmepYdvQfW3cnjo0LURV3SJysoaSmVFKprOvYdshLUBt50421C9iaP5U9rRvJN9RxuiixCQ3+9Ug7zWuotxWiC7pmCUFd8jPhJxByAZEdQ4Q1FQ2tDeg6xoOk4XyjGzsCQqvCakqcz58M+wxI4qeB9jU3MqNK7ce8fkgEzw+z3gNy65AiGd2deAOBNncodLHLmFRTHxrZA5Os/H7vrIxxKZalSIntPs0GtqgMBtOHGrFpBj/bV953HtkPpsMZ11lRTYYBq6FNPY+4yfURXfOXwCwQd5syBljzKmEbsfb92Zzd5ddZnSbhNShYp6SiexMwDvNG0Rr6oKgDhlm8ASRHBakHDtSjHDQtOPXM5I5PjZ0+rAqCmZFYn1NOxV5Dva2eplYnkN1q5eCTOuxFeIZ8MET50DtWlCsoEtgtoDNCV2NEOwAFFAyunebhi2A8/9xtHsdF9tbtrOqYRX9s/qzuHox4wvH49f8+EI+mj3NhAjR6mul1FnK9JLpDMkdckyE1wVqa6m/9094tm5FNpvRFQVLcTH+3bvRg0Fsw4ejtbaC1YrJZiX7vPPImjv3aHc7JgF/kH/e9nGP2tz8wNxj4jfraG5k+9JP6TdqLAX9+uPr6kINBelsasSZm4diNrNv+zaCAR+FfcvJzC/AbDUW2ns0UTsDSIqE7Oid0Om049cLaE01hF65H72tAWwZ3XFcnnZwZGE+43rkfmIFbwE8VZ/Q8O53wx6TzA4K59+DvVRMljjob2f1u1fg99SHPZ6RPYQx8x7AZGBXrrV9O4uXf58uT80Rx1yZAzhl5sNYzJlCtjc2LubJdT9E048UspCQ+OHM18i2ie9OPFezmD/teDHsMZOk8PiEOxjsjF6MOhqLGyv50fqFaHz5jClI3Dl0JmeXDRO2C3DHsk9Y1tES9ZxZuQX8doKYgxaPqud/p42hNFNsVfX365p4s8Yb8fjMAhu/niT22/qDGne/6icU5dV20WQzE8rFHJwtq71sXRX9nMJ+MO1kMQet/n0vnTHsl99kwZwpNuH2L+1Ae6Mt8gkDLNivjqy6GYvge9tRl1aHPyiDacEwTONKIrZPO349Ixnjoz+kcvuza3hrQx2yBNphz9KBHfQsm4nfnD+aM8ckZhExqbx2B6x8VKztRU/CSPHSR8nm9BdOp7orwjMXAZfFxVMLnqK/q39yOpUAdl1wIf6NG3veUJYZtn4dUorm0T/1s09prxcTUcoqsnJFCu/6/een32Pf1i/DVcw2G2owiBal/pGkKJx6462MnH1Sb3QxYeiqRst/t+Jd3wSShHN6KdlnDkj696ZVPXuB0IfPdjt9AD53t9MH4Okg+O4ThtSIGj74ccRjetBD0+JfCtvfteYvEZ0+AHfbNmq2/kfI9gFWbLg3rNMH0N65i43b/y1kN6QFeX7T3WGdPgAdnUdWieUnHuAvO16K/P26yvc3PiZsW9N1frXpo0OcPgAVnXu2LaEjGL3cQCxiOX0AH7c0Ctlu8cXXt0s+E1Ml7QioUZ0+gCWNPjqDcUh/huG/y4JRnT6A55fHIZ0ZgVhOH0DDXmHzMZ0+gJpnxaVFozp9ALsCaM1i10eraovs9AFoEHprK7pX/PqnST7Pr6jmrQ3ditOHO33AF2+1Dl+IH764Hm9ATAW2VxF1+gCevyJx/Ugw7+x+p8dOH0B7oJ3fLvttEnqUGDzr1ok5fQCaRs2P7kpshxKIqNMH0FFvbO6QTHavWXGI0wcQ9PmiOn3QHdL73j/vx+fuSmb3Eo5ndQPedU3dL0RNp2tJDf5dbUe7WzFJO35xoDfvi3ywvQlCYpMYXdchFH0CrLrr0VWxB93dtiP2Oe2xz4lGe2d0Ce/W9m1Cdt3BNjzB9ui2fZGd2lgEtdARTtnhNPmjf3803KEAbjX85FzVdWp9ncK2k82qlo6k2q/1xjdJrPeKlSyo74jPYVTDzWiPEdQk3z7aXrF3jtYYR9KKqqMLlgxI0zvsaIh/AtbpC1Hfkf49jxZLapYIt93ZtjOBPUksnmXLDLZfmqCepImXms3hEtPjQw0G6GhsSGBvkk+w4cjxLtxnqUba8YsDecDYiMekfsORzGIKe5IkYcqKXvDWWjwB2SQW+1zQL7bqaH7ZHCHbBygrih5yUF42X8iuy1pAaebQqOcMzxcPdzDLJhwxhGEmZIur1GWarZQ7wheWzzHbGJiRK2w72cwvjS/EUlTKYWCmmXiyFCoyxeLlJ5THDu+xmruVCI9V7P0N9D2O6Cd5pFgIrzIgN3YpCKcFqegYEAL5CnPS8MK4zx1U6KQ8L7WFNAxjoGRCsrlu9HXCbU/ql7qhddnnn2+ofcHt30lQT9LEy8h54kr3mfkF5PcrT2Bvko992GHzOEXCNjjn6HSmB6Qdvzgwzb0EZcJ8pLxS5KGTkUbO6P7vEdMwLxB/6QIUn/kwivOgfBfJDCYHksmOvc90Cuf9Sth2n2FXUDzwfGTFBsggKUiyBUkyY7JkUT7qBgr7n26o/5NG/x9DKi7CbMo+5HNFtjJy8DcY2E9cZOSqsX+gvyu8011gL+frY34tbBvgyYl34lSOHNAlJEY6+/Hbkd8wZP9v489gcEbuF06ODAxx5vH3CWdiMij+8cwJc2Ke8+asU4Ttz3DFzvt8+xSx/EGTLPG3KQVRXz73TMpDEUxiP2mEhSFFkY8rEtx+srgq5plXxl7omXe++O/b9/roDq+cAaXniyfCW75fSjTPW7kwFzlGuY1ISNk2zJeOgaww11cCyrKwfG0cksH7P01ymTW4gHsuHMPYPi5Gl2VSmGlFkboXSyyKTInLxqCCDBaMLubRqyYdE4IT3CyaBynB9/cktCuJpNxVzjUjr0GKazntS07vfzp3TErdcg6m3FyKfvoTobbWUaPIOSd1czLPvX2McNtLfiym+dAb5BSVMP/6Ww55vw+eMp0+I0ZhcTiQFQWL3XFIvT9Jkuk7ciwX/PCXyDFqH6ca1gHZ5F4yFHPfTCwVWeRfNRJTXuouEh0gLe6SJk2aNGlShrS4S89Ij49p0qRJ89XB6BhpXLc7hdBUFfXVD9Cq6pCyMzGdcxKyS0xR8gjbzftQl78NAR+SMwe9rQEptxhlygIkh/h3qL52Ghf/El/156BrIEkgW3D0nUHejO+h2MKHC8bLvm3Ps3P1vXBYPps1o4zBk39ETpGx+VVd4wpWbvgTHV1VaHoQkDApNkqLpjNx5K047FG2XuKgy9/Kv9feyd6OTWh8mRtmUzK4efIjFDvFFZTWt+3m1vUP4tWOzGcqtLh4bMId5FuNXf+F9Tt5s3YblZ42vKEg/TKy+cnw2fSJEAYaL75QiPmL3op6jpGSDksbmvm/NdujnvOx4I4fwD+3tPDUbnfYY2bgubkl5NrEX0+bawL8+7PIuYS3zTdRnC0uvfzKo9Fzc0//moLFJhYCrgV1dv/Thx7+8oAFBt0mvqqot4fwPVYHreFzIZVzc7BMEH+n6SGN4Msb0bY2Hf7aAQUs35uNnIByGmmSgy+ocuOTK/l8VzOqpmM3yzitJho6/ag62C0KN8wawPqaNpbtbkWRJWYPzefOU4bRN0aNxqOKpsEfh4BHQPTq5+L53r3B27vf5mef/gxPKL78IgWFUfmj+PPcP1PgMFa3M5kEGxrYcfIp4O9ZznHuDddTdEfq7mYGAyEevnWxUNtUL+lQv2sHHz31GC01VQD4vR5CgW69A0mSu0uj6TqKycSgydM48WvfIKsg/tDyNMY5rnb8As+8jl5V++UHNivW2640/P26z03g0R91K3oehlQyAMvlPxK2XfPy1QSbt4Q9ZskfQek54sqS7Y1rWPfBjVHOkJi44DkcmdHzDCPR2r6NNz+6kiNnd904HWWcddLzyJL49v1vPj6bNn94ERcJhd+e9LGQfa/qZ96SH6BHEXixyRYWzfpDj20f4P36nfxk4wdHfJ6hmHlz1hWYDYQ1zFz4WlzniTp/8ZRzGOV08MD0noesVHUG+fqSuqjnKMAHp4vVgVQ1nR+/GFts4rcXijlPsZy+A5xzrZj9yn96CbVFP8ecB+XX9Ny+run4flcNvujvfev/lSJniTnegRc3oG2KMrk2Sdh+MCfi4fSOX89I9I7f2fctYV1Nzx2dUpeNj743F3OqOvX/mAUNYkrEyDb4qbiYWDJZXL2YW96/Rahtgb2ADy4+coxKFTaPHgNBMfG88uf+i2OMeEhlMrn/JmPX/JYHE1PHONF0Njfx2O03fOHoxUNWQRHX/OUhFNNxtQ+VVNLlHA5CrznsxezzozW1GrarVW4M6/QB6LW7viz10ENCXfURnT6AQNMmQl3ig03VpidinKHTuOddYft79n1AJKcPoMtTQ0vbZmH7bb76iE4fgI7K9ublQrY/ad4Y1ekD8GkB9oqsDu/n3frwimluNcjatuiOz9FkWWN8z8yGLjH1qns2NMU8RwVCgqqby3fHpwZa05p6EvS6rsd0+gCCzYL2awIxnT6A4EfiOxzalhi/b6xaG2mOGrquCzl9APvafayoND7eJg1Rpw9AS13V0jd3vSncttHbSIsvdmmgo0Gwvl7Y6QOo+/kvEtibNPGwY8XnPXL6ADoa66ndFnkenCbxHFeOH+YwKwZO46EnkjM78kGTGexiBdBlayZE262Szd3nCGLPiq2QZM2IXEg5Fg57rO15CbuBAut2UyZRVSiAPLtY4eBSe15c52WbxdUHC62R2xZEOXa0Kc9IbrjWEFd8wiqKYDRLSVZ8DV321AuXSXoIT5xF36VisTBVAAyE6KY5ukiShM0kPi0odomLDiWfY0s4Il4KM4yFyWWaE5MOk2iUTGP9sgwZnKCepImXzNz8njeSJJy58c3H0iSG48rxU046NOdIHjUY2Sau3veFnT5DkEdMO+iD/ZdNklFmno9kFZsoy2YHOVNvj3g8d8q3kc3ik/DyUdchyZEncA7XQArjKPkQiQF9FpCdFfnlOmrwN8gwkONnNTk4sd/lEY9XZI8jP0MsTHVEZjkDHMVRzzkpfxxZBq7/18vHUmbPOuLzk4sGUp6RLWwXIFuJPbkuUcRy2Ioc1riSf/89dZSQ/W+NiF3KYmquWdgJKi8wYY3xB7hs4LSJvf7yy2KfYzbw2smdGXuCWnCW2LWRs03I42MsOpjAPElsMQvAfOaw6CeMif7cpTm6fO+0GL8f3cq8h3PDiQOoyE/dBS3Oe0C87YRrEtePBHPliCvJtYmVB7p06KWYBceJZCM7HGTMmSPcvuxX4oroycbhEl8cK6hI3WdswMTJ9B/XM9XRyWedT3ax+AZEmp5zXOX4AWgeL9rGHcjlpciFiV1F0Jr3QcAH+X2gvhLJVYCUabxmR8jdSMfmF9H8HciOAhSzlYyK+ZgyjCdd67pOzdb/UrvzBXTAZHbiKhhHXukMsg0KuxygoWkNLW2bcfuakJBwZfanqGACTofYbtzhNHqqWF37Dq3efdR2bkdRLJw1+Db65xiP3/+sZTNP7HkPp2yjNeQm15SBSTFxbflpDMo03v+QprGxowEJ2NbZxPjsUgZmJqaG37KGfdyxbmXYY09OmEaFyOrbwTa27+Hh3bVhjxkRdjnAveuaeHefl5AOIbrX43PM8JtJBQzNNr5zsHSnj3c26PiDYDN3ayfpEpw/UWZ0X2MLQl1tPt5/Ify7c+I86FNhTNI51KVR+YwfDo+6c0D/G82YDOZDhBoDBN9pBa8KWQrs9IMO0olZ2GZlG7INoPtCBD+pRPeH0B1mWF4Diox89XgsudEnLukcv56RDFXP+g4vzy2vwqwoFGdZKXbZ2bCvjeWVrZwxuoSTRxTT5gnw5vpacjMsTCjPoTwvdSekX+BthwdmQEdVfOdLVrh9NbjiWO05iqiayuKqxTy1+Sk8IQ/eoBeX1YVJNrGrfRcmycSIvBF0BDooc5ZR5izjlIpTGJg98Gh3PSae9evZ+61vo9cflPZRWopisaDW14PPB4oCoRDIMjlXXUXx97939DocJ7s21vPWfRt71OaSH08gv092cjqUQBoqd9FYuQtnbj6dLU00VVVitTuQTGbUoJ/m6mr6jRxD/7ETyC5KLwT2lHSO3360mnq0vbVIdhumyaMT6vSpu9YReO/fqA170bra0NZ8iNZU0x3mmQA8VZ8SbNuNKbscLdBB55ZXqV/4fbw14Sf1PUHXAqghD3ZnHyrG3EJm7gjUoBtJSkw4ViDopqltA6oeoKV9K62dO1D1ABn2xDzMITXI5saPqe/aRUANUJY1jOl9L8RqYCfuYPrZCyix5tIQaCNDseDWfGSaHTjNxh0PXdd5oWojD+1czrN717G5s5GWYHzCIPHwyp7ItaWkOHYEY/HxvsiJZD4DuRcHKHWYUPc7fdCd19cVgiUNxq9RUFVZUakTUsFqgqAKGjCoEIpcxp/b+prIC2beSGqcPaB9RxinD7DkgJKIWkceDYI61IVgk7/74phA8iUm71Fv8SC5bGBWkJq9MCgXqSIbJUH20yQXf1DHYTGxo6ETf0jlrQ37+HBLI0OLMgmqGv9cvIut9Z3MHFxAntOa4iGeB7FrEXRUx3++7gfp2JgmtfhbyDBnoGoqftXPjrYd6OhML52OTbGxumE11V3VrG1cS1AL0i9LLFqmt+n86CP0trZDP9y3D7WyErxe0PVupw9A03CvW8uxsKGx+eN9PW5Ttb0t8R1JAiazmfamBtoa6vB1dSIrJjLzC7Ha7XjbOxg7/3RMFjOf/u8Zmmv2Hu3ufuU45nf8dE0j+L930Hd3v8ylonzMl52BZDWQo3IQ/qfuhvrK8AdlGfMF30HuN1zItqaGqPrPGej+yMn0tr4zKD7lXiH73q5qVr51KboWfpKeVTCeMXP+jiSLOQlNrZt4d8l16PqRkzmTksH5p7yG2UCOXLuvgd99cgGqHj5ZeGrZuVww/IfC9p+p+pC/7Xol4vE7B13IBWUzhWz71RBnLXmaLvXIvo91FfGPCWcZyueKR9XzjKISfjhabFEoHlXPByYNZ1SuWFmKBe9W4Y7iA1hlePdUMVXPli6Ve96OnmA+f4TCSSPE3hFvPuUlGENd3GyDBV8T2/Xb/aAXtTP6OeU3WTDHma93OP7/NqJtjOJcm8D+U7FJoa7rBP+3obuUQwTk8SVYzogcTpje8esZid7x++fiXfz6zZ6JcpW6bDx30zT65KRwOYcHZkL9erG2J/8WZtyc2P4kiHZ/OwteXEBHoKNH7RQUFl68kHy7sciQZLJlwkR0j5iI2KDlyzAbzBNMFkZUPS0ZEtffOzeBvUksS559kqUv/bdHbaaccxGzLr8qST06/vjK7/hpO/d+4fQB6PVNqOu3JcS2WrMjstMHoGmEPnxW2H7HuieiOn0AvqpP0EI9q2FzgL0bH4vo9AF0NK6med8SIdsAy9f9IazTBxBS3aze/A9h2wCvbL03otMHsLTmZeq6witnxsNDu6Orod23M7JTGIu3areFdfoA1rbXs7K156t9PeWN+vBhmrFoC8S3m/fNFWKKrWuavVGdPgC/Bv/bLaYu+PBHsVXFPtwsvvMUy+kDCAqKAOq6HtPpA9j3otiOq+7Xojt9ACEIbhLbttQq26I6fQDaarH7Mk3y6fKH+OO7PVfY29fu4+HFu5LQowQi6vQBvCe+wJhsHlr3UI+dPgAVlb+v/nsSepQY3CtWCjt9ANXX35DA3qQOAXfqbtaEAgGWv/q/Hrdb/toLaFo6GqS3OOYdP9xhZlieBIXTdcaWOdY9cczSIhBvqQZdFXP8At7YsvlBA1LO/kBb1ONen1iZiwN0BmL3LZ5zIhHUo8v++/SgcMhInb8r6vGWQOJCPhNNe5yOnyi7u+Irt7ArzvMOxxuHmrSqg5aK0Q7ha6ofeZpHsO/++L5AbxS8BzzxSXkfC5EmX0W6fCH8guU2mrrExqk0xqhzi5cGMtI22QR2GVtICDakZt3F45lgwI+m9tyB0zUNLZR2/HqLY97xkwf3g4PDOhUZeXhiEpblQeMhRhikPHqWsH3XmK/HPEcyZ6BYj1SGjIeSgedGPS4rNvLKZgvZBhhUHt3+iEFXCtsGoip6AuTaSxmQPV7Y/tisiqjHT8gZJhyOeU5p5PBfq6QwLU8sjLEniGaClcdZAmVSllgo47n94lOMvGW4mHDSySNj/+V9ciTkZJdOEECKs4ZF7iyx8GwpywSO2K9983SxEF55YB44YuRQZlmTX7YijRDFLhvTB4qJT10woU+Ce5NoDNxzOdHHiqPJVSPEQ+S+MeobCexJYsm+8AJD7Yvv+nGCepImXuzOTAr69/xZyevTD5MlMelZaWJzzDt+UoYD89fPRh43DHnUEMyXn4VckBjVRMlkxnzlz7pVPM1WcGZ3a7nbM8FVgDLrAkwzzhG2b3b1o/CUPyPbC7rr+ZkdHDxdV5yl9L3sdWH7+X3nMXjST5EVByAjm50gW5FkC1kFExh38uNY4qxnF45RQ65m3PCbybCXIH9RNkLCbs1n1qTfUJA7Wtg2wOiiuVww/EdkmLORkJGQkTHhshYyo+8lfHPiQyiC+YkAfx97C3PyRiMfNiEwSTKnFU7knlHXCdsusWdy37gFOE1fvswUYHhmPk9MOZ9MI3r/wIezT4t5zkfzzxK2//iU6KUaFODPJ4wVsi1JEg+eUBjx5SMDd4/LJUOwntjMIRbGRpmDDiuCG+eKX/9zro3t8MZzTiQqbos+AGZNkHGNEheosd5WAsURnhsJTFfmI5nFJsmSzYTl6glIY4vBaTm0GKMMUmkmlm9OFbKdpnd46IpJXD+zghyHGYsikWVTMCsSEmA1yRRkWsjLsDC6NIsLJ5Zx9thSHr96MicNFy/d0yv8qBahKY/ihNvWJLo3CWNs4Vj+MucvFMcoT3QwZsnMr2f8mqklqfssSrJM3/88AwKLRNnXXkPWSfOS0KvEcM2fZgi3veXB1P27AC77xT0MnTYLR1Y2Dlc29swszHY7GTm52JyZmKxW8sr64nDlYLJY6DdqLF//7V+Odre/UiRd3EWSJAVYAdToun6mJEkVwLNAHrASuELXoyRykRy56jRp0qRJk3p8lcRd0uNjmjRp0qTpCUbHyMRo+kfnNmAzcCBe8ffAn3Vdf1aSpAeBawEDlVVBrawh9OZH0OUBSULKdWGadwJyReJCT9Td6wktfArc7eDIwnTS5SgDxyXMPoBn7xKalvwWzd+OObMPBSf9FouBEBNNC7Hho1tpb1gFHOrgS4qV4dN+Q56gaiVAW8duFi39Dm5v3ZH2JYVp435CRd/The3Xd+3ivmXXENCOzIezKRl8b/r/cFqN7e6ub9/NDzY+TnPw0OT4HLOTP42+geGZ4pLXz+xdxxOVq+kMdc/bZCDX4sCqKJxSNIhrKyYKhxtuam7mhtWfRj3npWnzKMgQU1V9fNseHquMLsJhpJbflYuq2eONvOg0q9DK3RMLhe0/t9TL6iilui6bojCmn1hoiaZpvPZ49HymSfOgTLCWX+fWAPWvRs53kOww4BabcLik1hXC/9d9EOFPsFyahzJCXI1X9wYJvLABvbIt7HHz18agVCS2xuoxTNLHR6MEVY0/vrOVtzZ054PVtnkIHpQqOmNgHn+7bDx5TmNRDEln0xvwXPT0gYj8pAlStNA5wL6ufVz2+mW0+OPPeTdLZv53zv8Y4BqQxJ4Zo/qnP6Xzued73E7KyWHYZ9HHx6PJ9pU1vPvPrUJtL/nJFPLL4kuXOBqseecNVr7xMt7OdnQdZJMJq91BZ3NjxPw/W2YWC771XSp6WPz9aKC6g7S/vgv/7nYs/TLJPmsgSuaxFaaa1FBPSZL6AGcAj+z/twTMAw7I/jwBnGvkO3Svj9Dzb0Onu7uei6ahN7USfOFd9M4EFNQC9I5mQi/dBx3NoIags4XQK/9Ab2tMiH2AkLuBhve+h+ZtBi1EsL2SurduQdfjVHsIw65Vf6K9YSWHO2XQLRiz6ZM70QSFYwDe/+xm3N7a8PZ1lU9X/5xAMLrISSQ0XeVvy74R1ukD8Klu7lt2jZDtA7hDPr697h9HOH0ArcEubll7P0FNTGDkvfqd/H3H0i+cPujW7WgKeKjxdvJ45Wqer94g2vWYTh/AeZ+JS0bHcvoATo6j5EM4trf5ojp9AB83+FnXIiaA0+pWozp9AP9ZJp5IHsvpA1ghfumjOn0AuhdqXhKUDQX8D9VFdPoAAs82o/vE3zvBN7ZEdPoAgk+vE7Z9PNEb42MieGDRTh5avIu9LR72thzq9AF8srOZ779gQDGztxB1+gD+ODRx/UgCV7x5RY+cPoCgHuTy1w1ckyTjr9wj5PQB6K2t1P3tbwnuUeIQdfoA/vurZQnsSWLZtWo57z/2AG31tfg9HgJeD77ODtob6qKKvvg6O3j5nl8JCcP0Nm0vbcezugG1zY93XRMtz4n/lkeLZOf4/QX4Hl9q1eUBbbr+hZxiNVBm5Au06jrQwkxSVBWtKjGy4VrVFjjcAdM1tL1icvbh8NWu5HBJP83bQrBdvLhlc83i6CfoGu0Nq4Vs67qOL46BZu++D4XsN3r2EtSiT25b/cZ+302de/FFKXfhUf1s7xIru7C0OXaR4HjOORpsbY/PWRd1Pe7d1BrXeY9tF1PMXbwtPmdd1VJPWVJX4+uTb7eBL2mP7dSpu8UdS21nHGrInWkFSHphfEwEH22LvcD50TZjCs5JRxVbwPsCb3Ni+pEE2v3tNHjFrr875KYpDvXvo0HLv/5lqH3rv55ITEfSxE3l2lXCbbVQiH3be15KprfxbWs75N/+7W3oKTiXiEbSHD9Jks4EGnRdXynY/gZJklZIkrSisTHywCPnRw71kxIl8pIfXoFRKkhcKKkld9CR9hUrJmf8CduH48g+0ubhZOSIrWRKkoSi2GKeV5QnprqZYytBinF7WhXxcDSA/o7oYgQyMn0dYsVtBzlj33sD4zjnaNA/Q1yYJB7O7RtfmMrcYrF+jC6L77WmyKmnLBmvqqdZTPC0G0vs75BLxMPapII4ft+M1A2b6w16a3xMBMOKYxfBHl4ipjzdaygGs1qk1L1fMy2Z2GWxd6WCQrY1O7EdShDOk+cbam+fMCFBPUkTL/n9+os3liQKjLTvJcwlh847TUUOpBScS0QjmTt+M4CzJUmqpDtZfR7wVyBbkqQDb+E+QE24xrquP6zr+iRd1ycVFBRE/BIpJwv5xMmHfqjIKHOmJEzdUy7qhzz9bJD2Xy5JRp56BnJJ4mLjLbmDyRpzFV9ITisW8k/8KbIptnMViaFTf4bJElmWvc+wq7DYxGeQJ4z7MV/+lEcyqPw8Mp1izrFFsXHxiJ9FPefqcfcK2T5AgdXFnYMviijy/f0hF5Fpiq+0weGcVzacuQVH5mceUBCdklvGleXjhGwDzM6Jnf92fqHYZoHVpFBmiz3ReetEMaf+tL6ZMYXVs81wTnnsCWc4BhSayYqRbjRCfD2F2efEfm3mGrDviGMtpuwy8ZwC8xXRFzPkaRnI2eITXfNZw8AW+b0gndAHST7mBaWN0ivjYyK44+QhTKnoHktNYSY4LruZ355vTMG5Vxgknm/OzZ8lrh8JRpZk/jzvz0gC5Srunnk3JgPK2Mkkc8YM5GLBF6kkUf7wQ4ntUAIprBBftB4yXTz3PdmMnH0SI2bN5YjSKXHko0+74DKsDmOL+b1BznmDMBV0L7QouTZyLxxylHvUc5Ku6gkgSdIc4P/2q5Y9D7xwUPL6Ol3X/xGtfTyqZXoo1J3TZzEjWSxI5sS/zPSgH93TheRwIhmU44+EFvIRcjdizixBStAL2dtZjaaHMFuy8HbVoOs6mTlDUAw4lQfQNI32zl047EX4A6243XXIskxu9gjMZjGn6WBULcSe9vX4Az48oXa6gq2UZA5hSF7ikoADWogaTyMt/i6sZjNWyUz/jCLMCbj+HUE/nmCApoCHMkcWGSYLXjWIy2z82gOcs/A1Dg9CcgJvGyjlcACfqnL5+8s5fD/hguJcbh9j/GVX2eHjLxtaKLPq1Pk1Suwmsm0Wzih3UeJIwLX3BPlwS4guH/j8YDJBXgYsGG9LSA2/FR95qdlx6GdWJ5x2ifEdU1VVqX83gLcZdH+3oIstB1wjZZz9jL97dF0nuMuLWuOFIGCSIFvBOjwT2ZIYp0xr9xHa147ksqGFNGh2Yx5TiqxEt/9VUvWE3hkfE0GLO0CmzUSHL4jbF6Sm1UtFvpMil7jQUK+jqfDUJdCyGwqGQWctBN3Q5wTY/hY4yiDYAthAdcOMW2HaDUe713GhaiqbmjfR5mtjn3sfA1wDCIaC7OzYyWDXYEKEkHSJXa276Ovqy6y+s1Bk0WqvvUewuZmaX/2KQGsbeiCAKS8X1edHbWoCCSSzBV3Xsffpg2SxkHPhBWRNnhzb8FFG0zQevGMRepxR9Rl5Elf/em5yO5Ug/J5ufQ01FMJkNoMkIcsKNVs2kplfQNDnw2y3YcvIxNvRQVZhIWZLiotDHYSu62hdQeQM81HZ7TsWVD0P5/vAs5Ik3Q2sBh5NiFVFQW9uQ29pR+5bgtbQDLqOPGwAki1BN5RiQq+vROtsQRk0HsklFgZ4MFrQi6fyA7SQD5O9gNY1j6IFOnEOPZ/sMV8zPKBqapD2pjW01n4O6FgcBZgUOyF/C3mls5AMvvjd3lp2Vb1Oc9tmfP423J46dFTyXMOZNfk3OOzGVqPbfPUs2fscmxo/RqM7Hy/DlMOk0gXMH3AdVsEdOYCgFuIvO17irboV+PQACgoqIUBiomswfx1zE7KBnYmuUIB/Va7m3bodeNUgBVYHxbZMKjJyuHbAxENq/Ikwc+Fr4b8XmLPwNRYZdP5Ofn952M9fqGuhLLOKiyqMFaF/r8bLmnaVL7JM20NAiOaAzu2j8rDGGfYYjpbOIPe8c2Rej0mC0twg48vNhp6tRS97aQ+T9uPvgtef9HLmFcacv+bFATwHaf/ogLcGvBs0ii8K4Owvfu/ouk7gk3a09zoO1WWySYQaNMwnZRsezNQdTQTf3AbuANjNSIUZyEVO9N2t6ANzjx1HofdJzvjYA3RdZ/H2Jt7fVM/uZjdDipzcOHsgL6ys4ZU11aiqjsUkgyRx1fRyLp4krnzc6zy2AKr3i1K1HbRq07w/t8hTf+j579wJWhBm3NI7/TPAno49PL7hcdY2rqXF14Ku6zgtToJqkJAeQtM0VLrFMxQUvj3+21wzxphAWrJRfT52nL4AOr4UYDu8tsmBV5h3fbfAkOeVV7B+tAhrUWrXlXzg5kU9Ot/drPPo9z7g2j+kdh0/gNrtW9m5ajktNVXk9+nH9Eu+jslioXzMeGq3b2HhIw/g7eogr6wPitnKqLnzGTRJXCW8t5Ek6ZhT8jyYXtnxM0o8K5rBNz9CW7/tyANZTixXn4dkN77DEnzpb2i79ivSmSyYL/4/Q+Geuhpg36vXEGzZEfa4tXg8JWeIK3nrus66D2+io3FN2OP5fU9i+PTfCNtvbFnPe5/cxJdaBIcjc878F3A6SoXsN3RVcu/nl6ETXozCac7lBzNfwhJHruHh6LrOmZ//jObAkYqeB7DLFj6c9Yce24bunb6LP/svHaHwIhYZipkXpl9GluDOcSSn72BkYLGg8zcrDsXO748o58w+JUL2b/28nrWtkcuT5VtlnptbiiLgIHgDOr98Nfoy6uQKmfMnil37d57z4otDd0a0iHvN/3x4d0d/L5dcaCKjQiwc0/dMA/qWyNdHKjBh+7bYMwsQ/KQS9cPI6jPKhFLMCyLHs37VdvyMkugdv1++tonHPjn095OkbtHscJwztpS/XiYW9t2r/LYf+NvF2s68E+b/OLH9SSCr61dz5dtX9rjdOQPO4e5ZdyehR8bRNY0tI0YKtx+6cgWyYDmjZHP/TQZkn81wy32p6/wt+vcjrHzj5UM+szoyuPGBJ9i+/DPe+nv4FJ0Tzr+EGZdc0Qs9PPYxOkYeF4kWepcnvNMH0NGFujG8Y9UTtMbqL50+gFAAddVCQzY9e5dEdPoA/HWrUf2RHZNYdDSti+j0ATRVvY+3M4bufRQ273w6itMHoLFxu7iy1ls77o/o9AF0BVvY0LBIyPb6jsqoTh+AVwuwtVNMeXNh/c6ITh+AWw3yRm1yZYBFBfmbvPEpLv5+0x7BbyCq0wfQ5NdY3Sym/PjYx7FjZ5bv1vAGxBa94nH6jBDL6QOoe01MpVD3alGdPgC9MYTWJq6CqH4S/b5QV+9Dd0f//dMcHTp8QZ78vPKIz6OtD7+6dh+dvsjqyCmBros7fQBL/pi4viSBP638k1C7V3e9muCeJI6Od9411H7Pt29NUE9SjBR+1AJeD6vffv2Iz/0eNxsWLeSTZ/8dse3KN15JZtfSHMRx4fiFLefQk+Oi32HUrh5HzRIDO7J6HPaN1AmMp60mWAcPQI3qVO63H881DGs7vnYhwf6rcVybUIrutqth6jImknijDFTB66PGeUun5tWPE9HOx3tNjbzaYn2HzjF+8Y9fdB16qkyu0/M2xx6p/QdqguO4nsp/l8ESHJpPvCRNGjG6x/bw95SmqmhR5sxG5qJpesZx4fhJWU7kYRFCLjPsKCNjlzWIhVzUD6nfsIM+UFDGG9tut/ebhSkrcp6UJW8Yii2yKmcsXAXjcOYMj3g8t2QGjqxyYftDB1wco+SCxMjBVwnbP3XQNzlCHeog7KZMRhXOEbI91jWArBj5gRbJxEhXfyH7JxcNwqFEDsWzySbOKknNosBFcYZF3zxQTLFVkiSGZEVPL3aZZSbmiYVnf2Nm7Nj7sX1kHHGUNQhHgnR5ImKNQ4y18HSx3FzJoSBVxAhxzVaQc8XTv5Up0XM/5VFFSM5jNz/ieMZlN3PxpCOf62hPyvzhhbjsqVvuAOiOVVUM5N1OTm2Bl2+N/5ZQu/l9jZVMSCZZpxtQYQXKHxRPk0kjhtWRwai5Jx/xudlqY9Tck5l24WUR246Zb+z3ThM/x02On65paFt2obe0I/UpRm9sAU1HGTkIyWlcXRJADwXRtixF72xFHjIROU88D+YAqr8T94630EI+ZKuL9nVPogc9ZAw6ldzJ3zIsvqKGvNTufJnWus9AB4s9D8WUQWbucAr6nYIcxTmJh7aOnWza+RQtbVvx+9vxB1rR0cjK6MfsKX8kK9NY4v++ju28svVP7G7/sjCoRbIzpmgeZw69DYdZ3DH2qQF+sfkpljRvJIiKjIS2f7VqsKOUhyfchl0RFwZqCXi5f8dSPmrYTUBTcZlsFNgz6J+RzS0Dp5JnNXZfxsrzW2JA3CWkacxduCzi8XNL8vnuaGMLKnevaeS92iNXZafkW/nF+HwcJvF1qcpGHw99dOS7TQJOHikze5jFkLLnW//xEvBEPi6a33eAfa948USIXi84TcE12oC4i6bjf7sF/XP3oQcUkMc4sJydF3c9wUgE1tSgvb8LfCGwKJBrRy5yolTkIg8vjCoek87x6xmJzvHTNJ23NtTx1oZa9rZ4GFzo5Ja5g3h2+V7eWFeLpumYFBlFlrhkUl9unD0Q+VipY/WXsdBW2bM2E6+Ds4yVDuoN1jas5a+r/sqWli10BbvQ0bHJNlRUQlrokN09CYlLh1zKj6b96Cj2ODZqezvbZp0IgZ6Fhvd9/nmco0clqVeJQSjPT4Zb/pG6+X3QPRffvuxTti/7lNbafeT26cecr1+Dw5UNwO41K3n/sQfwezxk5hVgdTgYOfskRs1J3UWIVMPoGHncOH7JRguFQAshWxK/3K+pAfRQACQJxZLRveWthZCUxKyK61oIVfXj62rAZMlEMVmQFSuKKTFqp8GQB13XkSUTqhogGPRgs7kwJaBchK7rtHrryLC48Ie8SJKEhITD4kKWjG9Y67pOna8Vh2yh2tuEQ7HiNDsoMLDTejidQS+6LmORZWRZxpJACe17Vy3j/ZZuJTqNbkXPKwr6cONY42ILuq7zhxXr2NLqxQyodMsA3zhuMBMK8wzbVzWN1c0efMEAWYqJpkAIT0jn1L4uzCbjgsNuf4h2dxCnTaHdo2KSZTLsMlkJ2p3YvcXLumV0x00EATMMHAWjxhkv5wDgawzgD6iEWrqjnhz5YC+1oCiJuX98tT6UTAW1XUW36sjImLPNyAYc7oPRVQ0kCc0TAIuCHtRQHLHVVNOOX89I1vjoC6rYzAqapuMJqNgt3fedpuuYFZmgqhEIqTgspmNLpXXfBtj8JlhdgASdNeDq2/2Q5faFgBsy8rv/t3wyZBooytmL+II+WrwtKIqC1WRF0zSsJiu+kA+TZKI90A46ZFgycFqcWGTLMfG7qapK14YNoOl0LV2KpaICU042/upqNLcHxZVFyO0GXUcKhcg/4wwsecbHp97gs7c3sGZRA1on3QO4Qvd4Yun+d1Zedxh1Vw0MnJbHaVeOPar9jRdd11FDITRVJeT3Ys90Ickyno52rA4Hsqygad2hn8dSGYfD0dXu0FYpRomiRJN2/HqBwCv3o+/oFp2X8sswff3HhnfKDtDw/g/xVH74xb9lSxYoJjRfG47yOeSf+GNkA/Xwti//HXW7Xgp7LKtgHKNO/AuKSWyi6vHW8/bia/H6D6/01o0rcyBnzHlaeHB5Z8fDvF8ZWc38lAE3MH/AtUK2Af65+y0e3ftOxON/HnUj0/Iih8rGYn17Pd9e/QYB7dB8wsk5Zfx69HxD5Rx+vW4FbzXURj3njkFDOb+/WL290979HHeMcz6YN0nYQbttaR1rWiJnqdslePs0sXIRIU3jZy/6o6apXTndzPBSsb5X7/Ky8sPo51SMhDEniD1X7ZsCNL4ROQfVlAf9rxF3LgMftKIuiqxQI421Y7tAvAyLrumE3t2OurImbLqHaf5ATCdEjgRIO349I9HjY1WLh9ueXc2qvW0UZlpo9QQJqjqKJGFSQNcl+uc72F7fhQ5k2Uz85dJxzBuW2vL57F0Gjx0ZhhYXd2yBLDEF42QTUAOc+8q5VPVQqC3HmsM9s+9hasnUJPXMOLuvvhrf50uF2g7fsjnBvUkcn7y4lTXv1gi1LR+bzZnfnJDgHiWO7cs+5f1HH8Dd1nrogYOkgSVZRt+f75ffrz8Lvv1/FPTr38s9NUbHh3v/n73zjo+juvr3MzPb1Va9Wpar3HvFYFNNMSX0TkJIIKQHQnpIT368CYRAQkgChNBCCb2DwQZs3HvvtiSr97Ztyu8P2ca2tunOrrQ2+7wfPm+8c+/Zq9kp99x7zvfQsbgKdIOU2UVknF/WbwspSVXPOKPtWHXE6QMwGg+iLXw6Jra79i86xukD0P3t6J5mMHS6939I24bQKkiRaK5eEtLpA2hvWE/FlseE7X+67lchnT6Ato49bNohZj+gecM6fQDv7f0nnf6WsG1C0RnwhHX6AO7a/EjUQiTHoxsGP9j4bi+nD2BVy0Ee3bdGyO5hIjl9APftFlMN7fAHIjp9AGd+KDbZ3NPuD+v0AXgM2NTkEbL/z0XhnT6AZ5aLS6NFcvoA9m0RNh/W6QNQm6BzjwnRpDBOH4CxwYNWIS6MoG+qRVsd3OkDUBfuwfCaE25IEj9+9spm1la0AlDf4Seg9fyQmmHgUw38ms7OQ04fQLtX5ZvPrKPbn+C/6WPzxfv+Y27sxhFjHlr/UJ+dPoAWXwt3fXQXAS0xZSK9+/cLO30A+667PoajiS2iTh/AgQ2tsRtIjPF2dfLWX+/t7fTBMaJfxlEiL40V+3nnoT/3x/Bihm9/G+3vHsDwaRgBnc6Pq/BuCVLYN0FJOn4R0Pdu6vWZURu6RlVf8FQui9jG1yi+atXRvD1im/bGjRHbhKKpNUQS0lHUNYbOEwtHoye6Mgr7WtcL2d8WxYtSRaNNjcYF6k1rwENbIHQ5gu3tjUJ2+4OFtfEd26f10Tl0T+8Vk1+vi6ICiqpHry6aiHRuE1OzNfzRKadpO004fjWR613otXGuiZFEmE0H+37fdfs19jWKPSv7DxP3e1foBc6B5tPqT4X7tvhaqOmKvIg4EHS8/bap/r4tJlbfkgjRVFWJ6ut7Gab6fXuOcQYTHX9VZ1SfJSpJxy8C8ujeYRBSWWyShlOGRl6BdBZOFbafkRc5HCCz8BRh+/nZkfPIBheLrbLmucqiaCUxInOGkP0J7iER2zgkK25rqpD9LJuLfHvo4rFTM80LA8WLi4rzomon+vA4qyi60OVvjsoUsj8kN/LI7BZOiPyWUGRMEQtTlWzR/WrKePHwcrkswu8mgVycLmw/SXyZNTSrz30yXVZG5KXFYTQxRDKRN5xZFrNhxJpzy84V7lvoKqQkTUydOd64r7zSVH/X3NNiNJIk0ZJXNgRHSt/nTCVjxiHJJ447Yh+S0Uvq2D4sdroQ8ebEOdMDhFI2FnnyWSArIElIg8dgnWfugXQYZ/E00sZey9E/gyV9ENasEciOTNLGXEX6+OuE7bvzpjB43NdCvPAkcgadQ8ko8XCI2ZN/jjs9dA5ZYe4pjBxyuZBtRbZw1Zi7CSUkLksWrhz9MxzW0M5VOOyylZ+VXxtSptyCwj8mf0fI9mH+POl83Mdp/1slmQUFI7mpbJIp298fOiZim0eniDn1FkVhuCty/uFH82cJ2S9yWVlQHN6xKHFIlKSJJX1/6VQ7zjBzPEWCr8wTz6+cd1lkh3GSiciwwuvDi7c4h4GzSFzgxXJZeMdMmZeOki9+fpRRuVjOGErQH0GWsH5hDJI1dgJHSWLLby4Zx/njCshwWhlblE6my4osQYpNIS/NRkG6g9OG5+CyKcgSlGa5ePRL07HFSBQobnxng2BHBW6PHJ0zUNw87mYm5/VdzGtYxjAeOOuBmIikxQNrTg4ZV1wh2NlK6YMPxnZAMWT+bZHf36GYc3WI0mUJgNXu4JK7fkbekOHHKNJLsox8WA9AkrC7UlAsVhSrjbKJUzj/G3cM0IjFsBWnknn5CCzZDhS3nYwLh+IYIbZQPRAkxV2SJEmSJEnCkBR36RvJ92OSJEmSfH4w+440r5l+kqO31BH435+hqwWch8KTPJ2QlonljGtQhk4wZV/ztVP/4U/wN25HUhzovnbQA2BNIXPqrWSMvcqU/YM7nqNm70vY7NnkDbmQ1toV+D312FOLKBz6BdJzxpuyr+sqHy77NnVNR4uVSKS6Sjht+u/JyhBTlTzMssr/8dqO+9H4LAHdLjtZMPI7zCq51JTt9a27+c6mf+DTj01ud0hWriqZyy1l52GXzam3rmup4ZWDW9ne0YhXU3HbHJyZN5QrS8bhspizHc86fl2qynlhxFuswIeCO34AHx3s4O6NrSGPPz4njyHp4jLPLV06f3nPhy9IKlx2Cnz3XAcWE7XHXn00fJ6i2Tp+lf/14AuR5lp0tRVXqblHt/+dFrRPj8uzc0hY5qRjOTXdVB0/Q9XwL9yNsb4WNB3sCgT0Hl3y/FRsN05GtidfPScC9R1efvnqFnbUdTB3RC4/PH8Un+xq4Nevb6GpK0Bemp3bTx/GlVMHJX4tP383/L6IPuf65U2Ar38SlyHFkt8u+y0v7HwBPYK0lYSEy+LiutHXcdvE27CbqFUbb7TOTnZOm97nfimXX07p734bhxHFBsMweOj2KFTCgvCNhxO7jh+At7OTtx+6j4pNG9ACfiRFobh8NAXDy9mzegVp2TmccvUNHFi/ls7mJkadOo9BY8zNRZNET3LHLwxGwI//gW8Q7kVhWXAryiixPDPDMKh8+nx0X2vINpkzvkXGeLFwzIqt/+bApodDN5AUJpzxNzJyxWu+vfHhdbR17gn1BVx05nOkpw4Wsr14/1O8tTt0uMYN4//AhHyxh2BHoJtzPg1fvHZe1njuGS9eLmJ5UyV3bngn6NUzLbOIByYvELYdyek7jKjzd9p7yyO2GeKw8cTcvstKBzSds6NQNfvofLFyDn7V4BevhBcncTvhhwvEnLM3n/SgRlFPWNT5O/iSB0+oW+oQpV+1Y3OLhWj532hCWxlaiEOZ5MJ2WY6QbQDv0+tgX2voBg4Fx/dDx8Imd/z6Rrzejz5VY9bvP6Cl+7OFsWG5Kexp6H3t3Dp3KD+5QLz0Tb/wSxM5OOUL4NpnYjeWGPPTT37Ka3tf63O/MwadwQNnPhCHEcWGbaPEr6mCv9xP5rni+Y/xRKh4+2Ek+MbfE9f5MwyDf9z+RbpamqPvJElc/qNfUjZJXNPi80SynEMc0bYtJ9LqoLbpY2H7/satYZ0+gPatLwjbr9n9UvgGhkbd3ugciGDouhrG6QMw2Fclrsz1aeXzYY+/uyeMUxuBh/e/GbHNR82baAuIK9W9Vr0j5NWzuqWag54o5CcHgM5AdLLs+7xReD9B+O2G6FRDX60QU37cVhNZ8bLVAz5VbNErGqfPDJGcPoCWZSbKOazrDn98YzeG4LkxPIHwTh+AV0Pv6LvyW5L+ZcmuxmOcPiCo0wfw35UV/TEkcVSTJQt2RH5fDCRv7xN7zy6qXESbT0w9Od4E6upM9a/9wQ9jNJIEI8H3amr37Oyb0wdgGGz68L34DChJL5KOXxiklMgrhFIY5cZIyLbIKmiyRVxdL5rC7BabuLqeFEVSuM0irvRmt4Q/t06LmOImQL49ciKuBQWbLB6SlhamQLsMuBRzoZ7xwhpnda3SlOjOaaFTTADEFeVpNRHNOOAo4o+dnjjdcFgk8TeDRY6ury0p7pLoZDijfz6lOxLzWXYE+eS+3myKmBiTVbZiNZnOEC8kp/jcB0BKMfOQTCKK3SU2L7Onis/nkvSNpOMXBnnoBHCFcVxkBWXmBcL2rRml2AvCh8plzRJXOxo6+Q6OVcU8dqZrc+RQNPJqYfuSJDO8NHSenc2aztBS8TyzS8rD/+1Xj/2lsO3rB52JEuHyv3XI+ThN5D9cVzqBjONUPT87NpFMm7k8sEiIuvR2JbrHwu3DioXs31IeWS5eAmbkir34h+UrpEb42SaWgEXQ8ysoi9xG8N0HQPaZkR3jrFnikzXLBeEXPSznuJEE87Ukq4IyJ3xot1SSnszxOwGYVpbFtMHHXiuXTirqlRsrAT84r7wfRyaALIOz72UqjnDhX2I3ljjwvWnfE+p3+8TbcVnNOVjxwpKeBo7g789oGPLi/2I4mhhjYuadVRDfeYNZsoqKKZsYOQXEetRv60xLZ9qFl8VzWEmOIpnjFwHDMFBXvIW+aw3SyOkQ8GFUbUcuG49l4jwkp/lVis59H9K5803sBZPw1qxFba/CUTAR99SvYU0Rz7UB8HbXc3DHM7jSB5M76Bxa6lYQ8LVhc2SSWTArql3BSNTUr2Llxv+HqnoxAKtiZ8SQyykfehWKydXEdl8jr277M1saP8JAJ82aSZl7MpeN/iGuKHZMw2EYBr/Y+gRLm7fi0wOo6DhlK3OzJ/LFwWcxNKXQlH2ALtXPsqZK9ne10BrwUuhIY1pWMeVp5n5XgEsXvkFDiLiPy3IKuWOSuTSp25asYWt38BCpf04tZ3S2Ofniaz6spCZIxN9Et5UHZheYsm0YBou2eflgK8dIHSgSXD9LYnSx+IQCoGKPh3WLgx8bORFGTzN3X3nrVaqeCsBxUavWIii9xmFKfAVAawrgf6ERagM9M/cUGXmkE8vsNJRc8VIOR+zXdqAu3ovR4YNh2Uh1nRidPiwzS7FMCP/bJnP8+kY834+GYfD+1jpW7GvmoomFTBqUSVt3gH9+vIctNW1MKc3k0sklDMpKTOehF2//CFb8vQ8dpJ5SDvkJnr8I7Gndw91L72Zny05ciou8lDwauhto8jUBYJftjHCPoC3QxqTcSdw89mZGZI0Y4FFH5sAPf0j3q33IX5RlRqxaiSXBd/xee2gVlRv7ls4w4+JBTL8g8X8zgN1rVrDpg3fpaGrEarcz9cJLyR00mI0L3yV7UClj5p5B7e6ddDY3MXjCFOyuE+QZkgAkVT0PoTU2Q1snckkBkt38xOUwkiRhnbUAZi3A8HSi11dgjJiM1FKP4emMieNnzSjDklaIPWc0jrzxdFd+gmvQHNNOH4DDlUfhsEtpqVvN/s2P4EodhDN9EBl5U5BNhDEejW6o5GSOx+fvIC11EO60wQwpOd+00weQbs/hyrE/wbUrnS0NH2ORHQzKGEPA8ALmHD9JkvjKkPPxqxq7u6uxyxacipWpGcMoceaaHjtAjbcTBYmpmUWUOjN4pnITHf7wwiPR8ofJs/jKuuD1pW4ZPsq0/Xl5WWzd3zvPwgKmnT6Auydm8dO1zbSrYJdAMcBph++MMV8IVZIk0h0yGU4dj79ngbVbgzQbFLnNX5f5xTKEUM8bMsZ8IIWS1vOf1g0E6PkDLGDNxrTTB2D4deRCG3qBAnUByLAgZVuQjNjEv8ppdphaBEsPQHUbyoJRWDKTL/YThcZOH6v3NbPmQDMzh/bs/KU7rKytaKbTq3Le+ALGFafT2h2gpduP22UlLdHDPQEmXQvrngK/BwiXJyuBxQVZQyB7eH+NzhSptlTOKj2L3536OzY3bOaJLU9Q7i6nprsGh8VBUWoRMjL+Dj8z8mcwLHPYQA85KuxlQwiflXwsaZdfnvBOH8C084dSubFvtSXHnlYap9HEFr+3m9baGmZecgXODDeVWzfh93iwuVKYd+OXj7QrGpn4CyonIyf8jp8RUPE/+yZU1/d8IEkoF8zFMs5cGYHj0dZ9iLroWTCOnezJI6Zgvfjrwnar37wdf+26oMcUVy7FV/4P2SIWbqjrKps/+i5t9at6HZMtTiae+U9SM8XPk66rvPjuBfgDwZLDJeZOv4dBhfOE7QN8Wvk/Xtnxx6DHTi29hotHioW4AHx/079Y0rwl6DEZiYcnfZsJGUOEbLcHvHxr3Zvs6gye5Jxjc/HSKddiEcynO2vh60SSx8iWFV49UywUORpVz0dnjGGkWyyg9MoPD1LvCy07PjRF4d9zi4RsBzSDX73iRQvzaJtYInHNLLFdv49e99BaH75Nei6ccbHYrl/16x66t4dvM/QOO3KUIbnH4/1nDUZVaLELebgD+015QrYB1KUHUBft7X1gVA6OKyJLdid3/PpGrHf8/r54D/e8E+ECPA67ReJPV07iooli92y/8OcJ0HZArO/5/wczb4vteGLI71b8jme3P9unPjIyb1/+NkWpifubmVH1HLF6FZYEzRszo+qZOziFq348M4ajiS2bFy/k3b/fH/L47Cuu45Qrr+u/AZ2EfO5VPfXNOz9z+gAMA+29pRiquOrd8RieTtTFz/dy+gD0XWvRm2uF7KpdjSGdPgCtu4HOHa8K2QZoqHgvqNMHoKsedq/5P2HbAJt3PR7C6QMwWLHh96bsA7y6496Qx5ZUPEt1x04hu3u6akI6fQA6Br/Z8bSQbYDnKjeHdPoAGv3dvFUjNnYgotMH0KRHVrcMxoHO6JRMb1m5Vch+k1cN6/QB7O3S6FLDtwnFB1sDYZ0+gA1VBn5B5cpITh9Ae4OQaYCITh9A5ZNiqph6gz+s0weg7/aiVYntShtt3uBOH8D2Rgy/2DWZpH+obfPyp3d39LmfTzW4+9XNBDSxe7ZfEHX6AN7+QezGEWO8qrfPTh+Ajs5Pl/w0DiOKDfV/MZdXuf8qcf2CRKbhgLjSeH/wwaPhQ6mXv/gsvu7E/htOdk54x89oDRIjHVDBEzu5cKOrDfTQjqRRXylkV22P3C/Qsk/INoC3szr88a7wxyPR1h5igncIf6DTlH3d0DAiFKNt9oj9Dfu7IktFN5iQuT7oiRy7v7erRdh+PFnZGF957/2d0Umr13SJSbBXNEXnXHT5Ej/aIRSBVrF+el1059SoFVs4M9rCO4xGd5xrYSQxxcHWbjTBKKCW7gAd3tgtuMYULUHHFQOavE3Cfas6qmI4ktjS8ZF4qSyAQG1NjEaSpC+ogfDPeMPQ6exruYckMeWEd/zkkWW9PpPyc5DSYhfjLWUXQWZ+iAEoSCPFCqDb8ydwvNLm8aSWXyhkGyC7eG5Y+7ml84VtA5QPvSrs8ZzMcabsy5JChj10yJlNdjI8S2y3+5Ts0cgRzv28nAlCtgHOyIscInphUWzDkWPFlWXRhf5kSWL5YFOyowuxHJ4hFuJ89pjIuUYSkJly4j7+sk4VG7syOoo8OwmU8WL5eFJxOqSH+N0kkN2JrUj3eWdCiZsit1gI9MwhWWSlxC6/PqYoJvPZbYkZMghQnFqMU1Ck7dLhoVW5B5qSv/3VVP/sm2+O0UiS9IWsovBq3670DLKKSvppNEmCceLOfA4hF+ejXHo2uNPBYUcePhjrlefG9DskScJ2xR1IwyeDMxWsNpAt4M7FeuWdwiIpkqyQf+HDSEdKBkhwuDaebCXzlB9hzx0rPO7UzJGMnftnbM5jnSdJcVA44kqGTPymsG2AvOxJTBr1TXpfRhJ5WZM5c/YDpuwD3Dn7v6RZs3t9nusczNen/xOHYC0/p2Ln75O+hTXELXBq1lh+Wn6tkG2Aebll3D16HgX2VKySTJpiw3GolpRFkvn+iFMYntr774qWp6adFrHNR2eIlxq5tiRyjter54jlGUiSxL1Tw//tD80UFzYammdh9vDwTukd88UnqBd+KXLf824QrxtW9q3w9pUcyJom5hRLioTlizkQanipMrabcpHsYq8GSZGx3TAJRvT+fa23zRCymaT/sCoyz3xlFqeNyOHoqg02BbJSrGS6rLhsCik2BYssIUvgdlq4YWYpD10fWcJ9QLnlA7F+sgV+JBbV01+8cNEL5LvykSUZuxTds+GiIRfx9cni+gTxxl5YSMoF5wv1tY4qJ+9b34rxiGLHVT+bKtz3lvsiv/sHkut/fx85pWVIsoxiteFMy0CSZSRZJm/IMK793X1IgovGSWLDCS/ukiRJkiRJTh6S4i59I/l+TJIkSZLPD8lyDv2A3lSNtux1jK42lNGzUCbMjal9Q1dp2/AEnfs+RG3b35NPKFvJnvcL0oaebcp2e/NWNn74NQzt2JxHSbYxdNJ3KBpxhbBtTfOzdM3PqWlchaoem6wrS1bmzfgjRfmzhe3Xdx3gwZU349OOtS0hkWbL5orRP2VU7inC9te37eUnm/9Nsxo8H++fE77NhMyhwvbfrdnJb7Z9FDRLcYjLzX9mXC6s6lnZ2cm1yxeFbbP4jAuwKGI7T79ds5V3m9rDtvlk/iwh2wAv7mvnge2hcwm/PCyVL44ULxnx4mofq/eHzg/99tkWCgXLOui6zuv/Dp9DfO51FhxOMfu+ZpXKR0Pn4lnzYfBN4iGThmYQeLkJbbsH/Mct/ElgvT4Xy0hx+3p9J4GXtmA0HiXCLgGKhFSWie2K8UiWEz7Y5KTmf2sq+f2b22jpDmAAmS4rv/3CON7aXEtDh48pg9y8uv4gtR0+ZAmmDMrk4Runkp0qthPdLzTtgwcn9b2fPR1+nNg7fh8c+ICfLPkJ3Wp0hQ+skpU7p93J9WOuj/PIzNH4zDM0/Po3fe5nGTmSEa+JC+PFm5a6Tp75xUqhvrc+MBerLbGn7juWfcKSZ5+ktfYoDYZDu3x2p4uM/EKaq6swdI2s4kHMvf5myiaIpUz1F7pPpemZ7fj3tyOnWsm8YiSOIeZLTw0EyR2/CBgBP/5HfgTdn02CLRd8BWW0+KT3eFpW/522Df8JemzQjR+g2MTzFT95fnZQNdLDjDv9b2Tmiy0cfLTyLqpqwydgX33BYiwC+QearvKzRfPQjNBJ+RISd899hxSbu8/2a7zNXLHiN2ghCqAfZvm8+/tsG6DJ181FS8Orgo5MzebxGZcJ2T914etRtVty9kVC9qMp5zDYYeOpuX0P76r1qFy9OHLi/fvzi7EJlCxYtz/A86sjizn84Qox5+bVRz1RtbvkFjH7u/8Y2X7GbIncU8VysXwvNaGvD6+q5rirGCmt74sGhl/Fd/+nEEa9UxqSif36SaGPJ3f8+kSs3497Gjo5696P+txvSE4Ki75/eszGEXN+aWKSVjgJbuv7OekPqjurOfdFsfSWv531N+aWxHYhO1YYmsb2seI6AQUPPEDm/HNiOKLYYaacA8A3Hj4zRiOJPfs3ruPF3/28b50kiS/+8a/kDBocn0HFgPp/bMC/76jFcFmi6GczkV39X7/0c1/OId4Y1XuOcfoA9J1rYvod3fsXhzzWufM1YbuejqqwTh9A3V7xVbGahsgrVhU14XelQlHVvi2s0wdgYLCu9j0h+582b43o9AE0+sLveoXi44b9Edvs7hRXY4snz+2LTuntgFdMofHlA5EVTwGe2iOmLvrxrugU/LoilJQYCPQoS1i0rxFfsNN3RHYstd3RObe9bFe0hXX6AIyKViHbSfqH/yzdL9RvX2MXLV0nqWprzfqBHkFI3tj7hnDfN/e+GcORxJb2d94x1b/uZz+L0UiS9IXdK5f1vZNhsGf1itgPJob49x83F9QNvLtaB2QsZkk6fhGQMnI4XhlTcosXNw6GJT20wpEtT1xZ0uaMLJDhyhgubN9hy4rYJjNdTLnS7SyIql1R2ggh+yWO6MRDMqxi6oZlKZHDFB1y/68URcOsXPEQy2goz4hOWGVmjtiOVn56dI81hzXxEszlKEMgLeni3xHNTp6UKShYFY0i5ACskCaJnrHFYheXwyKT6kjsEDRhlMQNYR3hFnsHAgzNEE9liDf28eNN9jenKp5EDHd+dHO3Xv0KCmM8ktgiu3o/2yxRKpQnGknHLwKSOxfllIvhkCKjlFeKMv28mH5H5vRvoKT0vlms7qE488RVPRWLg6zieSGP21NKKB4pXuR09pS7kcM4L9nusWQKOpYZ9lxmFH0hbJsRWTMYmikWFz4js5zzcsMra5U6crAKKrZOziykyJEWts0vxoT+bSKRFsWtOyVFbAI3ODW60OJnTxF7MZ9ZmEKk9DqHAmOzxEIlL5tqJZL/NDJfQpHFHL9hUcwnMkysDbmimMeVXC+uSmq9LCt8dneJFaVM7IUm56Qgzx4UpoGE9cJRQraT9A9XTy9lTGHvZ8fIvFQsh+6ZjOPyVyXg7ovGYhUIze43BpsIabzl/diNI8acPuh0JuT2fYG4KKWI60cnbo6fo7QUnOIT67KHH47haGKL0y2u+jxxfvhyCQPNhHPOp2R035zukbNOZcQMcb2G/sB9xchjPCbHuGxsJeHneIlKMscvSozudgxPJ3J2dDXO+mxfVwm07MOQ7XTtfBXX0HNw5MZmgtTdcZCD25/EXTAbXfPS3XGAnKI5pGWLO5WH0XWVg3WfkuoqYv22v+MPdJKZPpwRQy4nM938amKHr5n39z5Cu7eRwrThZDoLkZApdY8lP6XMtP06bwtv1a5ic/t+XIqVPe3VdBLggXFfoyxNbOXqaLa01vFC1Rbm5gymU/Wzu6uZHLuL60onCgu7HKa6o52rVgTPO1l0xgVYBYVdDvPv7bt5rKKx1+c5Erx8jvkc1zX1Hv6yrYl2r4Ehga6DzQrfGp3J6UXm62atrwiwfJdKVQu4nZCZBn4VrpphITvV3K5TOIGX86+3YHOYs+/vUKl8KoDhAxxAJ6BA+mTIO918LTxDM9B2ecApo27rwqjzg0vGNjcTJd98LTaj04+2uxHDboEWD5S6kTt8yCNzkCI4B8kcv74Rr/fjpqpW9jV0Utvu4/zxBQzKSqGx00dLl58R+WlUNHXx6Z4mUh0W5o3MJc3kNd8vtNXAI2eDvwt8bYBx6D8ZeslwKTDsLLjxhX4fpgh7Wvbw1t63AKjvrqfN20a9t54sRxYW2cLc4rk0+5rpDHRyzuBzGJ9rbketv2j55BNqv3pr1O3Trr6Kkl/9Ko4jig2tTV08/dO+hTfe9uA8LFZz7/X+orn6IE2VFdTs3o67qJj0nFy6mlvILCyiYPhI9q1bjawoZBUVk5Fnfq7VHxgBHc/OZmwFKViyB64mbVLV8xCGYWBU1mJ0e5CHlCDZY1NItsfuDgxvJ3LZOPSqXRidLchl45AcYmGAx+Nv3Y+/cTuO/IlY0goxBp+G1lGFnlGCbLJwrKFrtDWsQVO91Ox+HkVx4UgtwttVQ0pmuXANwiP2DZ2a+uXUNqwkI20ouZlj8auddHVXx8Tx82vddPvb2NWykl0tK0mzZpKfNpS8lNgkAT9TsZjnanqcJwUJu2Ql1eqg2tdk2vEzDIO1bdVs6ahnbWsNo9Nz+FH5XDLtsXlg3B7C6QO4c9nHPHDqGabsPxnE6QNoNGBvSztDM8XjDQ3D4N2DHVR0G8dmWvrhP7vbmFeYYqrWj6Yb7KrTqWoFDWjy9PwnAWsPaJwz1twkdcu60Kqeaz5WmT3fnP2u3SpG56F/HBb4VKFjC7hn+LG5zD3f9N0e1NWdGA0+6DJ6ToxVIpDRiXx2JpLgbiiArumo66vRt9dDQAdFgjUH0fNSsBakImXG5rmZJL6MK86gy6+hKAqZKT2hjjmpdnIOKXeWZqeQnWpn8Y4GNh1sY/bQ7MSvz9XdAJ5m6KV+GSy3VoM978GOd6E8trWB40FAD/DJwU/Y1bILWZJx2920+9rZamxFQmLZwWUYkkGaLQ1PwENhaiE5UaSDDDS1d9zZp/Ydr72O+uMfY3EkdhjeGw+s7XOftx5Zz8W3i9cA7A80NcDWTxaze9VyHCkpONMyyMjJY/D4SQB0tbaw/MX/0nSwkoYD+0lxZ3L2LV8nuyRMpEiCIFllXGOD3zNaux/fnlYs+S5sMVi4jicnzY5f4OX30Xfu7/lHihPbDRcjuU0kwhyx+wD63o09/7BYQT00C3OkYr3mh8jZ5uKS27e9RPOnfwQMkBTseePw1W0AQHa4KVzwD6xuMSdH1wKsefsavF3BxTqcaUOYPP9xFIugOqC/nZfeuwBdDy49X5x/KqfPvFfINsDamrd5dssvQx4/s+xLnDf8dmH7Zy35EV2aN+TxC/Kmc7eJUJgvLH2ael9vee1/TrmYce58YbsQnaqnAnwUR1XPe8YP55RCsYnD2W9XErpgQQ8fnS/2IvCrBr9+zYsWRifF7YQfLhBzwBf+z0NXJN0ZGS65Wcx+xdMe/NXh2wy61YI9Q7BcxDP16NtDX/fYwfHDQUiWvk/iDU3H9+cl4A0t8GK5bAyWMaGv/+SOX9+I147f7U+t4e3NtUCPw/fS7adQmv2Z017V0s1lD31KfUfPIsg5Y/L5100J/LOtfBTeukOs77SvwIXi77J489imx/jz2j/3qY+ExBPnP8GkvEnxGVQM2DZqtHDfkWvXoLgSc5HJjKqnbIfb/5KYqp6+7m6e+ME3aW+o73VsxMw5TDn/Ip7/9U8w9N4v53Nu+xYTzkz8BZZgeHe30vj4FjgkzpZ+zmDSzyqN2/clVT0BvabhM6cPoMuDtnqzebsHd33m9MFnTh+AtxNt9bum7BuGTuuah+HwnoehHXH6AHRvK22bnxG231z9SUinD8DTsY/GyoXC9rfteTqk0wdwsG4JHV0Hhe2/teuvYY9/dOBpRBculjRuCev0AbxVvwo9gipqKFY3Hwzq9AHcu2upkM2+El5bMTS72qJT3fzhpt1C9j+q6Yro9AH8c3uLkP1V+wJhnT6AVg90hHFOwhHR6YPgGwhREsnpAzj4dHTKpcejNwXCO30APtA2hy/3EAptRWVYpw9AXbhHyHaS/mNjVesRpw+gsdPHY0v3HdPm8aX7jzh9AO9vrWNthdg92y+8fZd439WPxG4cMcYwDB7a8FDf+2Hwx1V/jMOIYkPTSy+Z6r//usTNXzSDHr6E7ICy7ZNFQZ0+gF0rlvLh4/8I6vQBfPTkY/EcWlxpX3jgiNMH0L6oEt0n9o7uD04Kxw9fbwlpI8hnfcXwRZA0j3Q84hfo6IHwNnR/Z9jj4Qj4I0/g1YC4fZ+vNfIYVHH7Xi385FM3VAzBGXZTILoyDbqgY9kaCD257lQTW/K80RffN0t9lA7Xwe5o3MPedEY5fJ+Y+YTAEL2EfNFdz0aX2H1lRPObBUSXJJL0F+2e3pOWdm8g7L97+iXwTWWcnNedZmj4NLFndqeJ93+8Uffti9woDFpra2wGkiRqfN3h52y+rtDHtUACPzsiYBw/p9F0jEDilYs6zEnh+EmDCpGyjirOKkkoE8pN25VLR0NGbqhvRZlwmin7kmwhdeSFx36nI/PoBqSVXyxsP6fkdOQwMtSy4iRn0FnC9kcNuy7s8RRnEVkZ4r/DrJLwxc1HZM1AlsQSnS8smEmkQLYyRz4WWcz+3NwyLFLw2+uLg8WUSPuL2XnRhW/Oz3ML2b90cHRKWD+dkC1kf/awyCGQsgQ5AgXKgeOru8SeKNL3cs4Ve3RLhVakzMh/t2VydMqux6PMjhzeokyOj0BWktgxc2gWQ3M/uwYUWeLqaceGXl89fdARlU+AsmwXpwxL4Jyx0ZeI980RDzmMNxbZwvzB84X6fmnsl2I7mBiSf2ffcvuOp+Tvfd8FTWKOUXPmoViDv38zC4uY8YWrQvYdMzcxw1ejIWXmsXoQzjHZKKmx0RmJBydNjp/R7UFbuxWj24sydjhysbkcqiN2u9rQ1i/uEXcZPhmjZi9GZwvKqJnIJWI16o6xr6t07nwdX8M2HIVTcJTMonPbS2jdjaQMm4+jYJIp+57OKvas+RMdTVvRNA+ybMFid5OWNZay8bfhTDOXUNvQvJGPVv4Av78NWbZhs2UgSZCfPYVp47+PzSqe5KobOsurXuLNXQ8S0D/bQbPJTqYVXcTF5d8VdvwAKrvr+dKa++jSe+/OTU0fxl8mfR2LCfu13k6+t+4tDnh6YgOdsoVvD5/NJSWxUWuNlOe3RDC/D2BfWxc3rdgU8ni2ReKVM2cK29/T7uP2pfWEWqe+Z0o2s/LF8zMqm1X+tThAsEU3pxXuPM9Gil38t3310fA79ZfcIi7gYxgGe/7mhRBfkT5NIu8MceECw6Pjf6O5p5C7/7jnf5qM7aY8U8qeek0H/te3QWPXZ6KJADYZZc5grHPKwvZP5vj1jXjl+DV1+nhy+QGaOv18YXIxUwf3ru+5vrKVl9ZWkemycePswUeEXxKW/3wB9i3qWx/3YPjuxsjtBhBN17hvzX08ufVJjpPLCkq2I5s7p93JRcPE3xH9QfvqNRy84YY+98v+/vfJ+8otcRhRbDAMg4du7+N1eIhvPJzYDlLTwUo+fOxh6vbtQZIknGnpDJ44mVOuuA5nWjrbP/2IFa++SFtNDWrAh6xYmHz+Rcy7/uaBHropPFsa8e5owZLnInVmIZI1fvtqZt+RJ43jlyRJkiRJTnySjl/fSL4fkyRJkuTzQ7KcA6Bt2on66VpQdZRp47DM7Hsx01AYho625GW0zUtA0+BowQ5JRjnvZixjZgvbb13/OK1r/xU0/8DiHkLhhQ+j2DOC9IyO7o4KNi/+Hr7u3iIvFlsGU89/Dpuj90puNBiGzqLl36WmIXgtmhRnARef/ZLwrlxNxy7uX3FTyDy+sbmn88WJ9wjZBni7dhW/2vF0yOML8qfz81HiCeKNvm7+sP0jljX1Pvc5NhdPzbycdKvYzs1jOzbzWGX4HIhHps5hVGaWkP3fb9jJ23XNYdt8Ml+8lt/XP61lS1vomP7LBrn4zjixUE+An/zPE3bd+7bTrZTliD3+ag94WBFBE2nGOVBYKrbr177bT/3LofOR5FQY8jWHsHS+v8qD9s+G3gckkAfbsd2Qi2QTX63UD7bjf2odQbdbi9KwXTYW2T1wNZCShKe61cPV/1hGVYsHl13h918YzyWTi+n2q9z96hbe31rHkJwUfnXxWCYOcg/0cKOnYiU8do5Y3zu2Q7o5Be94oRs6N7x1A5saQ0doBCPFksLj5z3OqOzYRKDEg20TJoBfLPdr9PZtMR5N7KjY3sjr94vtIl//q5m488VC8fuD5uqDvPXgn6jfvyekkMvRSLJCbulgzvnqNykYbj6KLklkTvgcP72+CfWtj6C1Azq70BavQNtTGTv7m5agrXwbujuOdfoADB3t7ccwdLGkcX97VY+qZ4ikc7V1H40f/07I9mG2LvlJUKcPQPW3sfHD24Rtb9v9dEinD6DLU8vSNb8Qsm0YBg+uuCWseMuWhsVsqf9YyL5X84d1+gDerFtFcxQCOaH4f9s/Dur0ATT6u/n2ureEbUdy+gC+skZcPTSS0wdwThQlH4KxutEb1ukDeKmym4pOsRf+k0vDO30A/1gsnkgeyekDWPm+sPmwTh+A3gmNJsYf1OkDMEDf7yPwtrgyo6Hp+J8O4fQBVHcQeDVxJ2RJ4MZHV1DZ0nMPdfk07nh+Pd1+lfve28n/1lTR5gmwvrKVW59cjRpJPjeR+LcJqfj7xsRuHDHmj6v+2GenD6BL7eKr7381DiOKDS3vvSfs9AHsOEtcvyDeiDp9AE//om9F3/ubN/9yD3V7d0Xl9EFPren6/Xt59U+/RVMTVwnzZOKEd/yMypogn0Whhx4leuWOSCNAr9krZLt7b+QZpLd2nZBtADXQhad9V3j7neLlFiprQxcQP0xtw0oh2x3+JtSQGWCfsa5WrKTGnq7e100w3qwVf8iuaw3/Hfu6ElP6fEtrdM5uhKIAIXl+X3SKqh/WBC+HEYnttZHbAAS0xA9zD0XXbrHFJsMf+WWs7RH9ZcFo9kCE7zAq2zD0E/fcn+zsbzr2vtOMnly+5fuajvm8rt3H/iaxsh8DgmBpnh4S18FdVrNMuG+rrxWPalKdPE7U/urXpvrrB2M3D0wSHX5PN/X7xebDnS3NtNYmf7P+4IR3/KSC3qqbwT4Tt18WuU2eWIF116A5EdvYc8TDMCzWFOwpJWHbWJ3iKmwFOZFDjLPdYiulqbZMpCgikUfnRD6HwShzRSf+c3buFCH7AKPTwl+HhY7o1C37m/K06ERVRMUtF5REF6ZySq5YGGxplNGtViXe8pzxw1kiqOoZRQinXCIu0CFlOiBCZLdUkIokn7jn/mSnKOPY+06SYGxRBhNK3Md8numyUpKZmAWyg2Pmmkvc63VCjnhqS4o1BaclMcOuc281uRvpdsdkHEmix+Z0kVlULNTXkZZORl5B5IZJTHPCO35ycT7K6TPAbgOLgjJjAnL5kJjZVyadgTzuVJAVUHo7IsrcK5GtYgp4tuwRpI6+IuRx2ZFFztyfC9k+zJhTfodiTQ9uX7Ez4fS/CdseX/4VMtNDx2RbrWnMmyGWgydLCrdOeSBsm0FpY5hadIGQ/RSLg68PDq9oNi1jBIVOsRw5gB+NOo2RKcHz1FyKlfsnny9se3p65LzMH5eLTQgsisLYlMhO16KzZwjZn1eYQqEj/KPn1FwbI91iDsitp0ce+7WzxNOby6NYCxg7Xdg82WeFPzeSFfLOFVfdVK4NnTsp5VmwXSiW8wsgWRSsV08MPU92O7BenLjS+EngXzdNw+3qkWS3yBI/WzCaDKeVH5xbzhnluUgSDMpy8uC1U3BYxZVx+52rnhDve9snsRtHjPn57J9Tkhp+gTcYCgoPnBH+HTuQ5Hzxi6b6j14uvhMab067Zphw30u+FzsNi3iw4Ft3kZ6b16c+qVnZLPj2XVhsiVsC4WTipFH1NAwDDANJjo8va2hqj/Ona+i6DqofxSlequBodF3HULuRLE7Q/BhaAMliR7bEThpb1wL4fG1IBsgWG5IkY7XFZvyaFkDTA8iyBcPQUDUfimzDZo3NanC7p4WA6sNqteP1t6MoNjKcuVhk89pEhmHQ7G1HN3TsFiuqodPh91CamicsnnE8AV1D1XV8mopT6fmOFMHFguP549KPedfThpWejRYDuK6wlOvHToyJ/Ve27mJlTRMul4SsS/hVnS9PHE2pW1xw6DCqplHd5afFq9Ll96PIBgUpTgalOZFjcB93erzUtxvkpiu0dmloOmSkyGSmxOa+2rnRQ10d6Cq4nKABg4ZA8eDYrKB7GjzIThl/k04gABYFUgfZkS2xecb5W/1gA4tiQbJIGJqBbELU5Xg0v4oe0EDTkWwKitWCpES2n1T17BvxUvXs8qm4bEqv56Bf1bHF6BocEFoOQHMl6Dp01ILTDWmF0FXX878NA9rrIMUNqYWQJz5J70+8qpeAGkDVVTRdQzM0VEPFZXHRFeiixddCaUophmxgla2k2BNXIORoAoEA9c+/gE/TMNQAaksrlrQ0DAnw+ZAkqWf+l5KC1tjI4JtvxpGTwPUkj2LrigrWLN6N3QK+ANhsMq5UOx6PB58H0EG2gTvTybjZQxg85sTZEdPUQ/mZkoSvuxu703Vkju7t7sRis6Ec2kxRLJFr7yb5jGQ5B8Bo70TbshuMngo2kiShjB2OlB4jx+bANrR1HyDJCvLUc1CKh8fELoDu76Jz5xu0bXsRrasOJAuSYsOSkkvW7Dtwmqzjp6leqne9QP2B9/B2VKLrPiTZSnrOOIZO+h6pmSNM2a+s+YiquiXouh+HPZv6xrV0extITy1l6tjvkOUWD1XVdJW3dz/EqqrX8eif5YXJWBiXdzqXjvoBKTZxB6Q90MWXVv+Jav+xuXYWZE7NHsvvxt6MEqIIezS8X7uLe3d8itfQsEoyEjAls5i7x5yOKwYPunB1/KzAIhN1/HyBAGcvWhPy+HCHjX/PFQ+D9Wk6Nyyupv74OnKHeG5ePgUuced4S1WAZ1aoBEslK8iAb58trooJ8M5/Pb20no7GTB0/gIaPvbStNOilUmOFvPlW0seYW/TwvtaEsaGrJ3XpcLqgFRjlxHFBFlKK+E6O4VcJfLQffUc9qAak2LCcVoZlVHQh+EnHr2/Es5zD7vpO3txYQ06ajcIMB2sPtDKuOJ1zxxbEbGGsX/njyB4Hry8MPxdueD4+44khmxs38+ruV9nbupedLTtp97ejSAoYEKBnEi4hYWAgI3P7xNv52qSvDfCow9O+di0Hr+u7snbeL39J9jVXx2FEseNvX/uwz30UG3ztgcSu4wdg6Dpr3nyFVa+/hKHrpGbnovq9ZBaWkFVUgiTLSBjkDB5C+exTkeUTKHLgKHSvSvfaenSPimtSLpbs/gmb/tw7fkZbB/7HXwbvcUIgDju2my8z7fxpGxajLnzqmM8sC25FGSUW5nY0hq5S/eqXCDTvDtkm75w/4io9Tfg71r1/M53NW0MclZh09mOkZYvl4a3b+je27g4fPnP+3CfIcpcL2b932bXUdYVOFHZYUvn5aW9iVfqeC6bqGqd98v2wxW7z7W5enfXLPtsGeL9mD7/YFvzBnmqx8e5pN5maOEUq3g7gRuaNsxcI2T8tCsXOOVnp/L9pYtfOmW9XEkmeZOH8YqxR7BAdz556lUc+Dq8GZ7fAL78g9pB+7zkPns7I7USdv5rXPXRtD98m52wL7sliiweef9VCpT90Azs47ihBcvb93Bu6ge+h5dDaWyDGcu4ILNMjh6QlHb++ES/Hb0NlK1f+Yxl+tbewyVdOHcLPLkxcpcug/DoHdEGVyMFz4ebIz9yB4oOKD/jeou9FVbz9aG4acxN3Tb8rTqMyhx4IsGO8eFhjyRP/IW2G+XlaPBBx+g4jyfD1hxLb+Xvrr/ey7ZPoCtSPnXc25339u/EdUBwwNJ26B9ah1vWsAEs2mbxvTMLaD6U2zL4jT+B4jR60TTt7O30AXl/PMZOoq3qrRqqrxZQkj8dTvSqs0wfQsvZRYfsdTVvCOH0ABpXbHheyresqO/Y9F7Hdhu0PC9lv9lSHdfoAvGonm+oXC9l/r35txJdkna+V9oCYsuT9u0PnF3SqflY1i6upRkuroBLdjrboVD2XNkenznk8O9t8EZ0+gEd2tgnZf2Fl5MmdTxVX9YzG6TNDJKcPoPlTE7LX4Zw+AB9oW8Wue/1Aa1CnD0BdViFkM8nA8OTyA0GdPoAnlh/Ap4opyw4Iui7u9AEcECsb1F88tfWpPjt9AE9vDV/SaCDZd+11pvpX3ZbYu5mimBKn7Qe8XZ1RO30AWz/+EE+H2FxiIPHuaj3i9EGPYnbXiiglxQeYE97xI1wuUAzyhKRgW9AxyC0DkKIobC6Z+K6o7AsWV0eSouorC44/2qLviiRm3xplP1lwVy6SaKE1TrmoscAaZwU7S5Tn1C6ouhltdG7CBqpFMbC4R9kJXp5h1TpPxNDAzzGWML+lRZaQEvcO+tyhnKChcuGQTQp9SMrJd05OBCRJ7tOzXpKlnj4nGEHfdSeIUviJd7aPQ5lQDqlBRERSXSjjQytORm1/9oW9PrPMFFOSPB5H0TTseePDtsmcJl5gPTVrFBl54XaDZUrHfkXItiwpjB0eSXVLYvLobwjZdzvyKU0fF7ZNqjWLsXnzhOyfmTcRS4TLf7Azj1RBqeufjpob8liWzcnkzCIhu32hxCYmYjI0I7rw6IvyQ6tDhrWfbsMWxfPxSyPE8jevnxU5BDLdARbBh3S6uNBrdPYnRX4sZ58uviAkj4gQGp0ioYwRE2aSSjMgN3hfy7zYqS0niT9fmlNGqj34dXbr3KEnlsCLLIMZsbExl8RuLHHgy+O+jEVgEfSbk78Zh9HEhsFPPWmu/5MmVFwTGCXBhS/tLheT5kc/R544/wIcqbHR4+hP7MPd2Eo/K8kluyykziocwBFFzwmf4wdgeLzoO/ZhIIFk9ChXlg9BcorVATserb4CfcNHIMkok89Ezo7dj2tofrr2L6Jt2yuoLXuQrE4kxY4ltZDs2d/D5i4zZ19XqT/wLvUH3qezdQdaoAvZ4iSzYCZDJtyOI8Xc31LftI7q+uXoegCXI4+ahlV0dlfhTh/B5DFfJ9Ul7uDohs6SyudYWvECLd7PQiMdUirTSy7mvOG3CeX3HcanBfjG+r+xuXP/kc8kJFyyjYsLZ/Od4V8Qtg2wubWOX29dTEfAh8PS81I+LXcw3x4+G0sMdvzmLXw9ZMhkucXOo6fPN2U/XJ7fRXlZ/GCS+MKKZhh8c2k1Wzt6x63YgZfOLiLVhFR8VUuARz5S8QWJiBxbBDecYi4Je9m7Huqrgh+TZLj4ZnP2Wzf5aVyowXHjV1Ig/yIbrkHmVrP9S1rRlnSAbvR8hwE4JOQpKdjmupHs4tenoemoq6rQttRCwEBKt2OdOwS5JDpHPpnj1zfiKe5S2+bl3S215KbZKXY7WbW/mXHFGcwaKrboM+D84wyoWdu3PqfcAfN/EZ/xxJD9bft5Z/877Gvdx7bmbRzsPIhdsSMZEp1qJ7IkI0syft2PTbbx2zm/5fyh4iWF+gNffT175/Z9cbf4qSdJn5bYj5CHvvUhRh+jj9Nybdz0m1PjM6AYs33Zx3z63NPohk5WcSm+jjZyy4aSkVeAYrGiqwFySssYPGHyiSkUBRiqjmdzI7pHxTkuByWtf7zyz724C/QoCBltHUgOe8ycvePRO5rRO9uRFBnJmQaqHyk9GylIbT9RuqtWoKQWYHeLFYQPha6rVO74L1Z7Ninpg2hv2Eh28Txc6X2v/ROM2sa1+P0ddHfXkZZWSnPLdoaVXojLZV5SWdM11la/hSxZsco2PIEuJBmmFp2PEoOQ2yZfO/u6avFpfiq9TaRINlAkLiyYGZOHUbvfy46ORgwDOjU/xc40hqRmYYtRaE4wkRcF+MiEoudhuv0BLlq8huMzwq4oyuQ748QEe46mM6CxqKqTLa3d7GhRKXdbcFksfLk8M+ROQ1/YVOVhxW5wWnpy+oZkQ4cKZ4+14rKZt//p+x4ajk9bk+ESk07fYToP+GhZpWMvhEBXz6aFe4IFZ555RVhDM9AbAhgeDewSWo0fKVXBOtyFFINwFb07gFrRjOyyg8uCXtuFXJKGxR151yXp+PWNeDp+AHsbOgloOiPz0448E1u7/TR1+pEkyEqx4TahwNuv6Dqsfxb2fwrN+8GWAk17eko1peaA3Q2BDrA6exZDhsyBU789wIOOjqbuJl7Y/gLTi6ZjkS04LA6afc2kWlKp66ojoAZoDbQS0AKcPfhsitLiH3USCxreeYfGH/wQ/Me9iWS55/c8jCSBzUbmt75JwVfEIpn6E1VVeeyujwl4omufNcjKtT8VF/rrbwJ+Hx2NDTjTMzB0HVd6Bt7ODrrb23Cmp9PR0EhKdjadzU3kDhqMnAzNjZrPveOnHzhI4KX3wX9IrnhICdbLzkGyxMYhM9QAgad+g9FU3fugYsVy/i0o5ebmKF0HPqZh4Q85rN0uWVMp+sJ/sKYXm7ILsGfdX6je+UzQYxabm1mXvBU8jzEKWtr38tbi6+itOd+Dy1nIpee8ImQb4NPK//HKjj+GPL5g+HeYVyaWAG4YBl9d9xc2d+wP2ebu8uu5oECsErdm6Hx/wzusCCHi8tPR81hQKL5jdvnit6lTwwt8nJ2Vyy+nzBKyf/7C5XRGSCJ/5/SppNjEnJCfrG5gaUNwERCA4akKj54mNjHx+FV+/Vr4pdRBmfD1s8QctPpqD8veDt+mZCRMPU3MvubX2feXIIJVh1Fg6DcdyNHEywZB3dpN4NnGkMetl2VhmSQeeuN7ZgPG3ubgB9Pt2L81O+yiStLx6xvxcvwaOrzM//MntHT3TLgdVpn/fe0UHlq8h7c21RzT9oLxhTx0vXh5l35h7ZPwmmBo4w2vwPAzYjqcWKEbOhe9fBEVHX0TTypwFfDeFe8l9G7LtlGjhfuO2rY1Yf+2Z367nJYqMQGtqeeWMuvS2JUUiwcrXnmepc89hXGUY+5yu+lubQ3aXlYUzvvGHYyeI5a683njc63qaeg6gdcXHXH6AIx9VWjro5DFixJ12WvBnT4ALYD6zmMY/tAT2GhoXHQ3RztPRqCThk//z5TNw4Ry+gBUfysVgqqeAB8u+wahnD6Abk8NFdXRqzsdTzinD+DN3X9B08XUDV+uXhrW6QP4zQ5xxbP36/aEdPoA/rDtI1r8US71BSGS0wewsLlByHa3qkV0+gAWLA5d5y8cFZ3+sE4fwO5OjXa/mGrgXxdGjp+pbEFYlTCS0wdQZUJQuPrZME4fgAZ170RQ5gyBoRoEXmwK2ybwcjNGsAKIUaAdaAnt9AG0+1CX7BeynaR/uet/G484fQDegM7N/17Zy+kDeGtTDSv2hr+uBpzXviXe96lLYzeOGPPu/nf77PQB1HbX8uz2Z+MwothQ+X1zZSZ2nJG4JQ9EnT6ANe8mtjpyS201S/77xDFOHxDS6QPQNY33/vFAnEeW5DAntOOHzw9dvSfPRkOYiUcfMWr2hW+g+jHazb3wDK33JDjQuMOUTegJ8YxEa+1KYfs+X2S5/dqGVcL2o6E7ICb5v65tT8Q2ZvbC93SGvwZ1oLJbbOzxZn9ndC8lUTH3Dc0RHJtDbGkRc25ao/SnaxPz9OOP4vHlrRbT9DY6NQhEuLINwCtmXz/QGrlN5Ykn3f15ZFdd77oljZ2h78nl+xLc8TP1RE/cyKiNDRuF+y6tXhrDkcSWzg/Fa90BGLUnhrT+yUZTpZhjqvp8vZzFJPHhhHb8JKcDKa+3xJ48dFDMvkMZPTN8gxQ3UpY5gRTZ0ftvcJaa3/LuKaUQPtShaOQ1wvYz0odFbDNs8BeE7cuED9eVUEizi4kMXFgQOQTSLovnUs3KDn8NumQr5WnmcyDjwegoVT0LLWJhNPMKolPXm5Unlq87PD+6doOzEzOnIGV45POaPl5s7FKGAukRHvt2kFxi9pVxkU++MunEUD77vHPmqNxen40vSQ/Z/tJJ5lMT4ooipnIMgMWEImicObfsXOG+N465MYYjiS35v/6Vqf7OC2Kjvp6kbxSPGoMikGqV4s5ESuAyVycTJ/xZtl42H6kkHxQF7DbkeTNQymMnG66MPw154hm9awJKMlJeKdYrvmf6Yi269D9I9s9eqPaCKeTM/q4pm4cZf/pDIY9lFc0jd5B43sJ5pz2K0x7aeRleeinZbvE8tu/NeprQjqvEt2f8W9j2zKxybi6djxzCvoLMs9N/JGx/amYR3x4+M+gNlm118tcpC7CbEAa6c0Tk3IdnZogtHkiSxKVFkR3q58+MsCgSgnSbwvfHusO2+crwNOH8jJtPdWKNcEsumCCe+3HRzZEnkGddJWyeggsdEGaeaS2A7DliYhqSJGG/OR8pK8S1ZwX7VwuEbAPIWS4s5wwLedtK4/OxjMkTtp+k/7j7orHMG5mLLPX8nGML03niyzP57RfGkmZXkOj5PM1h4bdfGEtpdsoAjzgCX19Gj/SVAN83H4ETLyblTeKGUTf0ud+lwy5lZqHYM7w/yLrwQjBRy6/svntjOJrYcsZN4vOiG34nlrffXzjT0rn8J78mPScXWVFQrFbScvIYNnUmNlcKkiwf826XJImMvAKu+sUfBnDUny/iJu4iSZID+JgedXYL8D/DMH4hSdIQ4FkgG1gD3GgYRtiYrnirliVJkiRJksTg8yLuEqt3ZPL9mCRJkiSfH8y+I2NXi6A3PuBMwzA6JUmyAkskSXobuAP4s2EYz0qS9DBwC/B3s19mtHeirdyI0e1FGTcipuGe8UTzNNG88kF8tRuwpBWRMeVWvNUrCbTswVkym9SRF5tSpmqoWMiuNfeg+Y/Nq5FkK8On/oiCob0L1PeFbm8jby26AV+g5chnNksGp0z5BcUFc0zZ3t6wjMc33Il+KJtMOrR/pmClLHMiF5V/h8JUcXWrta27+O7Gf+A3gudC/nnsV5mdM1bYPsCbNTt5bN8a2v0+/IaGjsGIlGz+OmUBLov4aqZfVTlzcXiVkSUmSjpsaWrla2tCiyQpwOL54iuPjZ4Aly8OnYPx0Kw8xmaKh2a9ssbDihDpuRkOuPN8O1ZFfKf+1UfDJxJecJMFq1UsVNgwDPbc5+1JBA1CyhiZwgXi58bo1PA934ixP0iuZb4F+w15yBnmXg3+d3ai72iEw+HA7T6QJZQZJVjPiBwi/jmhX9+RfeXNjTVHhFx213fS5VeZWOJGkiAn1c5X5w6l2B2b0iX9ghaAe8dAd33f+g07B278X3zGFCM21m/kD6v+wIG2AyiSQqu/NWx7BYULh13Ib+b8JmGVLwFqn3iSlt//vs/9rOPHM/yF5+MwotjQ3eXj33eK5Vd+/e9nJPRv1tXayqt/+g31+/di6DqSJOPMyCC3tIyulhaaqqvQ/D4kWcaRno6ERNGIUVzw7e9jtZkIxx4gDMOga1Utns1NBBq6MTQdx1A3mV8YjuyIp4slTr+Uc5AkyQUsAW4H3gQKDMNQJUmaDfzSMIywQeoR6/ipKv5/Pg8dXUc+s151PvKQ2NSpixeGYXDwxatR245OhpU4OpHcPe3ruCfeJGS/tW41mxZ/I2ybCWf+g4zcSUL2Af77xlx0PbhYx9lzHiY/e7KQXd3Q+NEHp4RtY5Xt/GDOi2TYe+eiRKLZ38EFy34esd3S0+5FESx3sbSxgrs2vhv0WK7NxaunXi9kF4LX7wuGqPMXrnj7YYY67fznNLHfd97blRHbvHV2MSmRYjaDsLXaz5OfhpeeSXfAjy8Um7RGcvoOc8ktYvZ3/8kTUUsi81SF7Nl9XzgwdAPvnw4SVrbVIeH4UQmSLDa58L+yFX1zXcjjytnDsM4qDXn887LjdzRm3pHx2PF7aW0Vdzy/IWybYreTD78/D7slMXNle3HvGOgIrbQclnk/gTN+GNvxxIi9rXu57LXL0Iy+y21dVX4VP58V+T04EBi6zvYx4guvOT/7Kbk39D0Etj/429fMCdd84+HEVSx96KvX42nvu3Ja7uAh3PR/D8ZhRPGlfVEF7e8e6PW5tSiF/G/Hp8RNQpdzkCRJkSRpPVAPvA/sAVoN48gWSxVgOiPcqKg5xukD0LbsMms27vibdhzn9MHxM76u3W8J2z+487mIbSq2PCZsv73zQEinD2BvRXTOSTA+PhC6DMVhArqPLfWLhey/HKWa2WMH3hOyD/DfitBqaw3+bnyaWCmKeFMZRCk3GHs90alz9rYfudwCwNsHe6sKRsPLayJPgNrNVWCJL1GsxbWuFNNUNWr84Z0+AK+BXiWmqAqg7wxdIxBAW1ElbPtko7/ekX3lpbWRHaSDrR6WhyvdkWiIOn0AS/4cu3HEmHf3vyvk9AG8vkf8HR1vqu8xV9Kq8f/dE6ORJImWtrpaIacPoOHAPgJ+sTnFQNK9NngEQaC6C609Mf+euDp+hmFohmFMAkqAGcCoaPtKknSrJEmrJUla3dAQoR5ZSm8lBCnIZ4mG4swikuqm4hRTrQSwuyIr7DlSxecUdps77HGno+87cYcpTB0RVbs0m9j5KXJGp6hZniq+a5xrD30NSoAlQRWs3IJF2aMlLcpdvGKX2DhOpOgzURQxwVNIiW53Rko1cW3aw3+HJPi7noyIviP79H4UIDctupCr3NQTLzRLCGdoNdOBJtvEHCHVGp2C80CQMlksmuQwUlpajEaSJFocJs65rFiE1EAHGjk1ROSNLCHZE/Pv6ZeZp2EYrcAiYDbgliTp8NkoAYIuwxmG8U/DMKYZhjEtNze8AyHnZyNPKP/sA3cayrRxMRh5fLGk5JE+7tpjPpNT8kHq+VkkWyruqV8Ttl869hYUS2ilNUm2UDZe3L7dlkFeTvDdZps1g1FDrxa2XZ4zC5scfgY/1D2ZMblzhezPz5tCmhJ+ccCKzNzc8UL2Ab49YjZOOfiNf3FROYoU39svWxGbYKdZo3tY3TNBLL/SbVPIiRCl6JBhdp6YB3fLvMhe0eyh4jkS8Z4D2kNHQR6h8Eqx/FDZbUGZFF59UR7tRM4Sd86s54ZRrJPAeskYYdsnK319R/bl/SjCN88cHtH5u2b6IMYUJa5D1Is5d4j3vSlxd8YuHHohwzLE8mZ/d+rvYjya2OE+T7xMBcDwd9+J0UgSC0dq4oZW210pjD71dKG+M75wBbJgWs1AknHuYKQgi53pZw1CjrAIOlDEU9UzFwgYhtEqSZITeA+4B/gi8OJRiesbDcMIXXOA6HMY9IZm6PYglRQimRBu6G/8rfvxVC3Hll2Os3Ayamct/tZ9OPImINvMSWQbukrNntdpqHgH2eJClm14Og6QPegMysZ+BSkGN1pN/SpWbfwjXn8LTkcB40Zcx+Dicw7VETTHe7sfYXXNa5RlTMZisaJpATIdBYzKPZUyt7hTdpgXqz7h6cpF+HSVTtWDjoYVK1cMOpWvDxUXRzmMpuu8Wr0drxagS/VT5Wnn+tKJjEw3X8Pv3k3reLkueNjc3SPHMr90qCn7t3y8ip3e4CFE750xFaegeMlh3qps557NvcNCvjoshRtG9q5t2Rd0w+Bfi7xUtIBh9ERPSoDbBTedYqXAbe7arNzrYe2i4MeGjIUJs8xtO3ZW+qh9QeeQrhFSSk8ZMqtbpvALVmSTzzet2kdgWTtGtR/sEnTpkG3BdmYmSon5XRy9y4+2vhopNxUkCX1XI5JNRpk3FNkaYUfwc5LjF6t3ZLxUPb0BjZX7minMcLCnsZOaVi8XjC9kT30n2al2ygtOwB2Vxj3wzzPA3waSBWQ7aIfTRBR6FJWOmhNlDodvLAMTQlz9gWEYfFr9KZsaN1GUUsSSqiUsqV5Chj2DsVljafW1sq9tH267m7yUPHKdudw14y7SbIn/G+64YAH63r3Rd3A4GL1+XfwGFCM+eHoT2z/p22796TeOYOycxBcurNm9gy2LP8Celkp3ayvDps3E7nCiGwa1e3axf/0a0vPyGT1nLjW7dlI++1SyihJbkyMculfFf6Adza+hNXlxjsvBmhO/0KNEVvUsBP4jSZJCz87i84ZhvCFJ0lbgWUmSfgusAx6N1RfKueYmi6EwfB702r2gqkiudAh4kXJKkFyxeWgGWvbiqVmPp3IFuqcF15AzcKWK19I6GgOwOTMpGHoJrvQyOlp2gASqrx3D0JFE6xodotvbRGXNYooL5mCxOMnKGInNmoZhaMTi8hqVM4v67n00dlfQ5DmIIlsZlT2LbFdsHhIuxU6ew42MhF220BboZop7OLcMNrfaCD0v420dDZQ603m+cguaoVOSkk6HGpu475k5uSEdP4eJ4vOHyXQ5wds7z84JOGIQkrG6vneinQzs6TKf+ygBaU6wtQMGBLSeUpypdpBjEGIbJoqXgsGmzWP4JCQrGBqg9Divaitg1WOi6KYU2dGHOdE6dYxcCzT4oFtHP+iLieNnHEqi1DbUIOWnYjm1DKOpG8mrQgTH73NEv78j+4LDqjB3ZM9u4oj8NBo6fOyq62DCIDepCRrCFBGrEwbNgopPQfP3OH1yCugB4FBeq2QFSQJkKI6POEOskSSJ0rRSltcs57kdz+GyuLh8xOUEjACD0wdzsP0gZRllpFhTaPY2M8Q9BK/qPSEcP72lJXKjo7GfGOHHOUXpQN8cv/wyd1zGEksMw0ANBMgrG0Z6Xj4Ht2/G096Ormps+vAdUtxZnPHFW9nw/ltUbNzArMuvweY88fIzDE3Hs70Zw6fhHJuDo7zH/9A6/QRqu1HSrMgJ+pzsF1VPswxknSK9cgeBlx+EwHGTVMWC5fyvoJSLL0zrqpeqF65A7z5WDEFx5lB85fPIVnN5ir7uOta9dxMBX2vINpPnP0VqZnT5dMezc9+LrNoUPAHbbsvi7FP+hjtdfNfpsXV3sL0ptAjLVWN+zrQisXIUqq5x4bK7aVW7gh6XgH9PuZNRaWKra52qn2+ve5PtHcGFLspTs3l0+qXIgpP4Cxa+QXsEFZAU4N04qno+e8oEilPFrtFoVD0/Ol/s3Hf5dX77WnjnetZQmUumiE0QPnjRQ2dr+DYp6XD2lWIvswP/9hAIr49C6Vdt2NxiDpShGnj/VAXdIa4fm4TjJ2Kqnoau4392I8beEJM1WcJy/kgsk4tC2vi87PjFiv54P764poofvbSRgGaQ5rDw6BenM2NIfBZa48byh+CdH4v1ve1jKJwY2/HEkAfXPcg/N/6zz/1+OfuXXD7y8jiMKDZsGzVauO+wZZ9iy8yM4Whixz++uwjVKzb3Lh2fyUXfMJf/GC8CXi//vfsuGg6EqKUUgst/+hvKJiTm3xQMtdlL/V/XoXcfWqRWJHJvnYDa7KXlfztBM5DsCjlfHIN9qDvm35/Qqp4nA+rH/+vt9AFoKuriZzHjOHdsf7mX0wegeRrp3PWmsN3DVGx9PKzTB7DtU8EXIbB2y19CHvP5m9m4o+8vosO0+xrCOn0Ar26/T9j+azXLQzp90LNT+vsdz4rbr94e0ukD2NHZxPKmyM5PKCI5fQCh/7rwVHVEp6Z587LQqqXh2NQcnWro25XtkRsF4b/LIu+oLt+rowveu5GcPoAusaEDRHT6AA4+K666qa7vCu30AfgN1CVif4C+ozG00wegG6gL92CoEZRFkyQMqqbz2ze3EtB6rpkOr8r/e3vbAI9KgPfuFu/7vFhJpf7i0U1im8L3rLoHVU9MdekDXw9fiioSe848K0YjiT2iTh9AxaY+7oD2I5s/Wthnpw/g/X88EIfRxI/2RRWfOX0AmkHLq7tpe2MPHHpOGj6N1rf3D8wAI5B0/CJghJvldbWDLiajDBBoDy1rrnWZV2rzdYcukH0Y1ScmvQug6eFl+T3eKGawIWj1hq4Ddhif3i1sv8ITuYhvc6BD2H6DL7LbVe8Vdc3iy5bW6Bw/j+C7a0trdE7L1tboyj4cT3OUp1VLQN9D16MblBad7xwUoyXyedXrxBxLoyOKfj4V/OLPzST9i1fVafUce83UJahMeUh07VA4pyDdiTvZNgxDuJyDR/Xg18QXkeKJd6PYwuJnBhK5Zs/JSWdzk1A/T6dY6aaBQmvrfc9o7f5jnUFAT9DnZNLxi4AyembIY3L5NCRFPIY3fdSlIY+5hp4tbPcw+UMih0HmD71E2H6Wuzzs8bIS8Ty5QeljscrhQ/FGZE0Xtn9VSWQ10IsKQv/2kTg7bxhKmDBOGZibVyZsP56cOyi6/NJLisTUBK8oi04J8Guj3EL2L5gQ+Z5MsYFVMZ8rF2uizT/MmCk+dsuUyBLulrPdQraV8hywhP8b5GFZyZIOJxCpdgtnjTq2NNAlk0KH6iYksgIFk8T7T/lizIYSayRJYnC6WGLx9PzpuEymlMSLsv+9YKq/++abYzSSJNFSPvs0oRz0UaecFofRxI+UqXm9P5uej2PMsaVVXJN6t0sEko5fBJRTL0M5/Sqk/DLIzEfKH4w0qBxl9sVY5n/JlG1b1nDyzv4jku2zibBkTSFv/p+xZ4eRRI+S3EFnMXLG3ThTS7E5c3CkloJ8WJ1MJnfwBQyd9E1h++ed9hh52VPo0SaQAAt2WyY5mROZNelnlA+5Uti2JEl8b+bTZDoKgx4flTWHmyfdK2y/yJHNPWO+jF3q7SRISFxRdCq3DVkgbH9sRh5/nng+Z+QOIfUoRTgZKHak8c+pl5BlE09o/uiMCyK2WSKY3wfwreHh6zsWKjLfHycmIW6RJe4cFV5U4PaRqaQIioCMK7EyvSz08QwHfO9ccQGAS26J/Ltd9EVx+6W3WcOW97QPgtxTRAv5gZxtxXJdNgTzvWSwXpaFkinmmEkZDmxfnAKDM+BwjqAElKQhD89COaUU66VjhceeZGC4/5pJfOvM4Zw5Ko+7LxzDnfPDL/olJLe8A0VT+95v7BVw7m9iP54Y8uyCZ5mePx3puAeHhIRFtiAfmupJh/7PrthZMGQBfz3rrwMx3KiwFxRgnzFDqK9UUkLhD+6K8Yhix5f+NFu47+0PnR67gcSYvLKhXHX3HygYNgJXhhtnegYWmw2r03lMjT57SgqSLCMrCmNOO5Nzvio+Dx0IXBPzyLxiBJYcJ4rbTvrZpWScU0bWVeWknTkIx6gsMhYMJf3csoEealCS4i5JkiRJkiRhSIq79I3k+zFJkiRJPj8kcjmHkwK9Zi/q0lcwuloBGVpqQVNBkpDyy7Bc8T3kcNruUdC+/TWal98Lmo8jS/2KjbSRF5I163tIJurhVe74L/vX/wWOEwNRLCnMuPgtLFbxnQPD0Fm/9e9s3fNkb/uynQnlX2XMiBuF7au6n18vPh+vHjz++6zBX+bcEbcJ26/3tnHxil+EPP73Cd9kcqZYkXKA/V2t/Hrrol4iL/NyBvOHCfOF7QJsamni9jWfhm3z5qnnkOEQ+31/t34H79SHz2v5ZP4sIdsAj21v4T/7Qsf1f6HExffGZ4c8Hon/e8tDS5gU0NtOt1CWI7arFQiovPVE+HyhGWdD4WCxHV1/m0rFP0Pbt2RC2VfEd4sD+7tR/9N4pEbg8Sjz0rCdZU4NzzAMtGUVaJvrwG7BqO8EnwZWGculY7CMjH3R8STx4Z3NNfzj470YBtw6dyinDMvm929tY82BFqYNzuInF4wm40QI3dVU+H3RofdsH8ifALcuAhNpHfFmde1qbnv/Nvx6dPl6EhIXDb2IX875JdYYlP6JF9smTgSfWA7i6O2JK0C0c3U17z+yXajvTb+fSVqWufrO/YGns4MXf3c3DRX7kGUFq9OJ6vUS8B2be2mx2ymffRqn3/QVHCmR0xASHUM36Piwgu5NjVgyHWScV4a1ILF+r2SoZxgMn4fAi3/GOLAVGquhsarn5QFgGBi1+1BfEFeWBFC7G2le+vujXkZGz3+aj45tL9K24Ulh241Vi9i//n6Od8oANLWLNe9cJWwbYMe+59m654ng9nUf67b9laYW8YfvAyu+FNLpA/jgwGM0dosrY1624ldhj9++8a+oguI9mqHz3fVvBVX2/KjxAE8dWC9k98jYIjh9AAuWvC9sP5LTB3DBwsglH4LREdDCOn0Ar1R10+oTU5v73ypvWKcP4B+LxZXsIjl9ACsXCpun4pHw9tUWqH1HLGnc0AzUf4d2+gC0jzpQm8wJPmhrq1E/3ItR34VR2dbj9AEEdNTnN2OoSXGXE4Et1W18/em1rKtoZX1lK994Zi23PbmG51dXsaehi+dWV/LDF02KcPQX94/vu9MHULdRvAxEP+DTfHz53S9H7fQBGBi8tvc1/r7+73EcmTlalywRdvoA9ptUBY0nok4fwBM/WRHDkcSP//3mp9Tt3YWuqqh+H5621l5OH4Dq87Fl8UIW/utvAzDK2NO59CDtCytQ67rxbm+m4bHNCadinXT8wqBX7wZfePk8o0Hc8QAilm3o2v+hsO3m6vDlEPzdkZUzw3GwLrx9gF0HXha2X9u1J2Kb5VXi9lUi34y7u6qFbO/vaqU+jLLnG9U7hez2Bx/URKfG2iH4LFtUE50a63P7xVRVN1Ylfvh6KAzNIIrLkq7tYiffqAsEW6fphb7CnMqavju8upt+oNWU/ST9w0c7G9CPul4MA1btbz6mzYfbIyskJwQdYs9yADaKl/aJN1sat2BEc1MH4f0D4ouD8abmm+byvjwfis+dkpin4cD+PrXfu+7kCFf3bj/2+ai3+/FXJ5ZqadLxC4OcVUBYlQUAV3iRikg4CqaEPW7LFiuuDuBKHxL2uBRBNTMSGWnh7QPkZokXvbXLkbf9h2UKJOv3gUKHWJHiAkcqNjm0OMnIVPEwxngzNSs61U1RJmZGd93NyRULZ8xOrKiKPiFFqTRqcYupekqZ0YWrycPEQ8ABpNzwP4KUd+KH9HweGJHX+/1WmHHstTEi/wT5LWVb5DahyBsTu3HEmNL0UuG+IzPNi8jFC+dZJuvwud0xGUcSMZzpfZtHZJcMitNI+hdL3nGpXxYJS7Z4akY8SDp+YZAyclFOvxIOqzIeP5FXLFgu+Kqp73Dkj8deHDxXypJWTObU24VtFw6/nJSscSGPjzntT8K2AcaN+DKprtA3a07mBIaViitjfmXK/WGPZzqKGJ07R9j+t4eEL2VxYd50MqxiXkSKxcaPR80NeoOlKTZ+MmaekN3DBNc6PZZTMsScS7fdFmm5A4CXTp0kZH9wmo0CZ/hHT4YVxmWJOR+3nR55gjdVTP0cgHFRCLK5TMyFs+ZGfiyXXCuouumUkadGyEnOkrGUm8tbtswuRR7s7vnHcc6sNC4fOc3colOS/uGsUXlcN7MURZZQZIlrpg/igWsnU3TI+St2O/n9peMHeJRR8sXXxfrJFrjy37EdSwzJcebwxTF9LzeR48jhrumJq3xZdq+4ajfAyE8+jtFIYk9KtvgiRPkpiVki4Hgu+Nb3UazRvadSMrM4+5avx3lE/UP6WaXYSnsWzCS7QuYlw1FSEiuPNqnqGQWG3wt+L6RkYDTVoKMj+31IhUOFapYEQ+1uxt+4DVvWMLTuZiR7GraM2KyA+D1N1B54H4slBS3QgWJNoWi4eP2+4+nqrqWy5mPs9ixAI8VZQIoznxRXdPXgIrGq6i3W1byDgoUurZ00azYXj/4O2a7Y1JJ6cPereAJedAma/O2UufL5ctm5OC3mJ6c+TaWiu421zQeRZZlx6fmMzoiNsIWmacxb9FbQY2ZKORxmf2sbN67snaM5KcXBg3MmmbZf3enj6T1tdAd0WvwBVB3cDiu3lWcyKAaOweYqPx9v1zAMKHT3rNsYwIKJNmyKWKmIo3njaQ9akBrBF37JhmLSvqEbNC7x4m8DXe3RlVBSwFGikDHSxM7FIXSfhr6pC0rs4NEx/AZGSwB5uAuLoOhNMIx2HzgsGDIYu5ug1I3iCj/+pKpn3+iP92Nrtx/DgMyUnt9O0w1q2jwUZjhR5MSrhxmWj+6Dba9BzhjILoW2asgcAmo31GyGrnoIdMOYi6B0Fgw/c6BHHBUdvg4W7l9IpjMTl8WFIRnYZTtv73sbu2xnTM4Y6jrryEnNYUz2GIZkRI7YSQSqHv4HHfffH3X71BtuYNDPfhq/AcUITdN5+BuLo25vSYVb/3hGzOac/YGua9Tt2Y27sJCAx4sjLY3aPbtRfV6c6elISDjTM0jPyUWKsobtiYLa5kN2WpBt5ucax5NU9TwKvboeo7YBaVAhcq5YiF4wJJsDbA6MjhaMg7tAC6BLErJiRcoXD7MAUL1t1C36BYHqFYABzjyszgwUVw5poy4jZbC5wpYttavZu+F+dNVHSsYIrPZ0FKuLltrluPNnmn6INLZsZfn639DVXYema4CGw55F+ZCrGTnkUqwWczsH7+x6mE8q/3tI80ZCQ8Wm2Pmk4r9cMOIb2BTxkDRd1/nVtqdY2Lge7VBilYLE9q5KRqWXclbeJFNj92kqj+9fR623k0kZBXzcuJ+3a3cxLbOIm8omH1PfT4RQTh/ANR++w7NnnmfKfjCnD2B9l5eldY3Myc8Rtq3qBi9XdPJG9XFiCx0BGnwt/HV2HlYTL4KKJpU31mu0HXLMqtp6/n+aHUYX6IwqMvcw/vj14E4fwHvP+jn/enOhHZrPoGsXqMemC9C5QyN1mGbKsTQMA32Xl8DKLni3FRwy5FmhVcPY50O6LBvFbu786AdaULfWY7R5kUszkVKsSJKEHKG4e5LExH2Us97c5ee5VRVUNHs4Z0weZ5TnnTiT0YW/gmUPgeaF2nVBGsgcEVj7eDtkDYXrnoUc8ZSL/iLNnsaI7BE8v+N5Uiwp7GzZybambXSr3SDB7PzZTC+czj0r70GWZL428WtcXX51Qv923Q0NfXL6ADqfeoqmc84me+bM+AwqRjz8ncV9aq92wpp39jHt/KHxGVCMaauvZd+6NdicLla9/hINB/ZRMLznPvK2tzP29LMZNcdc5FOiovs0fHtakSQJx9jsuDh/ZjhpdvzUFRvRFn+mdmS5YB7K+NjFr+u1+wk8/0cIHDtRtZx9I8pEsYtX7aqn6tkvEE7NIW30FWSf8n0h+1U7/su+9feHPJ4/5GJGzhBfGdtX9Tafrv1lyONOey4LzngGu00sZ+yvK2+hon1zaPuWNH5y6mvYBZ3Lc5b+mA41tHjPgvwZ/HzUdUK2VV3noqVP0RYIriKXolh5dtZVZAuWAjl1YeSwJTvwgeDO32nvRVbsfGhqOeOzxWT/r/6wktowAnsysOh8sR3vzQdVnl4WXhnznDEKZ44Rc7zfe9aDJ7RuzxGiKfQeDLXDYP/DIbzKQwy/S9yx9P2vEX1jGIEdGew/LUG2ijlpgQ92oy0LLnolZTqx3TIVyRF6VzG549c3+jMi5kBTFwse+IRO32eqrFdNK+H/rhDP5e43Hp4HtevF+t74Kgw7PZajiTnP73ie3yzvW6H5WYWz+Nf8f8VpROYwDIPto8VzK0uff46UCRNiOKLY8beviQvPDJuWy3lfSezw6gOb1vPy//slmhpePXvUnHks+HbihhuLoHcHqPvberSmnne4JddJ3jcnI5tcTD0as+/Ik2L5tadm1LGrd+qna2P6Hdrqd3s5fQDqsteEbbZueJJIEn4d21/G0MQkjSs2h3+g1+17HZ8JZc81m/4S9rjH18D+qneE7Ydz+gA8agcb68R089e17g7r9AG8WbeStkAUM/wgvFW7M6TTB9ClBXilOr51hsQE/2F3e3QKVF9fs0PI/uYWX1inD3ruircqxZSwXl4TudzCou3i5QSicfrM0LA48i/XvELsmWB0aOGdPgAd1IVtYva9Ktry0ErHRounp7ZfkhOS/3x64BinD+CF1VXUtIV/lg44hiHu9AG897OYDSVePLjuwT73WV6znEZPdCrO/c2Oeaeb6l9x1dWxGUiCsWd1w0APISIrX3khotMHsP3Tj1H95koHJRrd6+qPOH0AaoMHz8bE+s1OCscPwwDtuIlcrOtmaCEu4lCfR4ERTU0hQ8cwBKXbI/Yz0PXIk+RQ6EbkybPWh9pCIgQE7XuidKZVwXPvi+K68B9/zSYInkB8a8749eiiDLoF72E9im5RDmFAMKK4NHWf2B9gaNH1M3yC16ZuRC4XkWA1jZJET7BnlgH4T/bfVBVdRus/AoLvclUXn8PEE8OT4IsJSUKiqVFei4aBEc0L+wQi2Ds2WccvDkiyjDJl7DGfKdPGhmgthjLpDJB6ny5lytnCNt0TbojYxjV4HrJFLI+tcPilYY9nFc7BmVoiZBtg7Iibwh63KC7KSs4Vtp/lCC/eokg2JuaLnf9TssdgIfzW+wx3Odk2sXIdFxaVYw9TzsEiyVxcPErIdrwZnx1daO6PR4tJY07MspMSxZPn8jKxc3/22Mipy9OGmAi7iPNTMycKVdKcuWLiN7LbgjQkcl/reWIhvJLLijw+P3QDlxVlXJjjSRKaa2eUYjlOzOX08lwGJ3oNFUmCdBNiYPN+GLuxxImbRod/HwdjuHs4BSmxEWGLNeVLPjHVv+Av98dmIAlGruB7sT+ZfN5FPfdcBAaNnYDVYa50UKLhmpSLnPLZHEROs+KcEBtBv1hx0uT4GYaBvmMfRk0DUmkhyjBzoivB0OsOoO9cjeHpAqsVedAolOGTTdn0Nu2m7t3vYXgObQVLFiRrCoo9ndTyi8iYcANSEIczWiq3P03V9ifQtQB2Zx4WWzpWezpZhXPIH7IAWTEnMLL7wKus3fIgAbWTw0v9smyjtPBMJo/5Oi6nuUne31d/jX2t6w/9q8e+hMzgjPHcMOH3pNvFBUba1W6+uuZ+DniPLUBslRSuLTmdW8suwBLGeYtEg7eL+3d9SqOvm1KXm41ttXSpAUal5/DdEadQ4jJXLy9Snp8ZZc8On58LPgodLn1Wbga/nDxa2H5XQOfOFbVs6+i9g5CqwOOn5ZPrFL82l+4K8PZGleMX3xQJzhwtnt93mFcfDb8aLZrfd5jugwGqX1AhyMJpyS0WHFniypuGahD4qA1tZQd4DVCAFBl8BqQr2K7KQckTPz+GrqNtqkPdUANdAeTCNCS3A0mRUSYWIKWHf9Enc/z6Rn+rXu+u7+AfH+3lYKuHs0fnc/2sUuyWxBIvCIphwOMXwIFlRN6WPoTV1VPKYaQ5oaz+4o09b/DSrpeQkDjQcYCG7gb0Q+kk+c58RmaOZFnNMiRJYsGQBdw9+26sSmJJzR9N7RNP0PL7P/S5n+Piixnyf/fEYUSxQyTPr3B4Opd9/8R4NB7cvpU9a1ZgAHvXrKSzuYm07Fxki4Lq8zJy1qnMueqGk07NE0Bt9dG9pg5kSJmaj5Ie2/JFZt+RJ43jdzSGYSS0UlUwdF0/Mm5ZltF1HTlGN8Th3/iwzXicm8Nj13UdSZJi/h2qqqJpGhaLxbRU/vEEAoEj5xxAluWYfYdhGEHPSazOT1NTExUVFUeun/T0dIqLi0lJic0KfF1dHZ2dPbl2LpcLj8fD0KGxUxXz+/3ouo7F0rNCpmkadnvsHpKapqGq6pHrXpblmN1XXq+X7dsNXC6wWsFi6akZnJYWm2Ktuq7j9/uRZRnDMLDZbBiGEfPnwtH/jpVtMyQdv77R347f4Wf9ifieBeBw7pEs9ziDh/+T5Z44cUnq+d+a1nNjn0Ac/b6BnneZpmlH7mtN0448B0+k327nzp04HA66u7sxDAOr1UogEECSJKxWK3a7HcMw6OzsZPRo8QXJ/kZVVaqrq0lPTz8yx4Ge3zEzMxO/34//UA5cWloaNpv5Uj79xfHPh6PfN4fnionwvjHD0X9jfz4Pk+UcjsIwDLRFK9DWbwOrFctpU1EmJfZDwFO9irp37gya2CNZXeSe+XtcJcELvEfC0DW2L7+bxspjBVAy8qYz/vQHY3KRLln9Mw5UL+T4FVRZsjBh1G0Rw0Ej8dTGn7KxvreAy6mDruHi8u+Zsv33PW/wn6rQ4jCPTPou4zLKhGxrhs51y1+g0tMe9HiZy82DkxcIq3r+buMa3q6v7n2gtQYqekRX/jJhBlPzxHZcL/twJQ2h4tJ39+yQfnyOeDmQn65uYElDaOXK0/Ps/GqqeKHado/GH948+p767G9RZPjhBXbSHGIvncY6D0vfCNfCw7AJMG66mAMYaNM58M+jc4oO74oeUglzQ+nNduHSCHpTAP+LjRhVQbYTbWC9JhfL8Ng4r0lOHlRN55evb+H5VVXohoGmG5xensufrpxIdmpsV7TjQtUqeEQgNaDsNPhS2Bt+wHll9yv86tNfoRrR5+sVuAr429l/Y2Rm7NTPY822UZ/N347W1Dr85DIA/6H/jvQ59P9Hb4+veJoZGirbef53Yos1l3xvIiXl2TEeUewI+H0s/Nff2L70Y1Kzsph3wy2seOV56vft+ayRJIFhICsKc66+gRmXXDlwAxZA6/DT/PwOfLtbUdwO0HW0Dj/OsTlkXjEC2Z7YrtWJ7W4fh75lF9qqTRBQoduD+u4S9MaWgR5WSAwtQN37d4VUczAC3TR88GMMweTrmj2v9HL6ANrqV1G33/yL7MDBDzhQ/T7BwmZ0Q2X9tr9R37Re2H5F25agTh/AkspnOdixU9h2l+oN6/QB3L6+7ypph/n3vnUhnT6A/d2t/GbbYmH7QZ2+4/jOxpVCtnXDCO30HcXZ76+I2CYY9R41rNMHsLjeR6NXXHTgT++EVkjRdPjXYnHRofBOXw97Ngqbp+qF8EISaivUvSUuyhR4uTm40wfgh8AzDRhxFvhJcuLx9IoKnlpegV/TUXUDA1i0o4HfvZW4E+xjeOQcsX77P4Gtiev4VbZX8vOlP++T0wdQ213Ljz75UZxGZZ7qe+8z1X+biVIQ8UbU6QN49c8bYjiS2LP6tZfY+vGH6JpKe0M9b/zlnmOdPujZYQd0TeOTZ/5DZ3PTAIxUnNbX9+Db1QoGaC1etDY/6ODZ1Ej7+xUDPbyInFyOX3V9r8+MmsSSUT2aQMdBUMNPgA3Vg9rV+++KhvaGYAVqe2ipiVynLRJVdR9HbNPYEr4kQzg21y8Ke3xnk/jfsKltX8Q2AcRVNxfXR7a/vT0xZbTXNUUn5S/qOn1UG6GcwCE+rRdXdQtE+OmauxI3xF2LYq3KVyPumOlVERQKVTCaElPpL8nAsa4i+IW5vqK1fwcijIl7fsMzsRtGjNnUuEm4766WXXQHonse9zdtjz9uzsAJkMZ0MlKza/sx/45GtbNq+5Z4DScu+Cs6Qh+rDH0sUTipHD+55Dh1KklCKk5cBTlreklP8ngYJKsLS6qY6pa7YEbIY9lFpwnZPJrSwjMjtsnLniRsf0IExc7R2acI256YETlPzW4iEnp+wbCIbcZnJOa1OTk7I6p2olpcZxRGF946N18sDBYgUq3UnLTEzW9RoojicZSI56DKpRHC8mwg5ZxYuU1J4s/0IVnBPy8L/nnCIZnI25725diNI8ZMzJuIhNjzbHTWaFwR5iADRdY3vmHOwAmeP3aiUjzqWEV9KQqBvEFjErsg/fHYy0IL84U7liicVHeGPHoYyuzJ4LBDeiqWC+YhZ0U3iR0IJNlCwbn3gxI8n0a2p5N/zr3Cqp75Qy4kf8iFvT7PKppLXpl5lbJBhfMYWnpR0PEpsp2p4+4gJ3OcsP2S9FFML7w46LEzB3+JgrThwradFjvfKOt9bo7mkaniOYQ3Dp7EsJTQE6Ly1Gx+MnqusP3riiOr1j46VcwxliWJQfbIE//354vlnuY4LMwvDJ9Ddn6xC3ck7y0Md10QOgnepsCt88ST5E+/NPIka5QJaZKSq+yEm8dZsyHvPPFFCeul2chD7cGf/g4J6w25SJbEdYyTDAzXTC/lq6cNIcWuYFNkbIrMBeML+MkFiZ1Hf4SvCZYHGH4ujBAv2xRvilOLuWfuPTiUvi3FDU4bzD1zE1f5Mv9rt5nqP3pr4u4iXf+rmcJ9L//x1BiOJPZMu+hSJp5zPjank6ziQVx6188oGnnsM+KwkqditXHGzbeR4hYrHzRQZFw0DMeYbCSrjCXPiSXHiWRTcE3JI+2s2FcUiDUnpapnkiRJkiQ5MUmqevaN5PsxSZIkST4/JFU9g6A3taJv2gGKBWXSKKQ0c9L2enMt6qL/YnS3Q3oOVO+GQABp6His59+CpJg7jf7W/TQvuw/N24olYzCeyk9AC+AonEbB+X8xZbujaSvbV/wSf3cdNmc+uubD723AYk1j5KxfkF0oHi5pGAYrN/6RvZWvoevHikVkpo/m3Ln/QpHNhYxtqFvIy9v+SLfaesznTks6N0+6jzK3eIjApra9/GTL4zQEeouwzM0ax/+N/4qwbYDlTZX8ZstiWlQvEpBlceKwWAgYOnNzyvjuyNnIJpRV41nHr9sf4NzFa0Ien56Ryn0zxXdzvQGN6z+updHfO/7/u6PTubTM3E797roA//5EJVh2QWkm3HqGA0UWP/fxruPnrdM4+JwfI0g6Xu6FMhmjY6OiqLeqqEvb0XZ7QQbLpBQsc9KRTJybJCcf3X6V/66spLK5m/PGFTBraOKqCobEMOCtH8Kax0APgGSDlEzoagQjVFKwBKd8B+b/ql+HKkJNZw33r7mf1fWrSbGk0NDdQKfaeeS4BQtIYGCQ7czmd6f+jlmFYlEb/UX13/5G24N/7XvHYcMY/WbiCvIA/P2bH9JX3b7MIhfX3Z3Yv9lhdixbwvalH3Fw5zZ8nZ3ougaGgc3pYtDY8XQ0NZFVVMyp19xIRp5YOlMSMU66HT+9uY3A4y/1KHsCpLqwfeVKJLtYaJfR3Y7/Hz8g5B2aXYj9S78Rsg2g+dqpfOaCkPYtGYMpueI5IdvtjZvY8EF452XcvAfJDJMLGI5Fy++gun5pyON2WyZXnPeOkG3ocfqe3vTTsG1+fto7pNn7HiZQ5WngipW/C9vm1Kwx/Gn8rX22DbCq+SDfWf9W2DYTMwr4+1Qx5yyS03cYUefvtPciC+d8dWgRNw0XC2s4651K1DCPnt9PzmJOgdiCzcFWjb8uDC89k5MKd54n5pxFcvoOI+r8+ep0Kp8IL8BScqMNR4G5WpNGt4b3gRroPtY9lie7sF+aY8q2GZI7fn2jP3b8rvnnMpbvbQZ6lNj/fv1Uzht3gk3WnrwM9nwg1nfuD+HMn8R2PDGk2dvMgpcW0BnojNz4KJ5b8BxjchJT/VILBNg5foJw/8xvfZMCs3mCcULE6TtMdrGLa36e2M7f8hefZenzT0XV1upw8OX7/0lq5gmSK5wAmH1HnlQ5fgD65l2fOX0And3oO/cL29M2fRLa6QNoqsHwiasPtm95Pqx9te2AsO2aPa9EbFOx5VFh+9X1n4Y97vO3oGnisvML90Ye2+s7/yxk+9H970Zss7R5q5BtgMf3h1ZUPcyGttpeRbQTgc5AdL/Zv/ZGLikRjFafFtbpA7h3S6uQbYCFmyOPv7ET/JEGMUC0b4w8I6h7V7wcxWG0rZ5eTh+AvqEbQ0/Mc5Ok/9ld33HE6YOejbOnV4i/lwaMPR+K911qLvIm3ry///0+O30Af1v/tziMJjbsOiOyeFw4WkR2CvsJUacPoOlgYqqwHs3698Mveh9NwOtlx6eC+bdJhDjpHD9sQcIubSbCDW1RrNpHoVoUsqs9TbhvJBRL5LErVvGQNCkKlTTJhLKWTYmsNpZiFQsJTI3i3IgqpQE4owj/lZGEC6DHE0uUv5noyK1RmHcq4ufFEeXtnqjRjFIUwQl91HEIjjXECVAk8R83yUmH02bh+MdUSrD3bKJjRtVTEReD6g+cgu/xVGtqjEcSOxS3e6CHkEQQm6NvLyhrH9snMcdJ5/gpE8rB/ZkzJRXmIQuGowEo4+aAK7RzJg2fjGQVfymkj7oU2R7aeXGUiis/FpdfgxQhx27opO8K2x897Pqwx7PcY5BNvGy/UH4n4WagEjILRnxbyPatZedjiTC2Lw+eL2Qb4FvDI4diXFRULmw/njiU6H6zP08eKWQ/xaqQaQvvWfx+qnio4fkTIt+PY4vAIuhcRpXSa8Jxck+xRnwyFywwn+OnjHEhFfR+PljOyEjIBYkkA0Ox28k10z97h6bYFG4/PXK5moRjpljYPgCXJO7uEcA5g89hSMaQPvWRkblj2h1xGpF5RrwRXTpDKIqfii7UcCBIzxV/fo+clZhloI7mlCuvJ9qXYEZeAaPmiM9zk/Sdky7HD8AIqOi7D4DVgjx0kKldJwBDU9HWvI/R3gyDyjG2LcfobkeZeg6W8ummbAMYukrbxqfQuhtwlM6lbd2/0LqbcU+5lbQR5souqP5ODmz+F631q8ksPAVd9dB88GNcWaMZOe3H2BxuU/ZrGlazZvOf8fqbwZDR1G6QLEwY9VVGD7vKlG2Adl8jr267lx3Ny/DrXsBAkayMyjmF68b9FquJlViP5uOPO//H4sYNdOufhc7ZJSt/GvsVpmebc8xa/R7u2/4pK1ursEkKs7NLsEgKraqXi4tGMTN7kCn7lyx8naYQxwZJVv57lrlr5/T3locsYf/47HEMSzO3WvzAliZerejm6KiXHJvEP0/JJ9tpThTI49f59xIflc3Hfi4Dl0+XmTLYnOO0+HUPbfXBj7lzYd7F5sRddL9B3XteurYd+7mUAoO/bMPiMJffdxhDNdB2eNB2eUACy7RUlOLYCMeIkszx6xv9peq5cl8zlc3dzCvPJSd1YK8RYfZ+BG//ADpqIHc0ZA2FA0vB294Tw+rvBEnu+d9GAFLy4YuvQl7il6wIaAHe2fcO71e8T0laCTUdNXxy8BM0XSPLmYXb5gYJOgOdTM6bzM9m/YxUW+Lu+AFomsbOsX0XESt5+SXSRif2b/bxs9vYtLimT33OumUUo6YXxWlEsaWltpoDG9ZRsXUjTZWVaLpKoLubnNIyxp91Lge3bSF/yDBGnXo6FmuybmxfMPuOPOkcP90fwKioQSrOQ3bGZvvYCPgx2hvBmQbeLlAsGC11yKWjTTuVALrqw9ewFbWzBkfeeBRnFmp3A9aMwTFZeW+sWkxn6x5S0ofR3rwVuzObouGXIscofMUwdBpbtlDXuAHQyMkcS07WOCwxiEdT9QB7mtfg17w0dVdhszgpc0+gIHUYsmB9w6N5u3olS5u34tdVGjwtZNrTOLdgOucWxKZWTrPfQ0fAx66OJvy6hiTBYJebMRl5pm1XtbVwzaolQY99ctaFpq+d9yqq+M32ql6fj3XYeHjuFFO2Aba3ePn79lZcsk6TV6Ndg7FuK9cOy2R4hvmJ5dYqP+9t0fD4IM0JWSlQkiMze5gVq2Lu2lFVlTf/EzyX8OKbHaZVMXVNp3OXhu7VQQbDL6GrOtZMC+nlJ16YneFTMTr9SFnOiNdl0vHrG8lyDn1kz2Jo2QeyBWQr1G+Dlr094ZwONwyaDoFuKJwExeafc/1FXVcd7+9/H9VQ8Qa8jM4ZzfSC6by2+zV2Nu/k8hGX0xpoxaf5GJ09msKUwoEeclRs+/o34MM+5GcWFTH6Q0ERn37E2+3nyZ99ij9InjUyoNOzaXZoiu5yK9z46zlYTrAw68aqCrrb2nCmpuAuLGbPmlWkut24MjJxZWTgSEnsxYdgGKqO2uTBku1EsvR/4GTS8TsKbf021PeWHLlRlFOnYplj7sGt7d2I+vYj4A2SUGuxYrnmhyj5ZcL2u6uWUf/+D3rkpY/Qc9dbMgaTP/9erOklQrYD3hZWvH4Rhh58glo+6zfkmQhnBOjorOSdT27GH+g45nNJUpg7/R5KCk4Ttr2zaQWPrfseepB9pzRrNrdNe4i8lDIh26quMe+Tu9CCCv6Dgszi0/4Pqyz+kH1w13Keq9yMTu97LNvm5IVZV+OwiK10nbnwdSLJe3xl8HC+NEJs1TMaVc83500lPYpC78G47IODNAUp5XCYwSkKT8wVW9nUdINfvOxFC/Nou3G2jTHFYrtmi17x0B5qq/UQY2fD8DFiu36du1RqXw0Q5LLpQYayr9uxOE+MSH11bTXq+7sgoCPlpmC7ZgJSRuhFoaTj1zeSjl+U+D1w3yjwtkbfJ7MMvr2eXkmOCcadi+/kvQPv9anP/MHzuff0e+M0otiwbZT4rt2oLZuRokxb6G/e+Os6DmxuEeo7+bxBnPKFETEeUezxdLTz3C9/RFNVRcg2smJh3g03M+WCS/pxZObw7W+j6alt6J0B5FQr2deNxj7UXPmpvpJU9TyEoemoC5cdM1nSlq7F8Imr3xmGjvr+k8GdPgA1gPaWuCqmYRg0ffyb45w+4JAzorYdoGX134Xtb1/+i5BOH8DOleJlKA6zevO9vZw+AMPQWL7ut+gh6yNF5rktvwrq9AF0BJp4c5d43sXPt/4npNMHoKHz2+3PCNvf2t7Afys3BXX6AJr8Hh7YHdm5CkU0V/UjB3YL2a7vjk6l9vKPQtf5C8fyek9Ypw/gQJfGqgYxtdw3NwTCOn0Az64Ufy5EcvoAtiwTNk/9u2GcPgAdal83r+rZHxieAOp7PU4fgNHQhfrx/oEdVJLPJ2/d2TenD6BlP6z5TzxGEzPqu+r77PQBvHfgPTY3bo7DiGJDxZ3fN9V/+zTzaTjxQtTpA1j3TmUMRxI/Vr/+UlinD0DXVD566jE6W5rDtkskWl/dg97ZM6/WOwO0vCI2zxpIThrHD58PtOOcBMPA6OgStxnwQ2f4G9TobBU2b2g+NE/4C15tE7/JPR3hJbcN3Y9hhJ+AR6K9M/R3+AKtqKq49HCnP/y5b+gSlxTf1hH+gdTTRvzcV3a3RWyzt0v84R9PVjdFHjuAV9R+Y3Q9VzeGr2UXioqmyNd0QHw9Iu7oUZyeQHPiR2oAGO0+UI/9PfSmxJcjT3ISUivo5FSYWMXpBw5EeM+HY0/rnhiOJLZ0ffyxOQMe8TJbSczTUhNduSdd02irq43zaGKH2ugJ++8TgZPG8ZNcTkg/ruCz3YaU7Ra3aXMgDRoVto08WDwUQbY4sBdMDtvGNVhc7Sh/SPji3XZXIZLJPLnSorNDHsvJnIjNKl6uYrB7fNjj4/LmCdv+atn5EduYUfWcnlWEI0KY6EVF4a+tgeKCQdEVZp7uFvttrx0WXb9rh4rF/p81JnJ4T366kOl+wZYbOawsffyJkech5aYgZR4b8qqUD1xx+CSfY2beJtZvzndiO44YMyl3klC+u4TEqcWnxmFEsaHk0UdM9Xecay6NJYk5hk2bGVW71KxsCoYnfujqYRxjso/5t3PMiVd4/qRx/ACs11+MlJ8DVgtku7HeeLFpgQvrhbchjz8NsouQMgt6JPtsDrDakYZNwrLAhEQ0kHfWH3CWnvZZjSGLE1veBGw5o3FPuZWMSV8Stj143FfIKg7uHNmc+Uw+9wlh24eZOOo2hg++jGMvJYnC3FnMm/H/TNn+8qQ/MzxzOtJxl6kiWZlbej3zhwm+yIEFhTOZlRHa8TolcwznFYiHimTZXPxl8gVMzyzGeZwDaJVkbiydyIJCsXIIAP83PnLu6qIzLhC2f05u5Jj1+2aMFbKdbbfwtZHhPa/vjXXjtos5N6OLrEwKI5jqdsLXzhAXjznvusiPzQu/JC5sVHyNDXt+6OeWa6hE9pwTQwVNkiWs105AHpOHVJSG5cyhKLPMqdkmSSLE5Oth6pejr+en2OCsuyF/THzHZRKrYuVf8/+FU+mdU2yXez/nZGRynbk8dPZDZDuzex1PFNImTACnuDrykL/8JYajiS03/DZyuadQfPm+xHXWj2bsvLOYd8MtONPTkS0W7CkpuNxuJFlGkmWcGW5GzpzDFT/9LYqg1sFAkHnZcFJPKcJanErK7EIyrxCfxw0UJ5W4S5IkSZIkObFJirv0jeT7MUmSJEk+P5h9R54Y8UIR0GsbUN/5BKO9E6kgF+t5pyGlx1Yi1mhtQF3xJnrjQejugIAXKbcU6/ybkDLEQ5e6DnxM05I/oHt753s5imaRf+6fkEwoS7bUrWbrkrvQj8+1kywMnfRtikdeLWxb11W27n6S7XuexRdoPeZYWkoZp03/HZnpw4Xta7rKfzf/go31C3sdy7Dn8bWpD5PtKha2/387XuCl2qVBjxXZs3hq+g9xKeI7Qz/f9AEfNOwFjlFlBmBUWjaPTrtUeEe62+9n/sfvhm2z5Ozwob7huHv1FhY19xbtOZpP5ouvWr5b1cnvNwXPcZSBP0zNZlaeS9j+G+u9LN0dfFHLqsD3z7eS7hC/r159NHxc/3k3WLEL7lgejWEY1L7qp2tXT56c5ISSq+3Yc0+qYI0kSfqH/90CW16CqHPbZZj6JbjwvoRW9qxsr+Tq16+mQ+1ARibflU+9px7tkLiadKiYtoSEjo6ExLjscTxw1gPkOBM39HrbhIngFxOyGr19W+RGA4Su6Tz9y+W0N/QtU75weDqX3jHVdLmg/qRyy0bWvv0ano4Omqoq8Hu6ScvO5eI7f0Je2dCBHt7nkhN+9mB0dRN46jWMuibw+DD2VeF/+nViuZNpaCr+F+5F37wEavdBeyN4OjEqtuJ/9v9h6GICKYG2ChoW/iCo0wfgrV5Ow6JfCI9b1/xsXvzN3k4fgKGyd919tDduEra/Yfs/2LD94V5OH0BH137e/fiWoIqf0fL27oeCOn0Abb56/rziejRdDXo8Euta94R0+gCqfc3csOoeIdsAT+5ff8Tpg94ijds7mvj1lkXC9iM5fQCnLnxd2H4kpw/gysViuwwNXjWk0wc9mrY/XNOEL5I0Zwg2VKghnT7oEXb5vzdDq91GIpLTB/DOU+L2j6ZxUeCI0wdgeKDyCR+aN/EjNZIkSSje+D5s/l8fnD4AHdY8BksTN2zQMAwufuViOtSeZ7aOTk13zRGnD8A49H/6ISVrA4NNTZv44ttfHJAxR0PH6jXCTh/AtvnnxnA0seXV+9f12ekDqNndzkf/3RGHEcWHxsoD/O93d7N71XIObt+Ct7OjR8ylvpanf3oH3s7OgR7i55IT3vHT91aBdtyDvL0ToyF28rDGYWcvGJ2tGHX7hex27Iw8Me+uEFe2aqxaTHhdeKjc/qSw/QPV74c9ruleahpWCttfVf1a2ON+zUNl+xYh2/fvfilim2pfM6pgOYrnKiM71B/U743YZiD49879UbWr9Ys53S/si24x4M1KsUWDxTsij0vQp+x3OjYHuf508Bwwp8abJMnnji0vivddaU5oJJ7sat2Faog9iys6Kqg0oV4dT6puusmcgYrIyt0DRfXu6JSzg7F9eU0MRxJfdq9chq4FvzZ1VWX/BrGSUEnMccI7fkFDOiUJKTWl9+ei35GWFSbMQ0JKzRSya3MPidhGtosXhnSlR7afkjFM2H6KszBim9Qo2oTC7YisLpnhyBeyXZ5WErGNgowlWiGA48izRw41TreKh5HGk9k57rjaH5EeXSJ3ebrY+clJOXHCYCKhhHiMWdJPnr8xSZJ+ISVPvG925HfpQJHrzBXuq6CQ5UhQVcKhiXvOzWKxiU+9nWm2GI4kvqTnhr/n0nPF5m9JzHHiO36lhcgjy475TD51KpJLXFWv13ekZ6PMvhiCSCbLsy9EShNz/FKGzceaGT7GOfcM8SLrqZkjSHGXhzyu2NIpHXOLsP0pY76F1RLawRlWeinZmeKKaFeO+RkQeoI7u/hyMqNwDoPxwxFXIYexDfDtoZcI2Qb444T5EazDvRPPE7YfTQZrmUNMEW1Uljuqdv+YIfbbnlOcijOCP13iUhibJeb4XTk9cm7d2CLxR19RFGmr1hg9fgq/0PscuEaAo/CEf3QnSdK/XPEIYlMeBRb8OdajiRmZjkzOGXyOUN87pt1BijV2i+SxZPQbb5jqP/jDD2I0kthz3m3jhPte+I2JMRxJfCk/5TSGTA6uQTJ8xmyKRiZmSauTnZNG1VNvasWoa0QuLUJKFReFCIfR0YLR1YZhtUN9BfKgcqRUt2m73toNeKpXgSQjKTY8VSuwF0zEPeFGZIv5XaG2ho3U73sDm6uIjqZNSLJMXtn55A4607RtTfPR2LKFusY1dHrq0DUfKc4CRpRdSmpKkWn7qu5n0d6nWFv3Fpm2AmwWJ6n2LM4a8iUyTewmHuaRfW+zsH49eVY3Nf4m0ixOhqQU8J3hl5JuNX8dPbpnNQe9HdxQOoG3anaxormSUem5/HDUXCyyucn7zuYmvrz206DHXjvlLLJc5sb/zU/WssETPMfCjLDLYT482MFftrUSUHs21FOskO1QuLU8k8nZ4jLeh/l4u5clOww8AVCBVBsUZsBFUyzkppmTj/b7/Lz9VPAw4DkXQU6e+fEfxtAMWlYE8LfpZM2yYssU24U+UUiqevaNpKpnH9A0WPkPqF7fk+vnyIS0XECCxt0Q6ISiqYAB1Rtg6DyY+kVQEl8H70DrAR5Y/wCzCmZxVtlZvLv/XTwBDy6Li45AB7qhMz1/Oh9UfEC6PZ0ry69M3N2+oxAReElkYZfDaAGddx7ZRNXOFlS/DsFeJ0rPUoXFLjNyegGnXjkSxXLiLfo1VVWAJBHwetm/YS3ls+aQWRQ56ipJcJKqnoeQs91golh7NBieDozOFnClg8UG1thsuasdNfgaNoPiwt+8A1lxINvSkRTztU1UfwedLTuQLXYUq53skrlIkmwqxPNYZGobV7O34k1UzU+qq5BBRWfExOkD6Aq0sb91I23eetq9TUgS5DgHUd9dYdrxMwyDRn87Nb5mDnobccl2vFoAu8UWcbcuGjRDJ9VqZ3v9Pr6z/i1KnBmMzcinXfVR2d3GEMEQ4cM8tzt0kvc7lQe4rny0KfuhnD6AivZOSk0q5+7rVPFo4DcAA7p90B7QqOgMmHb8NN2gpRuQQJYBHTr9UN3WM/czS2dr6Bw7fxAtJTNIikTWKSdOeE+Sk4sVe5v4cHsdl0wqZkyReOpBQqAokFEKVavBPRgatkJbBXQ39zh9g2ZCzggwNMgcDK7shFbzPJpmXzMW2cKqulW0+dto8bWQ78pnVuEsHt38KE3eJqbmT2VOyRwUScFtdw/0kKNDQODF292Nw+TCZ7zRdZ2sIhcHdzT3dvpkcLhkvJ09cjz+bp2dK2sZN7eY7OK0gRiuEI2VB9i9ZgXu/EJc6W6621rAMPj4v0+QXVyCPTUNq83GsKkzSctOXHXZYKitPgJVHVhL0rC4EzNtJxQnzY5fvFE//C/auuNCB+wurFd+Hzm/VNjuwRevI9AaXORDsqUz6NrXhXf9Opq3seGDWzH04A/OsgnfZNDoG4VsA3i9zby88BL0IPazM8dx3mmPCtsG2Fy3iCc2/Sjk8aHuKdw29SGhkgiqrnHGkh8SCJMU/+jk7zE2fXCfbQN0qwEu/fQZOtTQL61vDZvJtYMnCNmfu/B1Isl75FutvDhPLJz0tPeWR2zzraHFXDVcrBj3RQuraA+EfvYMcsk8NU+sVIc3YPCb17zoYR5tZ42WOXus2H21YbmH/RE0hXKL4ZTzYrfr93kiuePXN+L5frzjufW8tO7gkX9/+8zh3DE/dPpAwvPouVAZ+dl2DIWT4Oa3wJaYIZEAP1vyM17d82qf+kzKncSj5z6KTUncRaVto8QXL0tee5W0kYlZXLut0cPTdy/rm8DsIWZ9YShTzyuL+ZhizZJnn2DFy89H1VaSZRZ8+y7KZ58W51HFhu4NDTQ/twN0A2SJrKtH4ppoIoe4j5h9R554e8YDgNHWgLbuw94HfN1oK8Tj0L11G0M6fQCGv532Tc8I2z+w6Z8hnT6Aii3/QguIb0+s3fpgUKcPoKllM20d+4RtA7y8449hj+9tXcueFjFVqI+bNoV1+gB+uvVxIdsAz1ZuDOv0Afxzn/hkLZr3RV1ArKTArrbo1DQf3HswcqMg1HQFwjp9AJXdOl0Bsa25D7cFwjp9AB9s01EjNfr/7N13mJxV9cDx75mZ7T3JpvdegCQQQui9944IilQ7Ajb4iQ1BUVHsotJUEAFBpPcOIQkkEFJJ73WzvU05vz/uu2F3s3XKzs7kfJ4nT3beeefOnZ3Zed/z3nvPaUdnQR/A9uh+Ncb0Go3BMI/Pb/lBvuuN3pmJuEt2rOh+0AeweQEsfDTu3YmXnXU7ux30ASzYvoAX13acmTuZlkybHtPjN5wR/Rr9RHv7kU+iCvoAZj/R+/8GaysrmPNE1/9mNBLhzQfvS1yH4qzi2dXsPsmIKBXPrklqf7rLAr8u0Ppa2iuLoHXR1yEJ15d3uk+otp0yEl0QbOi4/Ui4gXC4+7VkmtQ3tl+LDaChMfqUxQD1oZpO96kNRvccuxo7f9+qQ9H/bnY0dB5Qh6L95k+wTbXRv+6uKGvs2uuuCUUXmFXVde1x8ZjyaUy6aghH9jjqBVuXTkol1Vuif2xd/MpDxVtNsPPjZHvKOzlHSKr6xB6HkqmuOoY6r71/kh6NtbXdrm9dVxV9zeeeFqkNtbodn7q9PcUCvy6Q/sOR/m1P5/Tvc1jU7eYMmQkdTrMQivb7bNTtDxp7dof39xl8OJkxLO6eMrb94q9+fw79+uwbddsAs4Z23P/sQD4T+h4cVdvHlE7rdJ/PDzsuqrYBLhrW+RTO/Yvjsw4y3o4c1LX04P2jTE4zpaTzKZY+oH9OdEuQj5zY+eOGlUBWRnRrd7K7snQkNZYFGdOuguwMRvRp+WE/YERs65KTauRhkBXF+qjMfJhyTvz7EyfDC4czrKD7U+4LMgqizgbaE0Y9/3xMj88984w49ST+ph8f/fKggWN6/zrb4oGDGNzNHAP7HN17P4ut5c0Y0Op2dNnlk8XW+HWR1lUT/uBltHyrK+sggm/c/vjHxjYdIVi1iW0vfZtg+VqIhGi6nOPLHUjp0T8gZ2Bs7W9b+zzrF99HQ/1OAoE8/Bm5+AM59B1yBIPHnY8/ENs6pPWbXuPdBT8hGPr0ak1RwViOPfi35GT3jantiEZ47pM/8dq6v+9x36iiqVy074+jLucAsKR8DVd+9FvCrUbeBDh/0BFcPz62g/38XZv44cevst2bTiuAH8GPj8P6j+CWfY6Nqf3DXnqyw/vfOu70qNt+c8Nmblq8tuN9Ysjsuammkc+/udUldmklzw8PHjWI4szoc08t2RzkwdkhQm2M6g0vgSuPyibDH3109sS9dR3Otz3zClvfFy1b49c9iTw+VtUHueHhD1m8uZKDRvfhF+fuhy/GbMRJVbERHvk8bFsCqhAJQiTskrkABHJgwBS3ni8SgtKJcOCVMCD6skQ9oaqxipvfvpl3Nr5DRCPkBnJBoDi7mFFFo5i9aTahSIhJfScxpngM2f5sLpx4IaOLOi4nlWxLjj4GNkdXsLy3Z/ZcNmcLrz+4lGB910fGSkfmc8F3ZyawV/HTUFvD7EcfYtWCeWTnF1DYr5TqXTvZuWE9jbW1+DMzyc7LI6egkClHHsvUE07B50uNjNUaUWrmbKZxTSWZIwrJO2gQ4uu5q72xHiMt8DPGGNNrWODXPXZ8NMaYvYeVc/BoY5DQK7OJLFsNkQgEAvinTsR/+AFRZX1s93lUCc9+ivDHbyHZeQQOPwffyOiLcVavfJGdb9+OBmvAnwGREBLIpuTAr1I4KfbpJeuX3M+ahXd9ekUT8AVyySkYxsh9v0SfQdFNlWyurHwZz73xBbRZTuLsrL6ce+IzMbW7bMds7llwA8qeSViKswfy1QPvpjAr+hTAH1as4rqFd1EbbtjjvhlF4/jt1C/hk+iubqsq96z5gHtXz6f5ShkBCgJZ/GDK0RzcN7qMmADPb1jHLUs/7HCfR2cdxcD86FI/H/PCbDqbtR7LiN9tH+7k+U3tr4P81Yx+HFAa/ajZK4uDvLi47eQ9PoEbT80mPzv674Wt68PMfaWRsPcUPp/72gHoN8jHoafEL71z5cIQu+a4JyqZGaBw37T52jam59SVw5PfgOXPuhp+ww6C034DT30d1r7rll0cfh0c+Z1k9zRq9358Lw8tfYiaYA2KUphZSFl9GY3hRjL8GUQ0gk98DMwdyFemf4UTR56Y7C53KJasnr15xK9yZx3/+L93u/UYn184/vLJjD1gQOc79wLBxgZe//vdLH3nDYL1dUTCYUR8KEpeUTFDJk5h07LFFA0YxNGfv4oBo8cmu8t7jRSes9FS+I15RD5cCvUN0BiE2jrC784nsiC+f/yRRe8QfucJqNyJbltH8Ik/oLWV0bUVqmfH6z9Ag9WAQrgRNIIGayl75+cEKzfE1NeailWs+eiPLYI+97y11OxaxuK3vk1j/c6YnkNVee7Ny1sEfQD1DTt5Y+5NMbV974Lr2wz6AMrrt3D/h9+Kum1V5dqP/tRm0Acwr+ITfv5J9Jncnt68nLtXf0Dr9AgKVIYa+O5HLxDq5uLn5joL+gDOm/1aVG2HQqFOgz7oWsmHtmyrC3YY9AHcMG8H0c5GWL093G7QBy4Z11/fiCGpUa0y+4VPgz74NOgD2LE5wvIF8VnsXb8pwrbnggTLlGCZsu25IPWbUjjBhjHJ8tyNsPhxCNW7Y+2aN+GeE2DNW+4YGaqDV2+DjR8ku6dReXnty/zq/V+xqWYTFY0VVDZWsqF6A7WhWkIaoi5UR0O4gbpQHasrV/OdN77Dmoo1ye52u7bcHVs5qCVTp8WnIwnwwA+7f+yMhJXn/7qI8m1xLhSbIO8+8iAfvvgMDTXVRLxMaqoRUKWmfBfLZ79F9a4yNi5dxOM//zHhUMdZ1k38pE3gF1nbdv70yJpN8X2edYtbbggFiWz8JKq26jbOoaOcvnUb50TVbpPtazteHK2RRiq2L4jpOerqt6HtlEXYtO2dqNvdXPUJkT2qmra0oTL6oH5zQxn1kY5Pzufuar9Aemfm7uo4n39QI6ys6Z2Z4u5YElsZjs78c2XnF0oU2F4fXdrNFds6f9y26K7VALBzS+ftb1gZn4NY7do9n6t2naUjNabbVr2257a2smZ//FjCu5II727u3ghSWMPM2RLbOUYi7brjjtgaaGj7om5vEOmknFFHNi0vj19HEmjtwgVd3rdmVxk7N6xLXGdMC2kT+MmAthOJtLc96ufp37qgt+ArjS5DU9aAqR3fXxrbgvKSAQd1soeQXxxbgdPsrL60l8KwuCD6heOleZ0XTi/Jjj4rZmlmEYFOpnGOyYu+/fH5HX/ufAgjcoujbj+RvjB6aELbP3VI1woh98mKbqH3kJLOH5cXQ83ior6df232HRSfr9asAXu2k9U/bb62jek5g9o43gbaSNE76ojE9yUBJvXp/rTIaB7TU7KOPibZXUicGFYf9RuWH79+JNCAUWO6vG9mTg7FAwclsDemubQ5gwgcdRAyrGWGR9+EUfgPjK2kQGv+aUfjm3gQiEBWLoFjL0aKu5b+vrVAdhFF0y53WUJbEAomnU9Wv4kx9bVowP70G35Cm/f5M/IZs/83yYkiDXRzPl+Ag6f/aI/tIgFOPPxvUbcb8GVyxvjrO7g/i8umdVzgvSMZvgDfHX8h0s43cGmgiB9MjL6UxnlDp3B0v1Ft3ucX4atjDyLbH/1arSNL+ne6z3VjJkTVdv+8rq2te+mY6NYWTyjJZkx+x8HZVyYWEYgyS9akQT72GdLxV9vVR0W/Bi+/yMe+B2e0e39OPux7UAyRZTN5o/0UzwwgAZAAFM8MkDc6NTKfGdOrnHw79J/y6e3CIXDRA1DY7ELXlHNgfNvHzN7uzLFncs64c/CLf/fa9Gx/9u77mx/rsv3ZfH3619m3NL7nR/E0+g+/j+nxE5cs7nynJDnta52Xe2rLjFNH0n9EYZx7kxiHXfQ5hk1p+3X6/AH6DnMX9/NK+nDyV24gM9syYfeUtMvqqQ2NaMCPhCNIZvsnZ7HSYAP4/EgMJ+9NIqFGIg0VBPJKCdXuwJdZiC8QnxNHgHConoa6nWgkRHZuKYggvgx8vvgliVCNsKNsMeFQkNzcfhTGGFA2iUQibKtdS2XddiIapjC7lJyMfEpy4lM3JaIRNtXtZGt9OXWhBgZkF9Evu4SSzPhcVasLB9lZV0tDJMTIghJ2NtTRNzMHf5xSon/5zVf4qKFlAd9D84q4/eDYr1pX1NZy2lsf7bH9tJI8vhOHCyrVjSHm7KgjHIKxhX7m7GxgVH6AGf3z8cUhIVMwrGwpb0REKM71M3dVIxMGwuA+8TnARCJKXXUYn0/IyfdTWxPG54PsnPgHZhGvmL0vkP4FAi2rZ/dYVs9uqq9wpRyyi9wFXIDqba5eX2ZXinT2bnWhOgISoCHcQG5GLvWhekKREDkZOdSH6gn4AgQkQIY/cedH8bT9/ffZ8dlLurx/5nXfYMw11ySwR/GzfmkZ5durycrKoLA0h6pd9TRUhyjsn0VjfYSCEhe4BzJ9FJfm4Q+k3lhNQ20t/oCf+toacvILqKusJLe4GJ/PT2NdLYGsrJQp49Bb9NqsniIyDPg7MAC3ZOcvqvobEekD/BsYCawBLlDVXXF73qxMdHsZ4RVrkZIifONHInE4ydZgA5Glc9D6WvwTDkQKoy983lqoaiO1694gEqwnVFdG49YFiC+D4hnXkDf88JjbrylfzvZ1LxFsrCIzqwR/Ri4lg2ZR2Df6bKS7+x6q59XZ17G97EMQEAJkZuQzZsQZTJ14TUwZVSMa4e0Nj/Diyr9QH64GQPAzts8Mpg04jqkDTyCz2RXN7lpcuY6vffhHaiItE31k+gKcOfBgrh17FgGJ/gtpe0MNj29YzFObl1HeWA8IipLtD3DekMlcMza2ejzt1fF7u6aC4196khdjqONXWV/fZtAH8NSuGt56YTZPxpDVE6C8UXltSz3LKhrZXh8BgXEFGRRmZTKxOPasmEs2h3huYYRdNQBhcjPgvdVw4KhGjp6UEXNw6fMJmdl+Nq4KEw6FGDLaT3ZOYgKzUJVSszxMIF/In+BH9oIAMJ0l6/i413vtZ/D+/ZCVDwdcAcEqKJ0EE05xqXnXvQer34Di4VCz3dXz2/e86Aq/97AddTt4dvWzZPmzOHnUyXy0/SM+3P4hW6q3sLVuK5n+TFbuWonf5+e8cedx8eSLyfD17uCv7Oln2HHDDd16TOOv72Tpm28x8Z//SFCv4mPTJ+W8dN9iassbwQeZ2X6CDWHQtlM/ZOT4OfqSiYxLgayekXCY5e+9TcXWLRT2K2XFvPdoqKulZNAQxkyfweDcySx9+w0aa2uYcMgRFPSNPju76b6EjfiJyCBgkKp+ICIFwPvAWcBlQJmq/kxEvguUqGqH+ZO7c0Uzsmo9wUefd1f0AN+kMWScEdtccY2ECT5wK7rNW3yamUPGxTfh6xv7nOS6TfPY+vw3vOLte+pz8DcpnHxe1O1vXvlfVsz7aZv3jZ/5fQaMOjXqtgEeeuoIwpG2F1H3K9mPEw//a9RtP7jwZhZsfaHd+4cVTuYrB/4NXxTB2bqabVww77YO9xmbN5h/zvh2t9sG2FxXxWVzH6Mq1NjuPgcUD+J3+58WVfudFW8HyABejTL460rGzrHZfu494sCo2t9YE+SSN7cQaefr5/YD+jGrf/Qjc88tbOT1Ze0nQRnZD645KraRv1BIef2/DVRXuBeRmQ1HnplFbn58r8rWb4qw8aGG3cl5c0b4GHJB/MpF9DZ7w4hfso6Pe7X7z4TVr7V93wGXwaBp8NQ39ryvdBJc/RpkRH+RMdG21GzhwqcupKzeJQwryiyiorGiw8dMLZ3KP0/5Z090LyrB+npWTJse9ePzL76YYd+/OY49ip9P3t/KC39dFNVjj7x4PPsckdh1+LF64pe3smJu+8mGcouKqa0oByArN4/P3vYrSgYN6aHepb5Yj5EJGzdW1c2q+oH3cxWwBBgCnAnc7+12P+5gFzehuQt3B30AkSUr0crqmNrUdUs+DfoAGuuIfPR6TG02qVz0ULtBH0D5B9EHTgAbl7b/xb6hg/u6YsOWt9oN+gB27PqIYKim3fs7UtNY0WHQB7C+cjEry96Pqv3vLbm/031W1GxiY10bWd+64H+blnYY9AG8X745qra7KtqCAr9duLxL+62IMusmwN+WV7Qb9AHc80nHJy0dCUeUN5d33Lc1O6C2MbaLXlvXhXcHfQCN9bCuk+eNRvkHoRYVWerWRmjYaiUdUlmyjo97rUik/aAP4IN/wFt3tn3f9iXwSccZspPtiRVP7A76gE6DPoAPt3/IqvJViexWTFbM7Cw5XceqH3wwTj2Jvzn/iz5z9ruPr4xjT+Jv15ZNHQZ9wO6gD6ChtoaPXu7df1/ppkcmDIvISGA68B4wQFWbzni34Ka6tPWYq0VknojM2759e0900yREgqekxWEtmGnJ3wt+pbF2oSuP7wUv0xg7PqYE+7bocXZsb5v9WkyMEh74iUg+8B/gG6raonqWunmmbV52V9W/qOoMVZ1RWtr1rJmBA/eFZtkAfZPGIIWxJeqQ4ZOQAc3KC2Tm4Jt6VExtNimc8hnoIMlK8QGxLVIeOvHSqO7rUtsDD8Pva3/KWWmfqWS0lS67C/Iyi5g24MQO9xlWOJkxJQdE1f6tky/rdJ9xeYMZkhPd3PMzBk+kINDxdLwDiqMvF9EV0aYH+so+XSvxMS47+vWPV44voqOknV8YXxR1236fcNj4jvs2uh/kZMZ2BB043E9+0adtZGbDiE6eNxrF+7usnk1yRvjaLPNgUk9PHx/3Wj4fjDqq/fv3/xwcfl3b95VOgvEdH4uS7ayxZ9En+9O8A0WZnX9/Tiudxuji6EsuJdrY97pf5Ly5/Eu6nhCmpx10RtsZv7vi4LO7XiYhGUoGDmbczEM63Ce3qHj3z1l5eex3bO/++0o3Cc3qKSIZwFPA86r6K2/bMuAoVd3srXN4TVU7zDvf3TUMke1lRFauc8ldxo2IX3KXZXO95C4zkIL4JXdpLF9D3do3iIQaCNWV0eAldyk54IvkDu/4D6grKncsZMf6lwkGq8nILMKfkUufgQdT0De2OoHgkru8PuebbN0x30vu4iczM59xI85m3wlXxpzcZfb6x3l+1Z+oC1UB4CPAuL4zmTrgWKYOOI6MGJK7LKvawFc+/D3V4ZbJXbJ8GZw96BC+OuaMmJK77Gio5YmNi/nfpmXsaqyjKblLjj/A+cP24arRsS1jOvylJ9s+KwTygOdjSO5SXV/PyW8saPf+fsDjMSZ32Vgb5K/LKlha0cC2OpfcZUJhBt+YUsKEotjXsH28MchzH4XY6c02zs2EzAAcOMrP0RMzYvpsNgk2qpfcBYaMSVxyl+CuCNXLwwQKvOQuvWFYNkH2hjV+kLzj417t9V/C+/dAZgHMvBIaKr3kLie7Eab1c2H161AyAqq95C77nOuSwfRyO+p28Nzq58gKZHHySJfc5aMdH7GlZgtbaraQ7c9mRfkKfD4f5487n4smXdT7k7s8/wJbr72224/zHXYoE/4WfTmpnrBpRTkv3P0xNbsaER9k5vhpbJ7cpeng7n3VZ2b7OeZzExkzPTWSu3wy5x0qtm2loF8pK+fOprGujpLBQxg17QCGTJjM0nffoLG2lvEHH0ZBH0vu0h2xHiMTmdxFcGsUylT1G822/wLY2Wzxeh9V7TCDRlcPbKoKjUEkK36lEJqL1FUj4oOMTAiHkMz4LPZWjaDBWnxeCQGNhNBQA77MrhW67tJzRMJUlX+C+LIQImTl9CUjqzgubTc0VhEM1ZCTVQLio6Z2KzlZfcjIiE9q7OXb5+ATH6X5Iyir3UhORiF9c4eQ4Y89OKgO1fHExnfYVltOfkY2fTMKqAjXcuHwo8gNxP7+bq2r5P2dmxieV8Saml1oGHIzMzh20LiY2wY456Un2dZq26F5Bdx+8FExt11ZX885byyg9SrOE0pyufnA6OoQtRaKKI0RJTfgoz4Upiak9M1OTLLhhpAS8LkRwXgJhRTBLSHyB1ymTxObvSHwS8bx0XjqK6FqO+SVQK53Abe+wgWDzS8St7UtxYQiIcrqy+iT3YeGUAM76ncwrGDY7jp/qaDs/ffZ2o1yDtnXXceoa65OYI/ip3xbLZk5AcLBMIFMP5GwomEltziTYH0Y8Qnig4pt9eT3ySI7t3cH6k00EqGhrpZARibBYCMBf4CM7N6bHClaGoqgEcWX2XKAQCOKNoTx5STmXKY3B36HAW8CC4GmTAQ34dYxPAwMB9bi0lWXtdmIpysHtsjqDQSffQOqapChA8g441ikID6BU2TnJoKP/w4qmtZSCKD4xk4ncPIVMQWAdZvmsuONnxCu2UpW/33JG3sy5R/8lUj9LnKGzqLfUbfgjzGV9OaV/2PFvFv32J6ZO5CpR/+J7Pzopxy+8NY1bC9b0OZ9QwYcxpEzf+GC5SisLHufuz74crv3Hzz0PM6e+K2o2ga4YPZtrGtoHTZ9alzuYP5xYHRZPWtCjZz+1gPUd5C45/sTj+SkwV2bVtnaxW+8wLrG9hPrANw2eRpHDI6unmJXsnq+ePQBZGdEfyB6en01f1pWQXUwQmm2n21espjiTB+/Pag/I/Ljc5BrDCmPzG1k0cYI2Rlw8n4ZHDgqti9kVWXh7CBrl4ZdkhqFjCzYZ2YGw8cnrErOXmEvCfx69PhogJqd8M/zYPMHn24rHgn5/WDDPFfI/czfuRHARy6D9bNdkfczfw9jYssMngz/Wf4fbn3vVoKRlmm+/OLnV0f9imOG9/7XtGTipKgfO2npkjj2JL7KNtfw8K1zCIe6d/5dMiiXi24+qFdfYFy/eCHP/fHXVG5vdm4lwpQjj+OEq7+Kz58eNfuqXl9P5cvr0VCE3P37U3L2OMQvNKypoOzh5YTL6skYmk/fiycR6BPfoLc3Z/V8S1VFVfdT1Wnev2dUdaeqHquq41T1uM4Oal16rnCY4FOvQZWb06UbthJ6bU6sze4WeuHvzYI+aBqDj6yYT3hu9NmINBJix2s/JFyzFYCGbQspe/eXROpd2aa6DbOpmH931O0DRMKNbQZ9AI21W1jxwS+ibnvZqofbDfoANm59i7UbX4y6/b/O/3qH97+74VF21KyPqu3Xt3/UYdAH8EntJjbV7Yyq/R8uerXDoA/gx0ujzwzbWdAHcNPiBVG1vbmmtkv7Hf9qdBlVAbbVhbhj0S6qghEUdgd9AOWNEX44P7psqm15+5MQH290z1MXhP9+EKS8NrasmJvXRFi9OEyk2ZScYAMseCtIfW3ips+b9NCTx0fjefUnLYM+gPI1LugDqNwAj10Dz9/kgj6Ayo1uWzjaHMnJUV5fzi2zb9kj6AMIa5hvvfEtQp0cn5Jt3Tejv6gLsGSffePUk/h78rcLuh30AezaXMv859cmoEfxEYmEeeb3d7QM+gBUWfTai3z8WvTng71J48ZqKp5dgzaGIaLUzttK7Qdb0YhS9u9lhMvc8qHghmrKn+x9WVhTZ7y/I1U1UFvXYpNujd+JY4tSDq3v2x5d4AEQrt1JuHVg0apyZ2PZJ1G3D9BQu7XD+6vLor8qtnVH5yf+28s+jLr9iHZ+YFq564NO92nL7F3LurTfK9uj6/+yqvh9/nraY+s6/szEw6rqIOEOjnvra+N3UrKpvOXfVERhS0VswVn5zrYDR1Wo3GWlFozpdTZ/1Pk+Ndtg0/w9t1UltvROvK2uXE1Y2y8t0xhubFH+oTeqefbZ2BoI9d7Atray41JPHdn4SXn8OhJndZWVVO9s/9xn25roy1j0JsFNe5aIa9xUTaQuRHhXQ6f7Jlt6BH5FBUhJYYtNvpHxKwbpG9F+EhTf8OinIvjz+hMoGtFqY8t1a9mDoyuQvfvx+UOADrKGDjw46rZHDjup032GDjwq6vYzfZ0X2J7S/8io2j51YNdGyc8eFF1ynUP7Do/qcb3BFyeM6HynGE0pziKngwQl+xTHr0D52AEtp5Zk+mFE39i++koHt/34QAaUlKbH16oxaWX0UZ3v03csjD1uz21F0U2ZT5aJfSaS1cEa+MLMQvrn9u/BHnVfv5u/F1sDQ3pvQfCSgdHnPxg/o/cmd8krLqHf8JHt3j9i36k915kEyhpdROu05Nlji/HnZZAxuOUSs6yxJT3ZtS5JizMUESFwzgnIiCGQn4dv2kT8R8QWMDUXOOFz+EZP9bI3+CErB/KK8R90Cr7pR8fU7/7H/YzswTPx55aSP/4MBpz4a7IGTMOfN4DCfS6maL/YUhKL+NjvmD8jbWTvKh44i7H73xB128MHHc34kecjXuZLny8Ln2R6zxtgn/FXMKj/zKjb/9YhD9PeR9Qnfs6deBP5mcVRtb1P4ShO7tdxKYhzBh5CXkZ0c7O/PfEwRuR0nFL7oZnnRdU2wGXDO0/D/dzhJ0TVtt/nozTQ+VfDmzFk9SzI8HHbAf2YXJTJwBw/B/TNIsfvaghOKsrkh9P7Rt12aweO8nPMpADFucLQEuFzh2bGXMqhdLCfqYdmkF8kZGa79X0lpcJBx2eSEWPbxpgEOPLbMP1zsDtTs8C4k2D/z0PBIBh9NFz0IBz/IzjgspbbUqymXE4gh7uOu4v+uf3xiY9cfy4+71hanFXMvSfdm+Qedq70ootievykl1+KU0/i7+wb9ie/pP3APJDpI5DpwzZ65i0AAQAASURBVBdo+bkbd2B/Jh4yKNHdi8kZ19/IyGkHkJWXTyAzC38gQE5hEUdecnmnZR5SRaBvDn0/O5GMQXn4+2ZTdOoocqa4zKR9PzuJ7Akl+Aozyd2/P8Wn976SKQkt5xAvtnjdGGP2DntDcpd4suOjMcbsPWI9Rlr6uV6gYuG/qFz8MBqqw184nIycPgSKhlE45UICubHVN9my6knWfvwXwsFaMnP7oxoiM6uEEft+meL+02Lu+7pNrzBv4R3UN1bg92cQibh1BX2LJ3PgvtdTUhRd1kqA2sZKfvHO+dSEytu8/zOTb2H64OhGtQA+O/tnrGzY0u79v5lyFQf1mxJ1++/uXMe3PnyetlZ85YifJw+7lNwos2KqKoe//FS79wvwZgx1/NZXVXPxux+3e//YnCzuPXx61O2bzkUalPL3QwR3KXlj/eRPSI9saCY9vLR4K88s3MzQPrlcfuhIinMTU0apR1Vthff+BNXbYL8LujY9NIWEIiEeWf4IC7YtYFr/aZw//nwCvt57Grj629+m/n9Pdv+BOTlMmh/d+v+etHbRTt59bAWRsLL/ySPIyPSz+O1N7NxQTUNtCH/Ax7ApfTjk7LEUxDkzZDLsWLeGBS+6tZvTTjiFfsMSv6zE7MlG/JKsfP49lH/wlzbvCxQMZch5DyFRfjFvWf0Un8y5pZ17hanH/pXCftFnvtqy431efqf9cgs+XwanHvUghfnRrXf7v1eOJBip73CfG2Y9xID8Ud1u+z8b3uAXKx/rdL/ZR97Z7bYB1tdWcOHshzvcJ1v8vHL05VG1f9hLnR8Mc4AXowz+ulLO4boJwzlnRPSlQEzHNjzUQP36Ty8b9D8xg8L9eu9JWrzYiF/3JOP4+MSCjVz70ILdt6cOLeKJrx7Wo32Iu3AI/jATypqy8Alc8uiea/5S2M/m/IwHljyw+/bFEy/mxoNuTGKP2le/cSOrj43+d5992GGM+ttf49ij+Nq5sZqHbula9vmcggwu/ckhZGSl7sW/yu3buO+bXyFY7xIxZmTncNkdf6CwX+9ea9ob9dpyDqZrqpa2H3yEqjZQv2V+u/d3ZtOyhzq4V9m2JrasWYs/+XuH90ciwajLOWyrWdtp0Afw3Mo/RdV+V4I+gP9ueDuq9u9d3fnVxnoNE4okLgNkXee7tGlNdU2X9rtzWfvZbk1sguWRFkEfQOXC9rP0GdOTHpm3ocXtDzdUsHRLZZJ6Eyfr3m0W9AEozH+g3d1T0eOfPN7y9orH29kz+VafG/0aeID6t96KU08S44NulGWoqwqyblF0paV6i2Xvvrk76AMI1tex/N3e/R6lKwv8ksyXVdjh/f6s4qjbzujksYGsjpOPdCY7q/NsRVlRJl/JCeR3ab+irOgyXGXStStnI/IHRtV+/+y8zncC/L0waUBhF6efWg6TxPFlyh7fzl1IcmtMjyjJazmt0ydQlBPdtPVeI7dPG9vil2SqNyhudU7Q+nZvkjl0aLK7kFC5hd2bGp2dn9p/XzkFe57r5hTGdg5qomOBX5L1mXUDSNtvQ97YU8jsOy7qtkdN+zoibU8Ny8juy+BxsV1Rmz7l6/h8HaSMzh/JqGEnR9V2QVZfRhV3vobslHFfiar9p2f9uEv7TS8eE1X7Xxi5P346joymFg1Aogz8SgKdHzSO7hddUNwnq2sHpIcOmxZV+6Zz/lyh5KBP/3Z9WdDnkNQ+8Jv08dWjx1KS++nn8crDRzOoKMWvTAyYAtOaZdEuGASHfDV5/UmA62ZcR8A7JwhIgOsPuD7JPWrfmEcfienxQ+/r3ZlLZ54+msycZt/xfsjIbvuC9Ih9+jJ4XHEP9SwxJhxyOAPHfprzYdDYCYw/OMWnh6coW+PXC4Try6la+jjh+gpyBs1ABQI5fckqjb5GYJNQsJqNy/9NQ+02+gw+jLqKVWTlDaTf0GPw+WM/kQyHgyxZ8SDbds2nX8kUamq3EwrXMmroiQwecAg+iW1O+sdbX+fBj28mpC2LYo4snMYXD/wTvnaC5q71Pcyhb7VdzqIPuTxz5G1Rtw0QUeW3y97lP5sW0XqS3m37HMtR/WNL83vfJ0v529pP2rzv11NncmBpbPV+vvbuRyyoqm3zvlePm0nAZ9eNEq1xR4TGXUrOcB/+rL1jiNXW+HVPso6P1Q0h3l25k2F9cpg4sOOZKyll03yX5GX0kZCR4sFsG7bWbOXjHR+zT799GJDXe2vCNVkysfvnQSPem01uUe8fTYpElI9f30CwIcLUY4YSDisblpZRubOOHRuqyc7LYMz0/gweW5zsrsaFRiKsX7wQEIZN3gexc4ioWFbPNODPLqZ42hdo3PkJEsgioyh+xb8DGfmMmHIFwYYKaspXkJk7kIzsPlEnjGktEgmxfssb1NRvJiezH5u3z8EnfoYPOjbmoA9gQ/nyPYI+gKq6XTEFfQB+v58Csqliz7WEg7LamPbTTT4RghomCz91hCkkA3/AT9+sXPYvir0Wz2XjJjK+uIQllbvI8vkJRpTheXlMLCxmSG7Xppp25HcH79fi9tKKKt7eXs4JA/tZ0NdDMvv5yIwtsa8xCZGfFeD4yb0/cOi2wemdrXhA3oCUCPh2GzEC1nZ9PRyFhSkR9AH4fMJ+Rw8DoLEuRNmmGoZN6kNmdoCGuhC7NtfQd0jXlr2kAvH5GL5PehRxT2U24tcLRIJ1bH3+Ohq2LgAgb8xJ9DvyB1FPA2xt27oXWP7ej9FIcPe2rNyBTD/h/k7XAXZk+erHmLvw9nbv9/tyOefEJ8nMiO6L69svHdTpPj879t2oAsCyhgpOmf2DTveLNqtndbCRE968v8N9rhx1AJeP2j+q9kORCOe89SJljY1t3n/q4GHcOHlaVG235WtzPmZBefXu28cO7MsP94t+GrIx7bERv+5J9+Oj2XtFM9rXZNzcOQQKCuLYm8RZ89EOXrh7EcGGMJk5AaYdN4wPXlhHqCFMVm6AU760L4PHdZ5TwewdLKtnGqhe/r/dQR9AzcrnqN80Ny5tayTEqg9+1SLoA2io3cKGZQ/G1PbchT/v8P5wpJaPlkWXTnntroVd2u/Pc78UVfunz/5hl/b715pXo2r/Ox893+k+f1v9flRtA9y/5pN2gz6Apzet58Nd8ckCtqyyukXQB/Dylp2sqY42b6gxxhjTvjVf+3pMj//kmGPj1JPEe+Pfywk2uAUhjXUh5j69hpB3u6E2xFuPrEhm90yascCvFwhVb21jW/uFxbsjHK4n2LCrzfvqqzfG2Hrno8VV1dGl/F9dvqBL+22uXh5V++Eu9B3glZ0fRtX++rqKqB7XVetqqjvdZ0t9fAKzVe2s89tav+cUXGOMMSZWde9Hf2EUgKqq+HQkwTSiVO9q2GNbc1U7Oy9tZUxXWeDXC+SOOqZFZk/JyCVn2KFxaTuQkU/JoIPbvG/AyOgybjbJze681MGEUedH1fYRIy/u0n5fmHpnVO0fVjK5S/v9buoXo2r/i6MP7HSfokD7GVE7c+GwjhPD5PkDzOobn8Koxw3su8cXRZZPmFaSRgkdjDHG9BojH/pXTI8v+VJ0x+6eJj5h7P6lLbYV9M1ucXvcDCtybuLHAr9eILv/PvQ/4Q5yhh9G7qjjGHjKHwnEsX7QxFm3MHj8RWTmDsAXyCUrdxDjZt5Mn8GxpdI96/j/khlofxH1jH2+yeABh0TVtk/8nDHumx3u0zdjOKP7RrdQ+Jf7Xd1pLb+ZBWPJDmR3uE97Thk8gaP6jWz3/lxfgCcPu6Td+zszubiEGydNJc/fsmhEls/HgX368fsZh1CU2b06Qe3J8Pv5w4GT6ZuVgV+EwTlZ3HPwfmT57evDGGNM/OUMHw6jo8x8nZ/PwGuvjW+HEujoSydxwEkjGDKhhANPG8V5353B/icOZ8iEEmaePopDz7f19CZ+LLmLMcaYXsOSu3SPHR+NMWbvYcldjDHGGGOMMcZ0yAI/Y4wxxhhjjElzFvgZY4wxxhhjTJqzwM8YY4wxxhhj0pwFfsYYY4wxxhiT5izwM8YYY4wxxpg0Z4GfMcYYY4wxxqQ5C/yMMcYYY4wxJs1Z4GeMMcYYY4wxac4CP2OMMcYYY4xJcxb4GWOMMcYYY0yas8DPGGOMMcYYY9KcBX7GGGOMMcYYk+Ys8DPGGGOMMcaYNGeBnzHGGGOMMcakOQv8jDHGGGOMMSbNWeBnjDHGGGOMMWnOAj9jjDHGGGOMSXMW+BljjDHGGGNMmrPAzxhjjDHGGGPSnKhqsvvQKRHZDqztxkP6ATsS1J1Etm3tJ7f9VO57qrefyn239uPb9ghVLU1QX9JOFMfHWCX6s5gs9rpST7q+NntdqacnX1tMx8iUCPy6S0TmqeqMVGvb2k9u+6nc91RvP5X7bu0nr23T89L1/bTXlXrS9bXZ60o9qfTabKqnMcYYY4wxxqQ5C/yMMcYYY4wxJs2la+D3lxRt29pPbvup3PdUbz+V+27tJ69t0/PS9f2015V60vW12etKPSnz2tJyjZ8xxhhjjDHGmE+l64ifMcYYY4wxxhiPBX57ERGRZPchGiKSl+D2B6bq78YYY3oz+241xpjeI60CPxHxJ6jdsSIyQ0SyEtT+FBE5UkT6JqDtw0TkUgBV1UQchEXkdBG5Nt7tem2fCdwuIv0T1P6JwOPAsAS1P0tELvX+z4xz2+O8z6UvUZ99Y+LBTv73PiIyFBJ33EkWERklImOT3Y9EsuOJSXfp9J3UXWkR+InIeABVDcf7C0tETgMeA34B3Nf0XHFs/2TgX8B1wN9FZGCc2vWJSD5wF3CjiHwRdh+E4/a+i8gJwC3A4ni12aztI4HbgSdUdVsC2j/Ba38QcEMC2j8Dt+D3OOCbwIg4tn0W8ChwI/Ar4JpEj4w2e+6U/cJMdN9T7XcjIjkJbn8guO+dRD6P6V289/37IvI1SJ/gT0T6AF8HLhGRMcnuTyKISCnueJKQi6G9lYgcLCJ3JrsfvUE8zxF7IxHJBo7xfp4sIsckuUs9KuXfXC8wWyAiD0J8gz8ROQQX8H1eVY8GdgHfjUfbXvtHAb8BrlTVs4BGYJ94tK2qEVWtBu4H7gYOEZHrmu6Lx3N4v59/AFer6osiUiQiI0QkNx7tAwcAf/PaHiwix4vIQSJSFGvDInIc8Efgs8A4YJKIHBFru83a7wt8BbhYVT8PVALTRKS/96UTa9vXAJ9R1XOBj4AvANeLSEGMXW/r+Q7yRqQPhPiexIlIYTza6aD9/b1R75kQ/wDEO1k4SUSOT1D7J4vI5+LZZrO2TwS+GuvnsYP2TwZ+m+6jI6ZN1cBLwEQRuRxSP/gTEVHVMuAhIA+4UESGJLlbiTDd+3euiAxOdmd60FLgeBH5SbI70pOa/iZFZJqIHCUiw+N1jtiL5QJTReRl3N/zmuR2p+uavV+TvVlf3f4OSunAzxvh+CrwDaBRRP4JcR/5u11V53s//wDoI/Gb8rkVuEZV53hXSA/CnYjdJSLnxekgGcJNY7wfmCkivxKRn4oT6/u/EwgCg7xg5L/An3Ajo/Hof6jZz48Cl+Pe7z+ISEmMbfuBz6nqItxBfBkwBeI2ahMCcnAnPoXAUcDngDuB78U4OhcC8oGm0ZR7cF9c/YDTYmh3D97J+z9xAfJNInK395wxn8SJyDnAm15gGffvIu+i0N3A1cA3ReSaOLd/CvBn3JXDb3gjvE33xfwZ8r5nvgjcJW7Kc9x47+vPgbmqWt/qvnj0fSbud/NnVV3R6r6UPu6YznkXHfOBYuDzIvJ5b3vKBn/NLupMwV2gvQK4PN1G/lT1BWAesB9wkTcCmLaazoVUdRdwM3CFiPwh2f3qKd7f5Em4mWeHAh+LyGFJ7lZCeRdw1gMHAqtVdRWAiASS2rEu8N6vM3HnNl/HLYU6uDttpPQBWFVrcMHAg7ipdNnNg784PMV7uGmeTXPes3DT9Qq9bTGtyVPVJar6qnfzCuCP3sjfu8B5uBP5WD0BbFHVl3Ff5l8ECtWJ6aqOqi4DTgV+DXyIex9OA54DzgViDc5eBa4SkYeAv6rqZ3DBdzUwM5aGVfV5VX3H+8IvB54GfiAi+8Zj1EZVK4Df4qZivgDcq6qnA38DhgJRj4J4bT+AO+m4VERuBRpw022Pi7XvTbzP/OeBH6vq1d7PE0XkUa8fUZ/EichI4HpgG26a8/7xPCEUkenAbcBlqvo54BFgYhzb3x/4MfBFVf02MN/b3h/ic4Krqg3AU7i/4TubTp5jDZxEZDJutPsPqvqaiPQVkQkism+8+g6MB/6pqq+IG60/tWnkUlUjFvylNxH5Au6C7L3A+8AsEbkKUjv48y6YXAtcDPwIF9im1cifd0HrMtyFywuAS9N55K/pXEhEvgFcilv+ca6I/DG5PUs8L+gdDHwNOAV4CxcQLWu2T9p8V7f63nkad566QkT+IiL5qhoSkXicdyeMuCnY1+HO9dYAI4Gl3RnsSvk3VFU3qWq1qu7ATX/LaQr+xE3zivpkT1XDqlrp3RSgHChT1e0i8lngJxKnNTKqequq/sT7+T5ccBmPOfZ1wATvoPtF4GfA8HiNfqjqh7hg72eq+ldviuk9uKBveIxtL8QF9AcBo7xtq3CjdXG5CtkU/Krqc7j1eKfFaTQUVX0U98f5Jl5goKqvAAXEvt7vX8CzwNFAjqpeoqp3AQMkTtMnvYsn85vdrlTVQ73nuMvbFm2QHAH+T1WPxwWs3wcOaH3FLYYTxBzchZQPvdvzgUNFZFicTjoDwFdV9V1x634uB64C7hCR30Fs0z5FJMP7cRvwH9yFoO+JyO3Ar7vzJd+GHNxnJ+Jd6f03Loj9VTz67tkAFHsHqaeAw4Gvexdx4jbd3PQu3ndnABiNOya8hLsAMw84p3nwl8Rudluz74yBwCJV3aWqfwdexv1tflVERiWtg3EiIsW4JQpf9y603o57Ly+QBCVYSzbvM1sInAHcoap34l7z0SLyp6R2LkGaPs9e0LsJd5H9EtzSpjO8c9zPiEhpOn1XexedTvaOo19R1RdxF+gjwC9F5Fjgtl7+WQ8Ai4CLgHNwF7d3AQd5f7+dSvnArzlV3YkL/oIishR3QlMdp7ZD3vSV9SLyU9xoxR9VtS7WtlufiIrIucAAYFOsbXt/1OtxUxiuV9Uf45KBPBNr282eY7Gq/r7pttf/UmBzHJp/FjfKd4mIXCEiV+DWH7wbh7Zb+xA3gumL15ed9wf5Cu4K4gnipgOOwq3Li6XdClV9ALc+9HoAb0SlDxDTaLe0TGC0EfiOiDQP4s8G+orIlGjbVtV1wALv5x8Dc3Hv83Rvv92jT1G2/w4uYGoaudyEm1pd4X35j+tu31u1PweY610g+Axwozei+11gH3Hrd2NpP+ht+gg4R1XfxyVqug4IRDOjoVnb7+NGjKcAf8BNo74IF7xOEpHDY+m7ZxfuwtXncCN/31XVGcAIEfl6NO2b3qn58cs7kQwBa3EJQoZ6F2Ufw039nNrVk5Nka3Vcbpqa/ybg80b+UNVngOW4iymVpL4q7/8DAFT1cWA1Lhj8vCQos3lPa+MzWwl8gvc+q2ot7lzyGhH5TnJ6mRgiIt4x8CgROd97T/fBfVefq6orxc1o+R5uNCltiMgM3PnvctzFjEdUdS3uwmcQ+D3wP01AMsFoNX1WReRAb2bBBtwaxZtw538rxOWs+A1uBkLnVDXt/uFOjrYA+8axTQEygZXAOmBcAvqdhZvyuQjYJ47tDgMOaHbbl6Dfu+BOHhcDU+Lc9v64K8d3xPN9beN5HgZGxrnNYtxc7NeB54GpCeh30+89pt8NbvS2Fnio2bZbcBcPhjfb9hAwM8q2/9VsW2azn2/GTRf+GS7g6R+Hvvua/sddRCjETef5H1ASa/+97Vmtbt8NHBLD7/7BZttKcFckL/De3+/h1tZeGIffzUzg7Fb73QfMiqHvzd/bLwKrcAfTYm/bt4EvxOtzb/+S+w+QZj9fjJvafhZu7cyNuCnFo4HTcVOrBiS7z1G8xmtws0G+A5wMfAu3vOH7uFGSd5t/N6bSv6b3D7f0YCLuHOR84CfAMd59BwBPAhOT3d94vmbv5yOBw3DH6MtwI19jvPvOwOUsGJvsPifgd3AWbhbMSd7tobiLGr8Ffoe7CH5GsvsZ59e8r/d99KVm2+a0OiYOav0Z6Q3/vO+d1cBB3u0zcYHe/d7ndhFwelfba/qjTxvikn48DNygqjGNqrTT/mW4hAiLEtB2BnA8sFLd+rl4ty+awDfcuzJxJG5N4dJEPU8iJPp34z1HAe4LJe5XhkVkBJChrRJpdLONPNwo2WPAIbiA5jPefbfgDoR/xK09/SxwqqqujrLtgKpe4t2XpW49GyLyGm592InqpvpG2/fm7ftxgd+DQAUwDZfYp8slSDppP6BulKMpYc2NwHnqriTGo/2f4S5mXayq/xFX5mRjV9/rNtrOVNWLvfty1Ju14I3UfzcOfW/e/lW4qXDP4oLYC3DBZkp9P5iOiavjejbuROQruBPmubg1NMcCipsa/WG7jfRC3iyKq4ArcRftfo07v5iCG+kPAL/szndVbyOuNNC3cRdpKnAzVMbhjuXbgYOBr6lbDpE2ROTLuMD9RdxFqtG4C2v74JbITAVOU9VPktbJBPCWJjyCW7O/CXdRfQjuwvTRQBGwTN0yhoSfF/UUcVmsv4X7nN/adIwTkUXAGlU9VVzOh141tdWbnfQEcImqfuCd65XgZlDMxA24fKiqL3X1/Uq7wA9cjQ5tlakujm2nzR+CMa2JW+hdCWTjsjIGmwV/Z+PWuBwA3KmqH8fYdn1TcOPdPx43PfuyaE4Qu9D+f3FB5dnRXFjpqH3vos3VuJHXz3f3d9NO+42qerE3nXSsqi6P9vunjbYbVPWzze7/PC5j7hfi1Pfmn5vDcAeqg4B/JOKilkkecfVif6mqXxRXL/ZcVT2+6YKON7WzaalEr9ZsGpzg1pJ/Dzc7YDLuRPlUVW0UkTxVrWl+0SoVictI+jdcYo8vARfiMjsWAP2BGcAn6qa2pzQR6a/eFD5xyb9uxV2Uuhy4SFUP8+4bhfu+2tmdC2CpQNxaxlrgHeAN3NIQxRtBUtVbkti9uGr2t7wvLpDfhVuC9H3c2twXVHW9t+8h6paH9ArNj/Piypf9EBekl+LWy28FHlDVR6JpP63W+DVJVNDntW1Bn0lbumeypEwR+Zd393LgGVW9MprgoI22mydimoYLKo+PdlSgk/bH4aZKnhdt4NFR+8AY3NX/C6P53bTTfpaI/NO7ApkrIpOi/f5po+3sZr+bSXh1yeLY9+afm0rgA1X9ngV96cX7TFbjyim9gZvSeYJ39yUiMlNVy1Mp6PNulnqj+GtwU7c/r6rHe0HfDbjp4qRa0Ccimc1+zgJqcIl3PocLgj7rve6xqrpMVR9Ik6BvOHC1fJqMbxOuzuSNuJksx3r7XYpL4PdBGgZ9o3GZaEfyadbWf6rqFbjfwWCJU7LC3sAL+k7GzfQ5B1iIS9D4d1zwdIb3uaA3BX2wu+8Hisjd6rK4r8TNMngTVz7qHdzU1aikZeBnjImdfposqV5EluGmG8SjTErztpsSMT0CrPACh3i3vxy3vug32o3pnd1ofxluVODfXZ1+2c32m34/VR0/Kqq2m97Xx9WrZRTH9ps+N4/hpqOYFNeUaMD7eTiufuVU3AkJwF3eSculwA1AXP6ee0KzK+zX4WrFFuKmha0HHhKRYhG5EDc98PXk9TQ63pT3c0XkJHHJO27FjdD3x6Xzb0oUcQLwJ29KWbqoxa1fGysiF+CS/p2Pu9h1gjcyfTFuWm/aBD+t5ON+D18EUNWvqCu3cxoucdjTGodkhb2F9/30PVxQuwb3XRRSN2X5QVzw15sHclYA00XkDlX9vapepqpPApNwydje7Pjh7ev1xQqNMcmjqjtE5CPc4uLjVXVDAtuOOYttJ+1vTXD7WxLcfiJ/9/HIwNtR+3Hru0meZsHRIFVdJyIVuHWdTfVJv+lNGx4LnB+viwk9RVyZpouAC9StxX5DXEmS6bgLGCHc+uAlSexmVFQ1LCJzcEGrHzhSVdd4I7X1wGXehZobgG+nw4hX0yiu9310IC7p0Cxc1tlzgdkicgcuqc3BuGUGcf0eTzYRma6q81X1IxGJ4BK7XC6utM4iXND/f6r6VDL7mQC7cNnrZ+Fqb57rfQ5Ow63Xnasu63qvIq4+eJWq7hKXrfNxb+TvCm/a6m242sovRv0cNnPRGNMeSWCypES2be0nr+2eaN8kjzd96oe4E5APcMkxvq6qL4jIANw6lO3xvtCSCK3W0uThggFR1ftFpNAL/pqmSObjRgxSsmyDN1pbjEvENAT4kao+6N13NC64LQLe1G4kiuitWr23V+LWLv4Cl8XzYFy24fW4hHq5wCuqujJJ3U0IcevD/4mbuny8t20qrnxBOfBTYJ2q1qbL+y0iB+BGbefg1jFOAfqoalBEDsKVc7i8ty078N6rwcA/cEmknvOmlvfFrUl8U1W/Jq5EzoZY3i8L/IwxHZLEJktKWNvWfvLa7on2TXKIyCzcOhlwWfJm4DIhfl29ZAmpoFVg0JTVEWA/VT2p2X7n4bIcpmTmzmYnxLnq6tM1nfzfC9yrqr8Tl1irIhWC9a5o9d4eDHwTV2t1uYgMxdXrnQE8kW4jXc3e7wwv2MnHBTsDgLO8+27ETRm8TdMow7K4Osm34oqzv+G9108Bb+PqNH4e+KGqPpHEbrbQOoATkUtw/fwV8Kqq1ovIj3DrcE+Ox/tlUz2NMR1K5Ml7ogMDaz85bfdE+6ZnicgxuJGiJ3E1+67EZckN4LICPoJbO5MSmgUGh+CS0pypqiEReVlcYqJvAifi6vedkryeRq9ZEHAmcKW47MO/VdVnROQbwF9FZAIuLfwXcdkCU1qroO9E3JrMkcDBIrLKGy15Ere+8XgReR2oTuXRrua89/sE4FQRCeFq7n7f+/e2iNyOK6vzpTQL+sYA/4erZ7dGXNKy/riR3m/g1pnfoG5dY68Y3Wz293kkcBSwEbfmfgfuolqJ9x7uiytxtTwuz9sLXrsxxhhjepE2rkSfjauBuS+u1tsOYLG3dugnpFipDm/q41BczcF+wFWqutALjv6Ny0Y7FDeSGZekUMngTc39CS7JxQ9x01m/rKoPicgUXMD3hKq+lLxexp+3XvN0XObOK3Hr+B4F3vNOtgcBdapanrxexp83Iv8v3Lq203Cf4w9V9R/eesZ84Cl1iUJSVhvfT32Bv+IKnYdxF6WG4zKX/io5veycd3HiF7gLZ0W4Worn4TKFn4ars/hrVX08bs9pgZ8xxhhjmrQaNTkJd0LyEbAZF/j9ETfSt1pVU2Y0rK0r/V7ChJuBV3EnxE21vfxAVtP0yFTSbCQhB1deYwuuXM51uDVftwPfUtV7xCta3VtGQeJBXFKMy3G1zp4WV7T8e7jkPE8Cb6XLa23S7D3/EjBEVb/nXcT4DG7E+hJvRLupvmbKvt/SrNC6uFJNAuzETV+9Dpds6m1c4qkZuILtvfK1etM4l+mn622vwk1FvhD3ec1WVzM0bu+XlXMwxhhjTPNyDeLd/grwS1wyjPuAz6jqm7jMgI8C/UVkULPH9WrNgtmrReRuEbkLF8DejEvvfqqIjPT2Dadi0Actapj9G5cY4hNciZVvqurfcEHut8UVNY80PSZpHY5R0+ev2edwDDACmCUi/VS1DFfDrgg3fTcrKR1NgKbX3Oz9W4V73fuqalBV/46b8niAt19Dq/1TioiU4kpzICKHAY/jam3+AChR1XNV9VncSNntwPze9Frb+K4swI3yNXkGN0qb5X0H1UB83y9b42dMF4nIZcAMVf1qHNs8C1jeNJVIRH4MvJFu026MMSlhEm76ZkREBuNGCk7z1swcA1whIhtU9UkR+Rlwu6ZAcfbmvO/xK3Brnsbhpq2ehEsK8VOgQUT+rqpxqVmaDCKyD27k47tN74+IrAQOF5dxtwFXlmJbErsZF61GQsYCn6jqXSKyDVe4+wgReVVdevxvATnpsv642Sjf4bh1mh/hpmC/hCtQ3gc3St8HKEteT+MqH8gSkQdwWWrPxQVKR+Eu3NTgynX8H3CzN+Lba0Y3vfdrFu4ixBbc9OvnReQWVb0ZN718Eu49S0gGYQv8jEmus3BZpxYDqOr3k9obY8xex7sK7QeeEJHZqnqpqm4SkWrgKBH5p5cUYRyuBthzTVeie7s2TvoGA39S1edxJ1ybcFNXD8GlUV+W4kFfAe64sh+uTAEiEgDm4aa9fRm4XlXnJKuP8dRsFPdrwHniahWuB34HZODWNmaLyDPeer6ULMfRlmaJQe4C/gd8G3cho+lizG3ez7eo6ifJ6WV8qepqEfk58AXgGKBSVTeLyKu4Uh3jvO+qz6rqtt4S9DUL0mfhEu68gvsu+hCXHOspcQlqpgLfUdU1ieqLTfU0xiMil4jIHBFZICJ3iYhfRL4gIsu9g8mhzfa9T1ya76bb1c1+/o6ILBSRD72r4ojIVSIy19v2HxHJFZdN7gzgF95zjmnerogcKyLzvbbuEZEsb/saEfmRiHzg3TexjddylIi8JiKPishSEXmg2XSYNSLSz/t5hoi85v38QxG5X0TeFJG1InKOiPzce47nxK0XMMakH5+qhlR1HC77YVMyhJdxo2JN331luBGFpJ9IdVWzwOAMcantg7jabU33PwZ8DOSr6ququik5PY1e8+ljqlqFW+P0T+BzIjJNVUPAA7jshkd5I7YpMT23K0TkM7hMlWfiknpcgBvBfRQ3rfUIXMKPtCKuDMdNuCm838YFfn4goqq/w51fXKKq/0n197vVZ/wT4E7gXeDXIlKsqluAJcD+4tYAbvP27RXfVV7QdxxwFW7K/OXApbhSOOfivmO/i8tK+lQi3y8L/IwBxKX+vRA4VFWn4Q4Sl+DWBRyKu5I0uQvtnIw7+BykqlOBn3t3PaaqB3rblgBXqOo7uKt031LVadqseKyIZOPW1FyoqvviRue/1Oypdqjq/riMdN9spzvTcQf6ybgaVYe2s19zY3BX0c7AnTi86j1/HW7BsTEmzTSNcIlL5PIU8CUR+amq/gU3LfDrIvJf3Enm771AItVchZtWdQewn4j8SUQGiEjTyVdKzoBqNpJwsoj8TES+hzt+/RyXHv4KETnAC+zDqroRes8JcTSaXcSUpguiuGDvEiAPt95rFm7q7j9xx9iqZPQ13loFBGNwUwI/IyJ+VZ0PvAVcKiJ9VXWnqm6H1H+/vc/4SSJyvYh8xwvsvoS7GPWyiDQFUo83rVvthabgRiqHeLd3AL8BpnjrMdep6ipI7PtlgZ8xzrG4xc9zRWSBd/s64DVV3a6qjbiF8p05DlcUtxZA3aJygH28kbSFwGdxXwAdmYDLmNdUt+V+3FXLJo95/7+Pq1HUljmqusH7ElzQwX7NPauqQWAh7srhc972hV18vDEmRTQfxReRC4A/4KY9noybNne7qv4Y+Kq3/XRV/TApnY3d13DravJxQcFw4BZc0pPPaYoWL/dOiE/DvZZXcFNWH8UFsr/HTfW7StwU0JTXaupenqo2qOq/cFM4D8N9Rl8GyoFCoE86BX3e+32KiFylLonJzbj3+DvebpuACJCZrH7Gm/eaTwV+BszF1aR80PubvQm3Vu5LuDp9z/WW0c1mFygOFZFZqvobXHbZv4nISO9znAtMFZGCnup3Sl7hMiYBBLhfVW/cvcElXjmnnf1DeBdORMRH51+y9wFnqeqH4pILHBVbd2nw/g/T/t9xQ7Ofm++3u++4IrZ7PEZdcodgswNspIPnMcakGHEJQI7CBQfgpm/e511sWi4uY95CEclX1a/gkkT0eiIyA6hX1Y9F5AvAGmApLuFDJnC5qt4prqi54oKHlF335U1fPR53QXEyLrCdD/wXN/vkV0BxugQ/zabuXgucKyLPArNV9VVxdQmvEJHtQF9ckfLtSexuXHkB0Bm4mUhN+QBewStO7n2mm9b0pcTfa1eISBHweeBi3NTzTcBEEXleVU8UkStxf8croPeMbjaNxOMuqF3mbbvNO2dcISK/x2Vc/XVP/n3aiJ8xzsu4K9z9AcRlw5oPHCkifb0r4+c3238NXnpk3LTIpivnLwJfEJHcZu2AS9m72Wvns83aqfLua20ZMFJExnq3LwVej/7ltdC87+fGqU1jTIoQl0TgUuBFEZkiIgOBXcAFIpIJ4F1NfxA4xZsS2SuuonfE6/sYYIf3XVsFfAU3GnYRrlDy50RkSrOpjykX9LVa71QN/Bh3ce4m3Anmd3CjXc8BFZoGiT28k+Wmn/fFje7djgvePyMi03A1607HTae7NlVHcdsjri7jpbgA6CUROQK3nOND3Gd7PvCONxLYVumAlKSqFbi/4whuGu/JwJHA8SLyuKpubgr6ehMRGYKbbnyhqr4hIgd60+lvxc1AuAZ3se0x6cEcCnYF3xhAVRd7ayNe8A4wQdwXzQ9xC4jLcdMlm/wVlwHvQ9zBtanWynPeAWieiDTiarLchJuO8R6w3fu/Kdh7CPiriHwd2J0sRlXrvavVj4jLyDYX+HNHr8G70v1FVb2yk5f7I+BuEbkFeK2TfY0x6cePWwN8Hm42QD9cYoingQ9F5Ive/f2BmakyatI0JV9EJgAPA1cCT+BS3f8Bd2FuMHAgsChZ/YyVN5JwNG6tkE9V/+6tC/8Qd4w5EFff7BHvd5LSvCmOTQW7j8FlPnxPXar+xbiyI1/BLbM4UUSyNU1KNrSiuFk61wIDcKPYRwL9VPXb3rnCBSLyVeAPvWXkKx5UdXuzC/I+3Lrc23F/073VNuBZXCbky3AXpWqBqap6u4gUAk+KyERVXd1TnZI0+lwYY4wxph0iMgooU9UK7wT6YdxUz3rcVKmbvZPGcbiaaDeq6kfJ63HXiCsz0Q/IAT5Q1XJxNdsOBW5T1TneSdbhuBkXP1GvdmoqabbG62DcmvM/417Pa7iMgPfjRm7PAD6vqs8kq6+JICJX4C5QLMCN+E1V1R0iMhyX3GU4rnZhbfJ6GV/N3nOftwRjAi7R2juqOtu70Pxj3OsXXCC4QF2Wy5TU7DULEFDVoDeleQJuhLMWV7LkIm+Kb9JLNohIjqrWtdoWwI1OHoybVfYK7u/1CFW92tvnBuDJZvkcEt9XC/yMMcaY9CYu9fu/cdPIv6GqW0Tkc7gsvi/j1oc1AneoaqWIZKbCaJGX9OEW3OhH08nhacBy4Iu4RF23qeq7SetkHInIgbj1Tm+o6sPislq+hhtZuA2YCPhTOAlPm8QVKf8RcIEX7P0JN/J3lrp6bUOBGlXdldSOxpl42TlFJKCqoaYA0LvvNNxUwptU9cnk9jR2zQK+ElXd1ew1j8SVI7kEyMIlafL1lr9pLxi/DvhhU8Dd9P3pjcRHvJ8Pxs08+F4yL8rYGj9jjDEm/a3CTW88FLhdRE7BJXNahcuI+D/cNMjrRMSPm+7eq3nrZW4GrlPVs1X1eOBu4ElgrKreiZsKdrs3FT4dzMRNbZwkIgWq2oCbsnsokKWqH6dh0JeDm9o3FLeOD1X9EvAB8JqIlKrLYJ1uQd8g4B/eVMCQF9wuEZGDvBHsc3DFvtOiLmOzZCj3i8gPcdk7S3CjvE+p6mpVXaqq7/WioG8i8A9cFvXdo6xeoDcClw15uLiSYdcAP1LVZ5L5ftmInzHGGJOmvGlw2aq6XET64ZIK+IANuCmdR+BGAa/C1fvcmQpJMbz1PjuAM9QVPN69rss7abwUNyKUiUti9Zyqrk9Wf6PVbBRkNLBFVWtF5Bxc+vrbgDnAfriRhOP00xJCKautqXteAHA2LvB9Q1Uf9Lb/Cvitqq7p8Y4mQPPXLi7Z3I3Av7zpyv/EBRi/9e7PUtWG3jDVMR5EZCZwD+5Cxq24DOTX4EpyrPL26TWvVUQG46Zv3uut2Qvgplk/h5t2+xTwvKr+zAv0+nlrFZP6Giy5izHGGJOGRCQPNyKWKS773X9FZBVuTd8LuBG+Sbh1J+Wq+rXk9bZ7VLVMRE4HfiYi73rT4bLU1XX7oYgcCYxX1Q9E5B71itSnmmajILcAz4rI/rgyDcNw0/zW4bJK/zjdgj4RmaSqS7zpjbtE5Hlvt8O99/peVb0+id2Nm2afXRWRIaq60ZvCugH4nYgcAtzclAREXMH2pvJLvSIQioNhuFp9xd7PF3rrdZuyo/e21zoKl2xmnXeB7S5gvrosnXm4zLIfwe5+b2/2c9JY4GeMMcakIVWtEZGbcev4fu9NHVuBW/u2QlXfF5HLgauBfyWxq1FRl9UxAswRkRlecJChqkHc9NWgt19KBX3eSEIWrvTOeNzox3m4qX39cCO4vxGRXbj38peq+t/k9Da+mgV9VwJniMil6pIRHY5bv/gsLrPlVBEp1BQsx9GaiAwAzheRe3AZv38mIgp8TVXvEJFS4HOqem/TFMFU+0y3pdlodn9V3Ya7iPF3XNmGo7zRsdOAY0Tke9rLkvao6tveSPRxuMLsb6vqTd59NcBH0LtGKcHW+BljjDFpS1W3eNPizsAFDtNxF33vEJEx3rTOW7UX1sHqCnU1y76KK6FToi4D4OeAgUCvn7Lamrdm6EVgBpCHOwn+B25a7gXAxapaLSKHqOrfcUkvbhCRg9NhnReAiByKC3S/7AV9++Iylm5T1Q24bLQ/SIegzxPEvef5uED/m7gyKz8TkT96+4wEFxj3piAiWs2CvtOB/3ojZqtw0ySfB0Z4yVBuBV7tLUGfiAwRVwcVAFV9ClcGZy4w35tO30Jve79sjZ8xxhizF/CSQ5wI7I9bI3YD8Bu888lk9i1W3nTIn+OSKVwKXK2qHye3V90jLnvhU8CvVfVub1sxMA83nXOKF/QdgSvS/gVvOuCXgKdVdV1yeh6bVtM783Cv7Xxchtm/ich0IFNV3+ttoyex8qZshr2ff+dtvkNV14jIZNxo0k24mprjgVXqZfVMdSJyFPA74HJVneutkTsEl5n387gLN39X1Sd6w/suLqHOM7j6md/BlcZ5ybvvZOAkXHbhh70LFL2SBX7GGGPMXkJEMnBT5e7AnWAuS3KX4sabFvYYMF1VU65Au4h8AZimqteKiA+YhhvpmYpLbHI7bnToRlzq+CeS1NW4aRX0DQAqVbVOXB3Ggbhsjq969/tIg4sUTZqNeh2Ey7C7ATdlsBH4Z9P6MC/wDabahYy2tHq/P4NbZ/werpzM53ClZe7BJW5qmq6e9KCviYj8FndR4g+4WpJLgdtVdbO4zMFXA5/gEg41JK+n7bPAzxhjjDFpQURye8u0sO7yEtLchivIfSGuIP1U3NS3w3AjIEuAV1T12WbrvVL+RE5ErsONbuXipvv9Dbd+sRB405tSl3a8qY4/Am5QV4x8AC74qwT+p6rvtdq/1wRB0fKm8q7HJXH5Nm6E7y6gBpdl+C+qOj9pHWyDl2Ao4q2TvgE3qjdHRF7Brcv8GPc+TgOWqurS5PW2Y7bGzxhjjDFpIVWDPs9c4BHcyF4hbtrqobiEF6/jipd/qynoS6P1XucDJwOnA8txZSl24oK/IDBLRHKT2MWEEFeu4evAVV7QF/DW3N4ClOISvhQ2f0w6vN+4KZGvAJtwo3ynqurfgPeBgwF/EvvWpmbTa2txCZbGe7cHAP8Gtnj/v9Obgz6wET9jjDHGmF5DRPpos9IM3lqoW3FTzDanycn/biJyKlANzMJloD3NS9IzCtiGy2K6M5l9TASvTMFjuOydC5vW+3lBbgAYqqqLk9vL+PEC25D3849w05dPV9W13jTt23AlK3r1FGZxJVWexE2Zv01V7/C2D9MUqBVqI37GGGOMMb1EU9AnIhkicgouAc9tqropnYI+EfmMiOyDK3b9d2CGqp7oBX3X4ILdcJoGfYKb2jgbmCEig7yg71Dgz4AvzYK+A4CbmrJequoPgP8Cj4jIQNwU5iuaErkkr6eOiPQTkWmttvkBVPUD4K/AA+rKbWR4fe61CV2aszp+xhhjjDG9iJeEZyZwPfA9VX06yV1KhEm48hSni8hJwAFeCv9DgMuAi1S1PpkdjAcv2Bmqqguab1bVBhGZAxwNnCAiC4HLga+rannP9zShKnCjuSoif/SC+T/ipvc+DcxS1ZWQ/OmsXoB3PVAiIner6jyvX2FxNTaPAVYCZ0kK1pK0ET9jjDHGmF5EXRH6OcAlqvpkbxgFSYDbgbUiso+qfhV4AzgL2Ae3njHlMrO21iyIuMbL+gi4NWNeIhcf8BDwOFCHK9HxTFI6G0dNn1cR2c+bGlmNm9o5E/iKiPTFZax9FrjG+7wnnbd2Ngz8H6DA2d6oNOKKtb8NZKnqP4APgX2T1tko2Ro/Y4wxxhiTcCJyOVAEPKeqS0Tkx7jRsMub7bN7LVgqa1auQXDp/3cB/1LVj70gYj5wq6r+NakdTRBv7eZPgIXAIOA/wAPAX3AlK07A1fB7NmmdbIe4Wpnfw2UcfRf4BRABRqnqY94+Kfk5tcDPGGOMMcbEXevyA97oz1eBMFAG/ByXKONHqvp8W49JdV0MItLtNRcCTwE3qurbIjIBV5/vl7hyHaVAfm9cxygi43FB6rm4LJ5N5TWa11b0Ncv0mVJsqqcxxhhjjImrVsW6Py8iXwTGeKN7PwDG4oKg0cDh6VSXsIkXRPwBF+weCpTjajSGmwV9vnR6zZ4IUAWsA1DVZbg1fQeqap2qruuNQZ8ngLsosUNVNwDfx9XR/LGIHAgtyjukHAv8jDHGGGNMQngB35W4KX//FpELvAyl5+IyWP4OeCgNgx9I8yCiSbM1fcNEJEdVq4F5wMNeoiJwa+ZGN8uC2Ss063uB19fVwEfAMSLST1W34UYrC3HvZUqzrJ7GGGOMMSYuRGQ4sFNVa7wkHofjkracD7wA/EdEslW1XlXn4JLYpIVm6/oKgHpaBhGvqeo2EbkHuJg0CCKgxWs+GbgTmOcFU9/2dlkgIncDVwHf6C2JXJp4fT8TNxIbAv4BfILL3nm4iHwMXANc35R5NJXZGj9jjDHGGBMzL1PlTcB64M+qWi0idwI5QH9c+YY6EbkemKeqbySvt4nRRhAxCZgIBIHmQUTavHYRmQl8Frc2bj1wEXAqcJL3vwLbVPW1ZPWxPSJyEG467inAfbgMpBfiymzsi8sy+x9VfS5ZfYwnC/yMMcYYY0zMRMSHG83aHzfa9XvcyM+PgH5eIHgB8F3gXFVdnbTOJsDeFkQAiEg2rq7dDlWdKiJ+r+bdH4DZXumDXkNERgEzVfXf3u3PAX5gM27t6SWqulJE+qhqmYhkqGowXRLw2FRPY4wxxhgTNREZB/hUdZmIPIAr2H0ycLWq3i4iI4CnRWQ9LqnL59Mh6GsdROAyd/4BF/iWAF/zphIuUNVX0iWIaDa9c5SqrhaRo4F3ReQ7qnq7t1sZMDyJ3WxPPrBaREpVdTtuhPK7uPfrAlVd412cOFVErsGVnkibpEMW+BljjDHGmKh46/iWATtE5Ee4Ug1/wdXrGysi16jql71C2AE+TXSSDvbKIMIL+k4HfiQil6nqR17ZindFZDLwMHAm8J2kdrQVL2BdKCIB4G0ReRA3Kn0Nbq1pqYgMBW7GlaKoT2J3E8KmehpjjDHGmKiJyDHAS8C1uCmNJbhpjo1AX++++9LpRLrZqFcAeBtoCiIewCUH+R+QBfwJF0Q8lbTOxpmIzMIF9xd7BekHqOpWL7HPXGAFcKGqbmia+pnUDtPi/ToNGAYsAH6LS0jzLPAt3Gh0BnC3qj6Z6iOzbbHAzxhjjDHGxEREjsedSE8FBuCyIl4EzMStnzpUVSuS18P42duDCBE5FJepdTbu9Z+Pq9n3fVwil1eB36nqz5PVx7aIyAHAz4GbVPU9ETkYV1/wl6r6gLdP09q+tHm/mrPAzxhjjDHGxExETgV+DczyTp5LcMFPrqquSWrn4mxvDiJEZF/gM8CxuIB3LXAcMFdVn/am9T4OzALKesNrF5FhwNeAI1X1oGbbDwLuB/6iqr9Kt/eqNQv8jDHGGGNMXHj13H4DHKyqO5Pdn0TYW4IIEekHDFXVBd5tgd1r/PKAoKo2eoHeA7hkNm94+2aqamOSut6CiJwEXA38G7ee7ylV/VWz+w/GJSd6O0ld7DG+ZHfAGGOMMcakB1Vtmur4klfeIa14QcRvgPeBGq8mIQCq+h7wBeA973YqB31+4HrgGhGZAe71eEHfIFyZinwvqcvfge+r6htNwSGubmHSich+wDeBm73sq78HxojIV5v2UdV394agDyzwM8YYY4wxcaSqTwCHq2ok2X2Jp70liPBGKsPA/+HW7J3tjerhTd99G8hQ1TJgE6723RPNRzh7Q9ArIsW4daaT8DKqAi/ikg0dICLfSE7PksfKORhjjDHGmLhS1epk9yGeOggiFDhDRL6hqncmp3fx1SxoOxyXpGYCLsD9BRABvqmqj3n7rmjjcUnTKvgsF5H7gIHA10TkDlVdKyIv4Yq2L0liV5PC1vgZY4wxxhjTSus1eiIyHlenrxpoCiIKgBOBJaq6KEldjTvvtf4HOBeoBb4HVAL/VNWPvH16RamGJs2yrZ4ITAPqgD8DI4ArcTMd/+gVnfel24h0V9hUT2OMMcYYY5ppHkSIyHdE5OvAGuCnuIDiqyIySlWrgMfSKejzBIAyYIeqbsCVajgM+LGIHAjQm4I+2J105jTce7QYF7Q+gCs1cReQCVwrItm4kdq9jgV+xhhjjDHGNLO3BRFNSVlEpEBEMoDVwEfAMSLST1W3AfcAhbiAsFcQkeFeXcGm6bgX4BLPZOLinAjwX2Aj8Dvgz6pa3xumpSaDTfU0xhhjjDF7PREZDgxT1be9IOK3wC3AfsA3cIlMCnHFy4cBAVVdmpTOJoCInIkLmkLAP3DrGSfiMnR+jCuFcH1TyYZk8gLVAmAZUIErJfGiiAwGioF/Aqd5u8/Frec7fm8N+JpY4GeMMcYYY/ZaFkTsrkH4B+AU4D7cOsYLgaOBfYF9gP+o6nPJ6mNbROSnwAxccPo3VX1MRCYB16rqF71yE8fjave9l8y+9gaW1dMYY4wxxuy1vACu0ssAOQO4TkQKvCCiCJijqpu8IOIeXBCR0kGfiIwCZnplKcBl7vwDsD9Qggt+VUQWqOorIpKhqsHeUJS+qS/ezddwwfmzwGXejNUXgXEi8kfc1M/PWNDn2Bo/Y4wxxhizV/LWszV5DViBywR5iYicA2zg0yDiMeCNNAki8oHVIlLq3V6PK1fxY1ygtFJELgB+7a1jDEPySzaIyETgbhE52tv0AlAEzMIVkr8CN0J5Dm666qmq+mIy+tob2VRPY4wxxhiz1/GCiJuAe1X1VW/K5wO47J1zgKuAW4FFwGQgkg5BX7OMpQFcMfYHccXoHwA+Af4HZAF/Am5U1aeS1tlWvFHX14D5uAA9givI/hngfuAo3FrEO1X1v0npZC9mUz2NMcYYY8zeqD9wCTBFRJqCiBtxQcR7QA5wG2kURDQL+k7DJaj5Bi6JzQ7gy8C3gG8DGcBNqvpUb5je2URV3/CCv+dxyXYOAR4ChgAvA48AghupNa1Y4GeMMcYYY/Y6e2MQ4QV9BwDX4QK797wahX/07r8RQET6qGpZbwr6mqjqW9403DtxGVefAE4CClU1JCIPq2oomX3srWyqpzHGGGOM2WuJyIl8GkRMxwURb6vqyyISSKcgQkSGAV8DjlTVg5ptPwg3VfIvqvqr3hjwtSYipwK/BGapakWrpC+mDRb4GWOMMcaYvdreEESIyEnA1cC/cevgnlLVXzW7/2DAp6pvJ6mL3ea9pvuBiaq6K9n96e0s8DPGGGOMMXu9dA4iRGQ/4Fe4+naLvKmSxwJLVPX3ye1dbLygvUZVX0t2X3o7K+dgjDHGGGP2el5x8suBqcnuSzyJSDGuVMMkoNHb/CIuG+YBIvKN5PQsPlT1aVV9zcvKajpgI37GGGOMMcY0kwpr3DrSuv8iMh74LlAN3KGqa0WkADgRN+q3KEldNT3IAj9jjDHGGGPSRLOSDScC04A6XM27EcCVuBl/f1TV1SLiU9VI8nprepJN9TTGGGOMMSZNNKvT91NgMXAurjj7OuAuIBO4VkSyARsB2otY4GeMMcYYY0wKE5HhInKo93MxcAFwIS7I8+GK0/8X2Aj8Dvizqtan8nRW03021dMYY4wxxpgU5CU0KQCWARXA11T1RREZDBQD/wRO83afCywBjreAb+9kI37GGGOMMcakIHUqgfuA9cB1InKOqm7CTeOc4/08FrgH+D8L+vZegWR3wBhjjDHGGNM9rYrMv4Yb4XsWuMyrbPAiME5E/oib+vkZVX0vCV01vYRN9TTGGGOMMSaFiMhE4CbgXlV91Zvy+QCwBpgDXAXcCiwCJgMRC/qMjfgZY4wxxhiTWvoDlwBTROTPuOQtNwKfAd4DcoDbgDtV9b/J6qTpXSzwM8YYY4wxJoWo6hsicgTwPLAJOAR4CBgCvAw8AgiwIWmdNL2OTfU0xhhjjDEmBXlF2u8E9gOmAycBb6vqyyISUNVQMvtnehcL/IwxxhhjjElRInIq8EtglqpWtEr6YsxuNtXTGGOMMcaYFKWqT4tIGFguIhNVdVey+2R6JxvxM8YYY4wxJsV5I381qvpasvtieicL/IwxxhhjjEkTIiJWpN20xQI/Y4wxxhhjjElzvmR3wBhjjDHGGGNMYlngZ4wxxhhjjDFpzgI/Y4wxxhhjjElzFvgZY4wxxhhjTJqzwM8YY4wxxhhj0pwFfsYYY4wxxhiT5izwM8YYY4wxxpg0F0h2B7qiX79+OnLkyGR3wxhjTIK9//77O1S1NNn9SBV2fDTGmL1HrMfIlAj8Ro4cybx585LdDWOMMQkmImuT3YdUYsdHY4zZe8R6jLSpnsYYY4wxxhiT5izwM8YYY4wxxpg0Z4GfMcYYY4wxxqQ5C/yMMcYYY4wxJs1Z4GeMMcYYY4wxac4CP2OMMcYYY4xJcxb4GWOMMcYYY0yas8DPGGOMMcYYY9KcBX7GGGOMMcYYk+Ys8DPGGGOMMcaYNGeBnzHGGGOMMcakOQv8jDHGGGOMMSbNWeBnjDHGGGOMMWnOAj9jjDHGGGOMSXMW+BljjDHGGGNMmrPAzxhjjDHGGGPSnAV+xhhjjDHGGJPmLPAzxhhjjDHGmDQXSGTjInItcBUgwF9V9U4R6QP8GxgJrAEuUNVdsT5XeOcuIvM+hkH98RXmEamth83b8U8eg29Q/1ib//R5tq0hvHI+Egqi+SWwfjG+kfsR2O/ouLSvkRB1Wz/En9OPSEM5jeWryRkwjczikXFpv7Wq8uVsXPUE/kAefQcehM+XQVHffRCJzzWBULierbsWUlGzgZ2Vn+ATP2MHH8+APvvFpX2AlZWL2Vm/lfU1K+mbNYD9+h5En6z4vecAEVVe2raY7Q1VjMkvZWrRMHL8mXF9juaWV+2iMRJmSmFfRCQhzxFRZVFFJTl+H2MLCuLadiiiPL2hnMIMH0cPKqIuFGFxRR3D8jLpn50R1+cC2FEbYUuNMq7ER1YgMb+vnlC/M0K4Tskd7EN8qfs6TOd68vgYq/98sJ7Xlm7n6PGlfLSpgvEDCpgwsICV22qobghRlJPBIWP7UtcY5oVFWzlhygBGl+Ynu9vxEw7CutkQrIOsfBh2EGgE1r8H+QOg37hk9zAhKhsrWbRjEeNLxlMXqmNj9Uam9Z/GqvJVzN48mxNHnsjg/MG7969urObxFY8ztngsBw8+OIk9j4+GFSsIl5eTM3064vcnuztJsW7RTsq31TFkQjFrPtpBTn4GoZCy9N2N1FUFmXLYECYfNpgdG2pYt2gno6b2Y8j4kmR3O66qdu5g84pl+P0BBk+cTE5+fM+XepqoamIaFtkHeAiYCTQCzwFfBK4GylT1ZyLyXaBEVb/TUVszZszQefPmtXt/8KV3iLy/qP2+jB9J5tnHd/9FtH6ep35PZPmctu/MziPji3/A54s+YApWb2Hjs18iVL15j/sKJ5xN/0M6/DV128fv/YCt657bY3tB8QT2P+qPBDJiO3DvrFjOM+99jfpg+R73De47g1Nn/SGm9oORRn720XUsKm/52RCEK8Z/m+MGnxNT+02qQ/Wc/96fKQ/W7t6W58vi99MvZmLBoLg8R5OIKv+38C3e2L4BgIkFffjt/seQF4hvsFQdDHHt+/NZXlUFwJH9S7llv33iEmRurm3kc2+toiHivluKM/2EVakKRvALfHXiAM4d0Sfm52nyzMoQD3wcRIGCTLjxkCxGFqXeZIaNLzVStjAMQGaJMPq8LDLy977gT0TeV9UZye5HIvXk8TEW9cEwB//0ZXbVBrv92GuOHM2NJ09KQK96WPk6uO9U93+TklEQCUHFenf7oC/Cybcnp38JMnvzbK595VpqQ7X4xIeqoihZ/iwawg2797vhgBu4bJ/LeG/ze1z94tVENALA5D6T+ffp/05W92O2+eabKX/kUQAyR41ixD/+TqBfvyT3queEwxEe/skcyjbXdr5zK4PGFnHONw9IQK963vznn+KVe+8CL1byZ2Rwxg03MXr6gUnrU6zHyESeHU0C3lPVWlUNAa8D5wBnAvd7+9wPnBXLk2go3GHQB6DL16BVNbE8DZGyze0HfQD1NUQ+eD6m5yhf+I82gz6AymWP07BrZUztN1dfu7XNoA+gqnwZG1f9N+bnmLf8rjaDPoBNO+exvXxJTO3P3vbyHkEfgKL8c8XvaGx2cIrFPWveahH0AdREGrhr9etxab+593Zu3h30ASytKuOpTfF735s8uXHT7qAP4PVt25lXFp+BhV8t3rI76AMobwxTFXQnA2GFvyzfRl0oEpfnqg0q/17sgj6AqkZ4dGn3T1KTrW57ZHfQB9C4S9kxP5TEHpkE65HjY6z+9NrKqII+gL+9sZr6YLjzHXu7t+5sGfQB7Fr9adAH8N6fYfvyHu1Wot0x7w5qQ+64F9EI6n3LNrQ6rv5uwe8IR8L8+N0f7w76ABaXLeadje/0XIfjqO7jRbuDPoDG1asp+/s/ktijnrfi/W1RBX0Am1dUsG1tZZx71POC9fW8+cB9u4M+gHAwyOt/vzt5nYqDRAZ+HwOHi0hfEckFTgGGAQNUtSm62QIMaOvBInK1iMwTkXnbt29v/1mCXTsoRapjC/yoKe90Fy3fGtNThGp3dHh/uJP7u6OxvqzD+xvqYn+u2voO3jegpn5bTO2XN7bfx/pILfXhupjab7K5vqLN7dsbqtrcHoudjXv2eUdDfF5Hi+dp2DMo3tHGtuja7jhgqQsrNaH4nBDWBJVgqxiyrC4xsxgSKVSzZ59D1an3OkyX9czxMUbryqI78QMIq1LbmAaBX3UXj+tVbV+0TVXba7v2uWoMNxKMBKlo3PM4ub5qfRuP6P1C2/c8Nwlti+18JdVUl9XH9PiKbdF/d/QWDXW1BBv2/D1U7+r4/Lm3S1jgp6pLgNuBF3DTWBYA4Vb7KNDm2Y2q/kVVZ6jqjNLS0nafR3KyoSCv485kZuAb2H4bXSGDx0FWbof7+GecEtNzFIw5sf22c/qRM3B6TO23eK6SCWRkFrV5n4ifgcNPiPk5xg45ud37fL4shvSbGVP7M0uPIdOX1eZ9U0tmUZhZHFP7TS4a2nY/TxqwT1zab+7QfkPIbzat0y/CcQNGxP15jh04AH+zaZ35gQAH9+sbl7bPGd7xNM79++TSL07r/EpzfUzo0/Jr7LBhCV26nBB5Q30EWs2sLp64d64p2Rv01PExVlcfMTrqx47om0ufvMStg+4x+13Q+T5Fw2F46q9pa+600ad1ab99+u5DdiCbk0ae1GJ7QAKcMjq2c6JkyZs1i0Crv6vC07v2+0gX42YMINqVH76AMHr/+OZZSIb8kj4M32fPfBSTDo9PTo9kSdgavz2eSOQ2YANwLXCUqm4WkUHAa6o6oaPHdraGQRsaafzX07CjDHx+KMqHqhoIh6FPERlnH4+vuDDm1xCp2Ebwub/AltVu6Fcj7v+MLAInX41/bOzLUqrXvErVKjdlNFSznXDdTrJLp9B3xlfIKBjcyaO7p752Kx+9eyPVu5ahCtl5AygsmciQMefQp398ltgsXfc/lq1/grKqVYTCdYj4KMobyXH730pJwaiY219ZuZin1z/Ikor51ISqyPLlcMSAUzh31BXktj6TjsELWz/mrtWvUxGsY0BWIecPPZAzB01LSOKVVdXl/HvdMuojIc4aMo7pJYn5Ap1ftov/bthIjt/PhSOGMyq/kwso3fDQ6p08uraMLJ+PL43vR1kwwrvbqxmVn8VnRvWlICN+QU11o/LkJyE2VUfYf6Cfo0ekXuAH0FgRYfu8EKFapWRKgMLRe2fgtzes8WstkcfHWD378WZu/M9CKuuDBERQgayAj8FF2eysaaQhpORl+TlqfCnrd9WxfGsVkwcX8ruLplOUmwaBH8DiJ+D9+6ByMxQPgwOvgnAjfPQQ5A+EQ69129NIKBLiwSUPMnfLXEYWjaQx3MiWmi0cOOBAXlr/Emsr1jK9/3RuPfxWcgI5qCq3z72dF9a8QJ/sPvzg4B+wb+m+yX4ZUWtct46d99xDeFc5xeecTf6RRya7Sz1u84pyXv/XMuqqGwlkBqivbiQSUULBCDSbaTNmRn+2r6mkpqKRgr7ZnHjlFPoNTe0EKE3qa6p57/GHWfXBHHz+AJMOO4oDTj0LfyB55xmxHiMTGviJSH9V3SYiw3FXNmcB/wfsbLZ4vY+qfrujdhJ9YDPGGNM77C2Bnx0fjTHGdFesx8hEh6z/EZG+QBD4iqqWi8jPgIdF5ApgLdCFeRTGGGNMWrHjozHGmB6V0MBPVQ9vY9tO4NhEPq8xxhjTm9nx0RhjTE9LvWJXxhhjjDHGGGO6xQI/Y4wxxhhjjElzFvgZY4wxxhhjTJqzwM8YY4wxxhhj0lxqFrxKMq2rIrLifcjMwTdmfyQQn2LUyVK1axnlOxZQ2GcKRX3jX5S8pzSE65m74zVCkSAzS4+Oax0/Y4wxZg/BOljypKvrN+l0yC5Kdo+MSbjG+hAfv7GRnRtrGLt/KSP365eQusYm/izw6yat3EHjgz+E2koAZOAYMi76HuJLzWLLG1c9wdL3b9t9e9zUaxk+/uIk9ig6DeF6vvfB5ayvWQnAI2v+yk8PuJ/CzJIk98wYY0xaCtbBX4+FbYvc7Vd/Cle/BvmlSe2WMYlUXxPkXz96j9rKRgCWv7eFSYcN4phLJiW5Z6YrbKpnN4U/enV30AegW1YSWbMwiT2KzZol97S4vXrxvahqknoTvbk7Xtsd9AHsbNjK61ueSmKPjDHGpLUlT30a9AFUboAFDySvP8b0gGWzt+wO+poseWvzHttM72SBX3eFQ13bliIi4ZZ/qBoJJqknsQlG9vzCCaboazHGGJMCwg1tbLOTX5PewqFIm9sj4dQbNNgbWeDXTb59j4SM7N23pWQgvlH7JbFHsRk2/qIWt4eOuyAl52kfVHoMfbMG7L6dFyjkiIGnJLFHxhhj0tqk06Fo2Ke3s4th6meS1h1jesKEgwaSkd1yedPI/fqRX5KVpB6Z7pBUmNY3Y8YMnTdvXrK7sZvu2kp46TuQmYN/yuFIdl6yuxSTHZvfony7S+7Sf+jRye5O1Coay3h9y9OEIkGOGHgK/bIHJrtLxphuEpH3VXVGsvuRKnrb8XGvU70dPnwQQo0w9SIoHtb5Y4xJcdW76pn79BrKt9Yyenop+xw5BL/fxpJ6QqzHyLQL/FQ1JUesjDHGWODXXT0V+DWdK9jx1RhjkifWY2TaZPXU2jpCT79OZNV6pG8xgZOOwDd0QOcPNMYYY0y7fvH8Uu57ew1+n/C1Y8Zx1RGjk90lY4wxUUibcdnQq+8RWbUeAN1ZTvB/L6ORthegGmOMMaZzzy/awh9eXUlNY5jK+hC3PrOED9btSna3jDHGRCFtAj/dtK3lhqoaqK5NTmeMMcaYNLBgffme29btuc0YY0zvlzaBnwxtlcijqAAKUjvpijHGGJNMM0f16dI2Y4wxvV/aBH6Bow/CN3E0ZGYgg/qTcfZxtgjdGGOMicHRE/rznZMmUlqQxeCibG47e1/2GVKU7G4ZY4yJQtokd5HsLDLOPDbZ3TDGGGPSypeOGsOXjhqT7G4YY4yJUdoEfsbUh2p5afPjbKvbxEGlRzOlxDLCG2NMrD7ZWsXD89aTneHn4oOGM6goJ9ldMsYYEwUL/EzauH3h9SypmA/Ai5v+w3VTfsrM0tQtSG+MMcm2cns1Z/7hbWobwwD8e+56XrrhSAqzM5LcM2OMMd2VNmv8zN5tQ82q3UEfgKK8tOnxJPbIGGNS3+MfbNwd9AFsq2rghUVbk9gjY4wx0bLAz6SFbH8uguyxzRhjTPTysvacGJTfxjZjjDG9nwV+Ji30yx7IsYPP3n07x5/LmcM/n8QeGWNM6rvwwGEM7/PpRbT9hxdz7KT+SeyRMcaYaNllO5M2rhz/HQ4fcBLb6jYxtc8sCjNLkt0lY4xJaX3yMnnhuiN4Zek2sjN8HDGulIDfrhkbY0wqssAvRlpXhdZX4ysZlOyuGGBC0VQmFE1NdjeMZ111AzkBH1XBMMPyssjwWW1NY1JNdoafU/bt2jFOVVm5vYbS/CyKctMsAUx9BVRtgX7jweoEGwNA+dZasvMyyM5Ps7/3NGWBXwxCc54k/M5jEAkjA0eTcfYNSE5BsrtlTNKVNYT49vvrWV5Zv3tbnyw/t04fxpRiSwVvTDraWlnP5++Zw9ItVWQFfNx48kQuO3RUsrsVH/PuheduhFAdlE6Czz4CxcOS3Stjkqa+OshTf/iQrasr8fmFA08bxYyTRya7W6YTNl8jSlqxnfBbj0LEZTvTLasIz3smyb0ypnf4x6odLYI+gLKGMHcu3pKkHhljEu03L3/C0i1VADSEItz6zBJ2VDckuVdxULcLnvuuC/oAti+B136a3D4Zk2TzX1zL1tWVAETCynv/W0Xljrok98p0xgK/KGn5VkBbbttlJ7XGAGyoaWx7e23b240xqW/NjpoWt4NhZeOuNDgRrNgIoZYXsti5Mjl9MaaXKN/W6m9boaL1NtPrWOAXJRk8DlpN6/SNnZGk3hjTuxw+oO0pz4f3t6nQxqSrE6cMbHF7SHEOUwYXJqk3cdR/MvQZ3XLbpNOS0xdjeonRU/u1uJ1TkMHAsUVJ6o3pKlvjFyXJyCLjvO8Snv1ftKYc/6RD8U8+NNndMqZXOGNYCcGI8vymCqqCYTJFmFmaz+VjS5PdNWNMgnzu4BEEwxGeXriZoSW5XHfcuPTIAOrzwSWPwau3QtlqmHwGzPpKsntlTFJNmDWIYGOEZbO3kFuUyczTRpGR6U92t0wnRFU73yvJZsyYofPmzUt2N4wxxiSYiLyvqjZ9oovs+GiMMXuPWI+RaTPiF5q7kPDchRCJ4N9nPP4jZiC++F9p1IrthGb/F63aiX/8Qfj3Ozruz9ET1q94lNWL/kIoWEN23mD2O+Rn5BeNSdjzLV33X1Zueon8nAFMH3cFhbmD49b2wl1zeW7Dv/GJj1OHXszE4mlxa9vEZlNtI39fuYOt9UGOHVjIacMSV1txe22Ex5eF2F6rzBri59iRafP1ZkzSRSLKT59ZzN1vryGikJPp54kvH8L4gS2ncpbVNPKbl5azbGsVR03oz1WHj8ZvZVyMSXlrF+1k4Wsb8Ad8TD9+OA21IV7/1zJqyhvIzgtw+AXjGTtjQLK7aTqRFmdG4Y+XE35l9qe33/sQ9fnIOCK+F401Eqbx0duhYhsAoXWLQXz49z0yrs+TaBtXPcHy+b/Yfbuueh1zX76Co85+FUlAbaKl6/7Hmws/zYC2uWw+Fxz5MD5f7B+/tdWf8LOPriWsLrvqgp3v8ouZ/2JgztCY2zaxCUWUb8xdx5a6IADv76zFJ8IpQ4vj/lwRVW57p5GtNW4Gw6IdEQAL/oyJkz+9vpK/vrVm9+26xjAn//YtVt52Sov9vviP95mzpgyA2avKqG0Icf0JE3qyq8aYONu6ppKnf/8hTZME1368k3Awsvv+2sogz/9tEX2HFVAyIDdJvTRdkQaT7yH88Sd7bIss2nNbrHTrmt1B3+7nXv5e3J8n0bZteGmPbZFwHZW7liTk+VZtbvl8VbUb2VGxNC5tz93x+u6gDyCojby/4824tG1is7SibnfQ1+TVLZUJea415bo76Gsye2O4nb2NMd312Acb9tgWjijryz7N5Lmtqn530NfkqYWbE943Y0xirZq/jeYrw5oHfc0temPP7wnTu6RF4EfJnlnDpDj+2QOloA9Iy1+ZFKZesors3EFtbs/JG9jm9lgVtHo+ET95OfGZDlCavedraWub6Xn9czL2+IIZmJORkOfqkyP4Ww1Wl+ba9DJj4mVE37av4vfLz9r9c2F2BoXZLUfZh5bY1X9jUl1B35wu7ddncH6Ce2JilRaBX8Yh+0Nes4NLZgaBYw+O+/NIfgn+Q88Fn8taJCWDCMw6I+7Pk2ijJl9OZnbLNLyDRp5OZlafhDzf9LGXU5Q3AnBB34zx15CXHZ+A+dD+JzC9zyG7bx9Uegwz+h0el7ZNbPpnZ3DFuNLdAdnwvEwuHdOv4wdFqThbuGBSYPdzDcwTzp5g0zyNiZebTplEZqurK4eN7UtO5qd/Z9kZfn5w+hSyAu7Uon9BFt89aWKP9tMYE38TZw1k6MRP1+iPndGf/iNbBnl9Bucx8WC78N7bpU1WT1Ulsm4zBEP4Rg1B/IlLKas15Wj1LqT/CERSM3ZWjbBrx4dU71pOv0GHkFswLOHPt7NyOblZpeRm9417+xtr1uATH4Nyh8e9bRObHfVBdjaEGFeYjS8Ba0ibK69XyuqVkUWS8OcyiWFZPbunJ7N6BsMRnv5oE68u3c6XjhrNxEFt1+wqr21k7c5aJg0qJDOQmsdIY8yeyjbV4M8QikrdYMvODdVs/GQXpcMLGDSmOLmd20tYVk+PiOAf8WmmyMiOXejOcnzDByE52XF5Dq2rIrJsNhoO4Z9wcMoGfQAiPvqUTqdP6fQee75+RYm78jskb2TC2jbRCasyf2ctEZQD+uYlLBBbURahvEHZp9RHcbZQnJ3aAZ9GlOp1EcQHecN8CUm4ZEx3bCqvY/66cqYOK+Ks6UM5a3rL5FlV9UHufms1xbkZnDF1CHNW72RkvzwL+oxJM30G5+3+edvaSqrLGph48CDKt9ayasF2hk4sITM7bUKLtJSW707onfmE3/SugGYEyLjgZHxDY1u/Ftn0CcFHfgrhEADhN/5N4Mxv4B89LcbeGpN+GsIRrp2zlsUV9QCMK8zi9zNHkhPnE8E/fdDIm+tdEpfiLPjB4VkMyEvdk81wo7Lq4Qbqt7uZGLmDfIw6LxNfwII/kxxPfriJ6/69gFBE8fuEO86fylnTh+y+f/nWKk75zZuEIu4z+8P/Ld5931ePHss3T7SMnsakm9ceXMaiNzYC4M8QwkH3959TkMHZN+xPycC8jh5ukih1z5DaoQ2NhN+Z/+mGYIjQWx/E3G7oncd2B33uiSKE3nw45naNSUevbqncHfQBfFLZwEubK+L6HOsqI7uDPoDyBnhmRaiDR/R+5UvCu4M+gNrNESpXWHZSkzy3P7d0d1AXjii3P9cyI/MPnli0+/7W/vz6SspqGhPeR2NMzynfVrs76AN2B30AdVVB5r+wLhndMl2UdoEfjUEItzpRqq9ve9/uqK/Zc1tddeztGpOGKttI9VwRjG8AU9O458lmVbCNHVNIuH7P1xSKw9eXMdGqqG35R1Xe6nZFXfuBXSiiVNen9sUYY0xLDbUd/03X16T4gTjNpV3gJwV5+Ea3TFTi3y/2tWX+/Y7ac9vUo2Nu15h0dPTAAvKbTevM8fs4duCeZVdiMb6Pj0H5n06BFOCo4YlL6tQTiib48TWreOHLgqKxqf2aTGq74MCWx9MLW92+6ojR7T521ug+DG+nDIQxJjX1H1FA36Htl22YdOjgdu8zyZc2WT2b08Yg4Q8WueQuY4bjn9j+gak7wktnE37/OYiE8e13NP79jrbEC8a0Y211A/9dvwtVOHNYCaMKsjp/UDdVNCjPrwpRXq8cOtTPlNLUD5Lqd0TY+VEI8UHfqQGyStLu+lyHLKtn9yQ6q2c4ovx77nrmrSlj+ogSLp45HL+v5XHvkXnr+csbq8jJ8HPClAGs3lHL6NI8Pn/ISPKz0jKVgDF7tfrqIB+9up6qXQ0Mn9KHsk011OxqYNyMAQybnJjSYMaJ9RiZloGfMcaY1GSBX/fY8dEYY/YeVs7BE5q/mPBrc9wavyY+H/6TDiew7/i4PIdWlxN6+X4imz/BN2gsgWM/j+SXdP7AvdT8FfexdN3jZAbymTHhGkYMOCLZXYpaMBLm9ytf5pXtSxmYXcS1Y45jn6IhnT+wl/nfho38a61beH3JyBGcOiTxUzJqQxF+u2QLs7dXMyI/i29MGhi30b93N4a4/6Mg1UEozIQv7JfJgYNTf9TPmN5m9qqd/PSZJWyprOesaUM4ekIp1z38IVsr61EFBURgVN88KuuDTB5cxC1nTmFE3zTL7rfjE3jmm7B1EYw9Dk6+HbLbrmdoTDop31rLGw8tY+uaKkRA/IAKDbUhAhk+DjhpBAecPDLZ3TSdSIsRv8j2MoL3/Kfd+zOuuwxfZka793dV42O/RNd8tPu2jNiXzHO/FXO76WjFxud5dcH3d9/2SYALj36M/JwBSexV9O5e8yZ/W/Pm7tslGbk8PuurZPlT59rJR+XlfGVuywy3d82cweSi+K69a+3Xi7fw+Lpdu28Pzc3kgcNHxzxNemNVhG+90tBim0/gV8dm0T+FSzrs7WzEr3t6YsSvuiHEwbe9TFXDp0kdMvxCMNzx+cO+Q4p48muHJbRvPe4Ps2D7kk9vT78Uzvx98vpjTA956Jb32LmxjUSHzZzy5f0YtV+/HurR3inWY2RanB1F1m7q8H5dvSEuz6PrFrW8vX5xO3uaTTtbnohENMSWsgXJ6UwczNu1psXtXcFaVtZsS05novRB2a49tr1fVpbw531/Z8sDxYbaRrbGIdPfkh17Zg6NKCzZued2Y0z0Plpf3iLoAzoN+gAWbqygsj6NMvxVb2sZ9AGsfj05fTGmB9VVNXYa9AFsWJL4cwoTm7QI/HwDO766IDEWb9/dTv+RrW6PiEu76ahf0Z6ZVPsVpW4h34kFg1rczvFlMCK3b5J6E53xBQV7bJtQuOe2uD9vYXaL232y/PSLQ8KHkcVtf32Name7MSY64wcWkOlv+Xfl68KA/ci+uRSkU3KX3L5QOLTltkFTk9MXY3pQdl4GBX2yO92vdETizylMbNLiDMk3dCC+A6a4fO6tyKyp+PJy4vI8gROuQPq5VNbSdyiBE66MS7vpaOKwMxk/9DRE/GQG8jl48vUU549MdreidvmIwzikzxgE6JeZz/cnnU5eIP5ZKhPpkNJ+XDxyOJk+H1k+H5eOGsHMvokPXr88oT9TS1xK94E5Gdy83xACXTlr7MTYEh/nT/Tj95oKCFw8JcDwwrT4WjOm1+iXn8XPz9uPvnmZiMCJUwZw2zn7khXY828tP8utsR3ZN5dfXTgtvTJf+/xw7l+hZKS7PewgOOlnSe2SMT1BfMJxl0+msF+2d9tt9/k//fueMGsg42fGZ6DFJE5arPFrouEwWt+I5GQRqahGivLx+eJ/EqiNdUhmfILJdBcK1+OTAD5felz1rQs3kukL4JfUDS4aI24qZGYC/jY6UhuKkOOXuJ8IhiJKfUjJDkhcAkqTXLbGr3t6MqtnOKI0hiLkZPp3366oa6QgO4OtlfX0zc0kJytAdUOIvEx/egV9zalCYzVk2eiG2buoKsGGMIEMH5Gw4g/4aKgLEsj0E8iwxGo9wbJ6ekJLVhJ+cx7U1EHfYnzDB+MrLUEnjkb88fkwRmorCb10L7pjA77xMwkcfDaSQsk9mqvctZSdm98hp2AY1buWU1G2iIHDT2DI6LPi+jwB/6dTAxpDNazc+DyNoRrGDD4hrole6kO1vLXteVZXLSHbn8fUPrPYr89BcWu/SY4/M+5ttqci2MALW9YS0QgnDBxJSWbn0yy6oicCvqUVddy3YgfZfphcnEtDWDlyQAHD8+M/ShrwCfmZaXqCmYI0GCb88TaoC+KbVIqvxC6SpbId1Q08+v4GFm+qYGTfPM47YBgrtlXxm5c+YWdtI/sOKeJbJ4xn5Y5almyuZPLgQlZvryE708+Z0wZTmB17YrWkaayFjx+F2p0w5exPR/rKVsHiJyC/P+xzLmR4n/Hlz8OmBTDqCBhxcLJ6bRIg0thI1bPPEty8hYITjidrdHzqQ/dWK97fypJ3NpOVl0FuYSZ1lY30GZxLTkEWNeUNjNinL+GQsm7RToINIbLyMhi7f39KBqZZFl+gcsd2lr3zBpk5uUw67Egyc3KT3aWYpMWIX+i1OYTf+7DN+3yjh5Fx/kkx90Eb62j801ch3Gyheukwsi69Nea2e9q2ja+x8J0bgT2TYAwedSaTZtwU9+cMhxt5/O3L2FW1EoDMQAFnHXYvRXnDYm47FAly0/uXsa5mRYvtF476EmePuCzm9pOhMtjIZXOeZWt9LQB9M3O4/6CT4hb8JdK8HdVcP2/9HtszRLhz5nD2LUntL03TPlWl8d756KYqtyHDR+YXpuPrn9/lNmzEr3sSOeK3vaqBk3/zBjuqG3dvayubp+DKObQ2ujSPZ75+ONmpOBIQCcPfjoNNXibkjDy48kV3DnDPSRCqc9uHzYLLn4OXfghv3/np40+7E2Z8oYc7bRJl3RVXUvP22wBIRgbD77+P3P33T3KvEuPdx1fwwfPruv04X0A46xvTGTS2OP6dSpJdmzfywE3X01DrEtv0Gz6SS376a/yB5F3Q2uuzeqoq4Xkft3t/ZNV6IttjzzIU/ujVlkEfwPb1RMo6zijaG61b9gBtBX0Am9c+k5DnXL/93d1BH0BjqIql656IS9sfls3eI+gDeGr9A3FpPxle2bpud9AHsLOxjue3rEleh7rhr59sb3N7UJVH11rGr3QWWVP+adAHEIwQfn9z8jpkYvL4/A0tgj5oO5tne5ePV22v4cXFWxPQsx6w5s1Pgz6AYA3MvRvm/PXToA9g/WxY8za8d1fLx7/z257pp0m4+qVLdwd9ABoMUvb3fySxR4mjqnz48p4XbrsiElI+fCU+WfR7i49efn530AewY90aVi/4oINH9H4pH/h1STzWGbS7pisFp5h18PuQHnw98Vv/0XY7KfjO7NbWryZVXk9H/fSlzKswUbG3N63E43jgS9l1fm19Cfva/oyLtPGlnaqv2+yhjc+wpPN68hj+ZlM4/UGXpfra5ZR/i0QE/0H7tXu/b8xwfP1KYn4e/75HQaDV+q7+o/D1GdTm/r3ZiAmXINL21JtBo05PyHMO638IfQrH7b6dlVHIxOFnxaXtqX1mMTJ//B7bzxj+ubi0nwzH9B/O4OxP58r3z8rlhIEjk9ehbrhmfGmb2zN9wnkj+/Rwb0xP8o0oRoY0S3iR6cc/Y3DyOmRicvb+QxhQ0HJdbuuyDtD+eeK4/vkcO6l/IrqWeCMPh6EHfno7swAOvBJmXuOmfTYZcRiMOARmfbnl4w/7Ro900yRe9oQJ5B15xO7bkpVFyaWXJrFHiSMiTDsuuiU4/gwfU4+JfflObzL1uJPJzvt0qULpyNGMnJraU3zTYo0fQHjFWkKvz4HqWujXB9/Iwfj6FOMbPwpp40AVjUhdDeFX7ieyfR2+iQcTmHka4kvBtQtAdcUKdmx+h9yCEVSXf0JF2UIGDj+JQSNOTthzBkN1rNr8EsFQDaMHHUdudsf1F7ujIVzPu9teZHX1MrL9uUztM4vJxan9x1kVbOTlreuIoBw3YDiFGalTPuKTyjr+vnInWT7YpySXurByxIAChuT2XHIckxwaihBZvB2tC+Kf2A8p6t66VFvj1z2Jzuq5q6aRx+dvYMnmKkb0zeXs/YeyZnsNd760nB3VDUwdXswNx09gxfZqlmyuZN/BRazcXk1Opp/T9htMXirX8QvWw+L/uuQuk8+EIq+GX/k6WPw/l9xl8pnQVNpn5StecpcjYegByeq1SQANBql68UWX3OX448gcPjzZXUqo1R9uZ8k7m8nOzyC3IJPaykb6DM4jpyCDmvJGhk/pSzgUYf2SnQQbImTnZjB6ej+KStNvDX/1rjKWv/smmTm5TDjkcDKykptr4f/ZO+swSaqr/3+qqr2nZ3rcZ2dm3V2AhWVZ3IMGkhBeJIS4kBCXN/LGk1+EQIgBwR2C6y6yyyrrOrPj7u3dJb8/em12pnukaqSH/jwPD1tVt+453dVTdU/dc79H7zNyRAM/QRC+CtxCdAnATuB/gHzgESAT2AJ8StO0cMxOGNqDTQuF0QQB1euDYBgpP9vQaVkt5AeT5ZiapxYOgGhCGMOFnnrRNJWAvwlNU7DZspFMxv2oI3KAsOzFbklH1RQ0TcFsMv7G0BZsxmVKxWoaOQXB7kgAl8mWwKlLEw9/RCOsaGiahlkSSLEkfBLDR56PSuA3Fs9HPciKii+skGaPPuu8QZmGLj8ZTitZLiuaptHlj5DutOAPy3T6IxS6J5iiq6pCZxVklBmzhCRJknGOHJbpaPKTXeyipy2AqqiIoogz3YooiYQDMjanmaAvqoFhtkpI/dT3TGIc47acgyAIhcCXgFmapgUEQXgM+DhwIfB7TdMeEQThbuBm4K967WmygvziWtS9Fb32K4B03mmYFszS1384gPziX1ErPwSbE+n0a9Bq9qAe2AhmG6bTrkRaeK4uG2NBZ+s2Plz3ZVQ1dGxfftmlzFryXV39aprKuu0/40D9fwEQBRMgoKEyvehiTpt7J2KMdNOh0OCr5gfbbsUrdwNweu6FfH7mD3X3eyJ1gU6+t/tp9nubyLel8cMZlzLfPbHSGRKNkKzx+40hdrT2fnFV7hb4zqlWHObkoCzJ+GW0n496eXV3E999ZhetnhDLyzJwO8y8svu4aEuB24ZFEqlq95NqN+EJyGhAusPMs184jZKMCSDxvv1RePbzoEZAssCV/4BZl461V0mSjBhvPbiXPe/EFucyW0UiIRWTRUQOq0f2Say8ZiqzTkum+I9XRjosNwF2QRBMgANoBM4Cnjhy/D7gciMMKdv29An6jh179X30zmwqm16IBn0AQR/K6/eh7v/gSCHXAPJbD6J1JpZ6maZp7Fz/rV5BH0Dj4edoa3wvxlmDo7Lx9WNBH4CqyahaBE1T2Ff7LIfqX9HV/1H+sOc7x4I+gHeaX2RXp7Fvv39/8FX2e5sAaAx287/7ntf9e0qij1cq5T5BH0Bll8YzByL9nJEkybhj1J6PevCHZb7++HZaPdHnxAeHO3oFfQANXUGq2qMqxD1Hgj6ATn+Ezz+4bTTdHRlUFZ77YjToA1DC8PRt0ed/kiQTkKAvHDfoA4iEosHe0aAvuk9h7YP78XaGYp2WZIwZscBP07R64DdADdEHWjfR1JUuTdPkI83qgML+zhcE4TOCIGwWBGFza2v/8vC97LW0x3MGwvoGg1pL9Uk7Ti6HoKG2Dr3uyViiyH4ioa5+j3m7Durqu70n/vntPQd09X+UpkBf2eGKnt2G9H2UA96TBjnBLrxy8qY2llT1xB5wVXT2X6okSZLxwmg/H/VQ1xnAE5QHbhiD6nbfwI3GO4FOUE6650f80f+SJJmAtFR7Bm4UA1XV6Gj0GuhNEiMZscBPEIR04DKgDCgAnMCgK6lrmvY3TdOWaJq2JDu7f5XAExFL+30+RpEkBKs+UQlh0pzeO05W+JTMiEXTddkYbUxmJ/aU/lMWM3KX6eq7MCv++UVZy3X1f5RpqX0VXRdknmJI30dZll7Wa3umKx+XefwXUp/IzM2OfetamJtcX5BkfDPaz0c9lGc5KRiiQM+JLJqkX1V7zHFmgs190r5ssEyAFNYkSfqhcPrw/27NNom8sjQDvUliJCM5QjobOKxpWqumaRHgKeA0wH0ktQWgCKg3wpg0eyrSGUshxdG7fI5JwnT9xfr7X3AO0vJLITULoWAq5iu/ibTyakjLQcgrx3z5VxEcqbrtjDYLz/hTr+BPEK1MX/hNUjP0rYkszFrKKbPvwGpORRRMOG05pDlLSHNO4tTZd1CcY0xw9pXZP2eqaw6SIGGXnNw45WtM6qe0gx6+OvUcLsqbR47VxWmZU/jprI8Z2n+SoXNmicRlUyWsJ5TVMomwepLEhVMSV2gpyUeGUX0+6sEkifz900s5bUomBWk2bjy1lG9dMB3TkTpmAnD2jGzOn51LXqqNeUWpOK0SkiiwoNjN3Z+cIOqWNzwLroJoobK0Irjh+bH2KEmSEUOSRM66YQai1P96eZNFJKvIidNtwZ1nj4q6mEUyi1K4+PPzsNgTWM13gjNiqp6CICwH/gksBQLAv4HNwBnAkycsXt+hadpd8foaLdWyJEmSJEkytnwUVD2Tz8ckSZIkSTIcxq2qp6ZpHwiC8ASwFZCBbcDfgBeARwRB+OmRff/QbUtWkN/agLq3EsJhUDUQBcQZ5ZgvXq23++N2wgHkzS+iVWxDk8yI7hzQVIS8cqQF5xwr8TDekSM+dm/8MZ0tmzCZXcxc+l3MZhf1lc8gShaKp1yDw6W/Rk1jxzYO1D6PxZzKnNJrcTlGvtj97s7NrG16kVSLmwsKryXTljviNpP0ZX93gLv3N3OgJ0SqWeL8wjQaAxGcJomrJqWTPwL1/DoDGi9VynSHNE4vlpiTnZg1NicCmi+M/EEdWk8IaXYO0tTMsXZpXDGaz0ejeHlXI7999QAa8LWzp3HhvOj9fO2BVv713mF213cTiCgUuu384JJZnDZlZFNQR42WvbDxXtCUaAH3vLlj7VGSUSawazddjz6KYDaT/slPYi0vG/ikBEZVVN58YB/1BzrJyE/h7Jtm0VbjYf8HTThcFjIKnLz/9CECngiiKKChoalgtZsom5/FgrNLyCxMGdhQAtDRUM+2l59HiYSZd/YF5E2eOtYu6WZCFHAPP/4yWmVfkQ8AcVop5o+dY4gf4Sd+iVbTv3CIOPt0zOfdaoidkWbDK9fj6zlJAVUwwRFNAZMllVPOfxyL1T1sG80dO3h+w2fRNAUAhzWba858HPMI1tnb3bmZn27/IhpRcY8saz6/X/4YZjFZNHw0qfaGuPHdSpQYxzOsEg+dPhmHybjATFY17ngjRIs/ej8TgG+dYmFuTjL4G200TSP8ty1orcdFPcxXzUaakTWo8z8KM35GMhozfpurO7jqr+t77Xv0M8vxhhRuvq+vbQF44vZTWDwpY0T9GnG66+EvyyF8ROjC7IDb34OM8rH1K8moEaqo4PAVV6KFouI+Ymoqk198AVPW4O5nicjTv91Kw8GuY9tWh4lQQIZBhgtmq8THf7CM1MzEruPp7+nmX1+5jaAvKlQjmc188v/+QFbxpDH1S+8zMuFVEDRZjhn0AagVxihtap6OmEEfgLr3fTRl+Mpno0XQ39w36INjQR+AHO6hrWGdLjsH6186FvQB+EOt1LVu0NXnQKxtevFY0AfQFmo0vLRDkoF5o7EnZtAH0BFS2NBqrNLf3jb1WNAH0efT2tp4XiQZKbQGT6+gD0DZ3jRG3iQxgr++1feZcdfbFTyxpa7f9hrw2Ob+jyUUe587HvRBVMVz11Nj50+SUafnhReOBX0Aak8PntdfH0OPRp6GQ129tkP+wQd9EC3pULFlZNWGR4NDmzYcC/oAlEiEfe+tHUOPjCHhAz9EEUxxUiyNmlWw2ECMY8fmBHH8zy5IJge91W/6x6xjtg/AZul7vk1nnwOR2o/NVPMEUJRLMNIsA/8duAfRZiikWvv+plOTE71jg72vuI7gSAruJDLZLmu/+zKcsf/IslL6npNwOPqZ1XFO3JmeJH2R0vvOWve3byIhmfSHBnZX4t/zHal9lUntrsRXK034wE8QRaRVsWc8pTWnGmPH6kA6NYaaoyBiOv1aBGHggGqsMVtclEy7vtc+yeTE4TqeupKRs4zMPH3f26zSq0h1FB3bLs07k/yMhbr6HIgLCq8ly3p8HeHKnPOZnDpzRG0m6csFhWmUnjTQP/EvY2VOCgszHIbanJQmckbx8WAy0y5w4eTEWHM70RAz7EhLTyivk2JBOrX/sjFJEoNvXTAD5wkvaxwWie9cMJPbzphMTj9BYYbTwo2nlo6ihyPErEuh5AQF6oJFMPeasfMnyaiT9rGPYZ15fBzhWL4c11nGaUeMR5ZeVNpru2RuJinpx//OhQEih7zyVKYsyRkBz0aX8kVLKZm74Nh2dkkpc1afPXYOGcSEWOMHoHZ2o+w4EJ2S7/aBSUI6awVSmrELTNXORtS6/QgmC0J2CVpXM2JuKYIrscQLPF0HqTnwECnuaZRM/TiaptDVuhVRsuLOmm+IDUWN0NC+BavZRY57tiF9DkREDbOrczOp5vRk0DeGKJrG5jYfG9q8FNjNXFKUzo4uPykmiVnukcv7P9yl0h3SmJUlYokhQ51kdFCbvWg9IcRSN4J58DO8yTV+Q2O0VD1lReX+DdVomsanTynFJEVHf8GIwruH2qho8VLX4WdBiZtL5hdiMWDWYFygaVD9flTcZdLKaJZRko8UmqLg37gRwWLBvmhRQrzk10tno4/9G5somZVBwdR05IhC/f4uHKkW0vMd7FpXT8W2FjILUrDYRZoqeiibn03OpFQKprgRxInxHWmaRsP+vciRMMWz5yKOg8w+vc/IiRP4tXehNbej+QOoXd3gTkNAQ8zKQIpX3H0IaP4etK5m1IAXrb0esWwegqqCxYaYnmeIjV72NJVQ214kWzpmV4Hh/Y8G4YiXDk8FGa7JWMyJr/Kkahp7ehpoC3uY4conzzYy0/6qprHf04HbbCXfPnLfm6Jp7OvpIctiJddubFH6HR1+GgNhzshNxT6Cg8CqLhWLBAWu5IBsIpAM/IbGaAR+3YEImw63YzNLLC3LwBuUeXNfC9NzU4io4AvJFKbbSbGaeHV3E2fNyKEw3dhZ/XFN857o/93F0LQLcmfBCD0bkiQZTVRFpWpnO4qs0F7nI6MwhabKbsJBGVe6lRmnFiCHFdCYMEqe451xW85htNA0Dfnp11APVvc9BqiAnJ6G5ZarEHS8qVN2vIX85v2gHheMUN997Ni/jVb1lP3tNLzyBcJdhwEB95zryVr6RcP6Hw1qWzfwxtZvE5H9mCUHaxb9jOIcY1Jvx4LOsI/Pffgfqvztx/bdOOk0bitbZaidjlCAL217i8O+bgTg4yUz+MJU49NkW4JBvrLlQ2r9fkTgU2Wl3DJFv1qdrGrctv4wBz3RBfG/2NXIb5eUsCjTqbvvEwnKGr9YH+ZAR1TQ57Qiic8tMn8k3sYmSTJavLyriS8+tJWIGn1J7DBL+CPxhZO+/+xuPr96Mt84b8ZouDh2KBF45BNw8JXotmgCVQazE678O8y4cGz9S5JEBz1tAR792UbCgdh/75tfPD72LpmdwYW3zzNkjWCSkSPhr45aWdtv0NeLzm7UD/cO24YWCSGvfbhX0NfHj93voNYfGLaNk+na9eCRoA9Ai253D/A5xxnrd/+OiOwHIKL4eX/P78bYI308WrepV9AH8O/q92gIdBlq5+GafRz2dQPRlxcP1+yj6si2kTxYVU2tP3p9VOD+w1U0BAK6+32rqedY0AegaPDrXY26++1jp1o5FvQBvFensLtNjXNGkiRJhoKmafzg2V3Hgj5gwKDvKHevrURWJvjf455njwd9EA36ACI+eOnOsfEpSRKDeP+pQ3GDvpOp2d3BoS0tI+hREiNI+MCPHu/AbYimgg6boA8iwQGbaZ72AdsMFtnXPKh94xlvoLeEuy+QWP6fTHOop9/9LTH2D5eWkL+v7WDffbrtBEO9tjWg9aR9w6ExEOmzrzNsfGmF9kDfNPU2//hPXU+SJFGQVY1Wz/DuCYqqERhkkJiw9NTHP6ZO8MA3yYTG0z70F8GejoHHyknGloQP/MTJJYMq2SAtGr64iODKQCiYGr+R1YE4ae6wbZxMSllv5SDJkY09d4Fh/Y8GkwvO6bVdftJ2onF2zqw++3KtqcxJNWYN6VHW5PYuDpppsbPAbbxC1lm5vfvMt9mYnZaqu9/Veal9CoackevS3e/JLC+Qetmxm2Bh7tgvvE6SZKJglkQumDu89esFbhsuW+JLusdlxsUgxShbMftjSSGYJAnNzJVDG9uIJoHJC7NHyJskRjEhxF3UxlbktzagNbdDRI6qcEH0puu0Y1pzCtL0Ml0+aAEPyoZnUWr3QndrNKXDkYaQmomQmoW05CLEbGMlyz2Vr+GpeAnJnkn6vBuwpCaWJLqshNhecT/NnTvITZ/L/Mk3YJKMFRAZbd5q3ce/qt6jK+Jnblohny8/iwK723A7bzTX8FLjYTIsVj5VOptih/GBE8ArjU283thMts3KJ8smUWA3RnFzY5uXP+5txhNROD3XxVdm5mEaAZWv7S0Krx+WsZoELp5sotSdHGglOklxl6Ex0uIuvpDMb17dx8u7mrGaRK5eXMTO+m42VXViMQnYzSbCisq03BTaPGFqOvxMyUnh7k8tIislse/3g6JmA2z4a3RMYM+A7hooXAKnfw0sxq5rTpJktNn6ShXb36wj6I2gqRoIoB2dyBYgNdNGer4Tk0lk3lnFFEx1j6W7HwmSqp5JkiRJkmTCkAz8hkby+ZgkSZIkHx0+8qqeAJFD1ahPv947nz7FASkORIcdaeVixHx908+aqqBseBa1Ymt0OxIGfzcoEQRXFtL5n0EqmKLLxslEvE20bvgtweYPEUQzqdMuIWPhrQiicZdN0xSq9t1Pa91b2FMKmTzndhyuEsP6P5EDdS+wt/opzCYHC6feZEhB95fqHuXxw/cSVPxYJTtZ1ly6Ix0ICMxLX8b1k79IujVLlw1FU3mgZj1vte6j0J7O7WVnUuzI0O37R4EKT5C/HWhhb3cQSYBTslK4bXoOaRbjfsN1PSqP7Y3QHtBYUShx8RRTUtlzDFFVFfmx3ajVXWCRkGbnoDZ4EMwi0mmTkErdY+1ikiEQCCv86pV9PPthPd6ggqJpCAKkWCTkI6UcJAFEUUAUBTIcFtwOM+fPyefzq6cgJXI9r8bt8NbPwdsM86+D5beNtUdJkow4kbDCU7/eQnudl1hzQyazwFXfXsqHr9dyeHsrAgJlC7I47aqpWO0TIrTohSLLbHjyYSq2biKzsJjTr/s0qdmJWaQ+4Wf8tFCY8B/ui9+B1YLl9usQrJZh+yCvfxpl/dOxG0hmLJ/9M4LVuOLUNc9+inDHwV770ufdSObizxpmo2rf/VTs/MuxbbuzkFMueBxBMHatVG3Lel7e9JVj25Jo5eOrn8ZhG37h+92dW/jJ9s/FbTM9dR4/XnTvsG0APFCznrsq3zq2XWhL57Hln0VMBhdxCSkq1647REeot8DDqdkp/GKxMWnLsqrx5deCdJ6wnvzGuWbOLZ94D55EIfzUHtQ9rf0flASsn1uGkBY7BTA54zc0RnrG7ztP7+ShD2qGde43zpvO51cb+0J01Ah54Q9zINB5fN/ld8OC68bOpyRJRoEnfrWZ5sqBResE8YS0zyNMXpTD+Z+ZM0KejR3vPnI/Hzx9vIRbdkkpN/z6z2Pii95nZMIviFEODaLEQSiMWqNPTl6t2DaAIxHU+n26bJxIxNvUJ+gD8NW+Y5gNgLaG3v0FfPV4uysMtQFQ3dzbjqKGqG/7QFef7za/PGCb/T078ET0lUJ4p633dagPdlLpizGwTXKMfd3BPkEfwPpWL4pBL5wqu9ReQR/AlqYJriQ4zlEPd8Y+qGgolXGOJxl3vL5n+GrMr+k4d8yp3dA76APY/+LY+JIkySjSWuUZVLuTgz6Aqh1tBnszPqjY3Hu82lpTRXdLYt7fEj7wE3IHl8YnZKTps5M+sLKZkJ6vy8aJSLZ0BHNfQQ9LWqlhNgAcrt4KkqJkxeYw7nMcxZ0yqZ99pbr6nJQygNIq4LZk4pD0LbAvOSmt0yqayLXqV7+c6BQ6zEj9TIoWOixIBs2W5jrEPjYKUpIzsWOJkBpD5fAIYpZjlDxJYgTl2cO/f07OTjHQk1EmcwqcrE+cNW1MXEmSZDSxpgw/Y8adNzHv7xkFRb22rU4nDrd7bJzRScIHflJWOkJZUZwGItLpixEz3brsmFZejZB5RNq2n0GruORCxEEEh4NFNFnJPe1bCCdIRZtchWQuvt0wGwDls28lJS0aQEkmB9MX3oHZYryC5IySyyjOOQ0AQZCYV/4pst19yyMMhTUFlzPZdXIfx6+Nw5TCrdO+g6RzTeRnSs9gqjOay+2QLNwx9Txc5o+AWp1OsmxmPj89F/MJa3zSzCLfmG3c30maTeBTc8xYjmQml7sFLp8+wSXkxznmy2eC+YRHS8qR6yGAtLwQsVjfS7gko8sPL5lNXurQ73cz8lx8/dwEDpTSS+HsHx0v11ByKpz6hbH0KEmSUeG8W+YgDCI6mLu6AKvj+PjK5jRz5vXTR9CzseP06288FvxZHU7OvuXzmC3xX3KOVxJ+jd9RVK8PZc8hVJMZyWFFml4eLe5utSDYjLk4mqZBVwukuMHfgyZK0N2CkFWMYBsZ2WZVDhLurkU0WTGnFo+YaIXfW4fFloHJNLJva7yBZkySDZvFuMFfk7+GtmALWbY83NZMOoItAGTZ8rDEqrE0DOoCnWSYnThMw18r+lHEJyt0BGUQIM9u6RUIGoU/ouEJa+Q6E/5d1oRBqepEyLAjptrQekJgEhEcAwflyTV+Q2M0VD0VVaO63UdE0fAGI9itEjaTRJrdzI66bvLTbFhMIl3+MNPzUmnzhpiUOUFKGQS6INgN6X2zVpIkmaioqkbVjlacbiu+7hCqCrmlLvaub0QAFpwzCbNZQlFUupv9ALhzHYjSxH0Ga5pGV3MjKekZmK1j9/I/qep5FElCbe+EvRUoERVFehvsNsT5MzGtmIdgMuajaj2taPX7EcsXINhdaJ1NqIe2IJbNR3Aa/yZbNNmwZQ6c0jhUPF0HqNr3H4K+OtJzljJp+vUjEvTtqHiQiobXSHMWM7XoQgRBwBdspSTnNOxW/cqY3nA3/617mMM9e0k1ZzDDPZ8z8i7SreR5Mls6q3modgMuk43PlK0akdp9R2kO+tjY0USJI5X57pErhtoZDrO+rZ0sq4UlGRkjIlYTUlRerOvm/RYPc9x2Pjk5iz7pUzqRVY29bSoBWcNlEXCYEy/VU1U0PJUqmqLhKpfwN6q0bY1gcgjknmrG4kq8h6lUmg6A2hlArepCzHEOKvBLMv5o6gnyyMYaDrf5qG730uKJYBJgSraT0mwXgYhCWJbZ3eDBZTdx3uw8ZuansXp6NqZEHwja3dH/jnL4HeisgslroGUP1G0EmxumXwBWFxx4BVx5UL46WcB9ghA6fBj/pk3Y58zBNktfplKiEAnKdDb72fxiFUG/jCPVjCvDhtlqIr88jf3rm2it8VC9ux1BAFuKiUBPhNyyVM67Zc6EDAAFQSA9r2Cs3dDNhJjxU3u8RP76cOwOHDYst30cwaJv0BF54S7U/RuiGxY7QtF0tMoPo9tmG+ZrvoOYW6rLxmhQe+hxDmz7Ta99omRj+TkPGFrK4al3bqC9Z3+/x8wmJ5esuJvMtOGnArUHW/jSBx9D0eTefYsWfrTgHianGnOD/kvFm/yndkPvffM/waIReAO8paOZO7a/TfhIaZJri6fzpWmLDLdz2Ovlc5u24pWj392ZOdn8ZP5cQ20EZJUb3q2gOXj8+rhMIo+fOQWHyRjVWEXV+Ml7YQ50RL+vDBv85Awb6fbECf5UWaPy0RCBlui9WDSDGundZvLHrTjyE+9BqhxsJ/L4blCjn006fRLmVaVxz0nO+A2NkZ7xe+9QG5/6xwdHL+GQWFqaziOfOSWxSzqcyHNfgq1HVMQFCbQThKQEEUx2iPii2zMvhWsfGH0fkxhKz4svUn/HN46VC8u5804y/+fGsXVqhOlpC/DozzYRDsgDN+4H0SRw+59XG+xVkqN85FU9AZR3Bnjo+YOo+w/rsqG21x8P+gDCgeNBH0AkiLL5BV02RgNN06jcdXef/aoSpPbgo4bZCYZ7YgZ9ABHZx47KB3XZeKjyz32CPoCIGua5WmMeuEElwsN1G/vs/2PFG4b0fzL3V+0+FvQBPFF3gK5wyHA7j1TXHgv6AN5uaeWQx2uojbebenoFfQAeWeW/tV2G2djRoh4L+gA6gvBG9fAeVmNFT4VyLOiDvkEfQOM74VH0yDjkd6o5MWJQ1teihZOqq4nEb1/dP6ygD2BTVSfrDk4QBeSuWth6//Ft7aTfsaYeD/oA9j4HTbtGx7ckI0brn//Sq0Z02113ocmJ9YwZKjvX1g876IPoy8y97+tT0k8yckyIwE8L9zNSOpnIINrEPX8Qg+/BtBlzNFSl/0GkogQMs6KqAw9UIzrtBRV/zGMhgz6Loqmo/WgWh/obnRtAUO09mFA0jYhq/EA5qPTts799umyo/Wg9Az65//3DIaT0HZGGEuyZrA7C3xH6uY08kZN+U4rKsKOIJGOC/+RrOEQCEyXQl4PAEH+7kdjPqCSJgRroPZbQQqFegeBERO6nDNNQ8XsSYTz80WRCBH6mUxfGbyBJiDPKddkQcssQ8iefsEOAzKJe2+L8NbpsjAaCIFI05ar+jlBY/jHD7DhsWXHX8AmIzJp0hS4bV5XeGvPYOQX9fcah4zRZWZXVV6XqhpJTDen/ZK4o6r2e84zsIrJtxq+9vLyosFdJhRmpLmanGVuiYnVeKvaTai2YBLik2G2YjQW5EtmO4zasEqwqMSaNdLRImyxhOlEHo5+suJylibkcW1pS2GtbnJOLYEvMz/JR5daVw392FmfYOWtGjoHejCFZU6FsVfw2J0oh5i+AoqUj6lKSkSfjE9f32nZfdRWCZWILvM1aWYCgMz170blJMaTxyoRY4weg1jcTef4t6D6h8KQgQGEOlkvOQkjVX09ICwdQdq0FTwfitOUImYUou9ZBTyvitGWIBcaLsIwEmqZRf/hZavY9QCTcjTNtMtMXfh2X21jpbVkJ8drmb9LctQubOZWpRRciimZC4W7K89eQkz5Ht4393dv554Hf0BJowCbZKHNN57JJn2Z62nwDPkEUWVW5r+Y9nm/cjk00c3v5mazKHjnJ4i0dTbzTVs8kRyoXFZRjEUcmkNnX3cMbzc1kWq1cUliA0yABpBNpDkT4094mdncHKHFYuGNOPsVOYyWQu0Mab1XLBCJwRolEYQIKoUS8Gh27ZDQF3DNFOvcodO1VkCyQd4aF1LLECmZPRDnUjlrZiZDtRJqXizDAov/kGr+hMRqqnm/ta+GvayuoavPR5Q8TUTQEIMUmkpViQ9XAH5bp8kcwiQJzi9ycMS2ba5cWk5WSmJLn/RL2w7b/HBF3WR1N5ax6Jyr+Mv86cGTCrifBlQ+LbgBbst7rRMDz+uv4PtiIfc5sUi+5BOEjINrTXu/l/acraDzYhSIrSGYRq8OMzWkmPc+JZBFpONCBpz2EIAgIAqiahsNl4fKvLsSdO0FUfcchep+REybwS5IkSZIkiU8y8BsayedjkiRJknx0SJZzACKvvou6bW/sBplurLdcrduO2tlE5IlfgKej9wFHGqYzrkWatVK3jdHA213B9ne/TtDfSDSv7MTgX6B8zmcpm3mjoTY37vsLOysfQtVknLYc1iz6ObnpxqhI+mUvP9h6K3X+yl77S1Om85VZPyPPUWyIHZ8c4tOb/0F9sAuAYnsG9y+5GZtknET9K42HuadyB95IhMsKJ3P7lAUjUmZhpGn0h/nFrkZ2dvpJMYl0RY6vifhYsZuvzs7XbeNwl8rftoWo6Tn+C56TJfK15RZspsT7zk4k0KJS/3qYYJtGyiSRonMsmByJ85mUwx1EntoLARnMIqZzp2BaqP+aJxl9vv3UDh7eWBvzuEkUkPtZtykK8MRnT2HRJP1le8YNB16Bl78NPQ2QWQ5dNdFSDmt+CPP0jzGSjC8iTU00fuc7+D44IvCmqiCKpF12GXk//AGidQLNZp9AT1uA1/65m6bKniGfa3eZufzri8jIm5gzfpXbNvH2fX/H09HGzNNWcdZNt2MyJ1aZooSfr1Y7u+MHfQDtXYRfe0+3rcgzv+sb9AH4u5FfuRe1s0m3jdFg+3t3HAn6oO9idY3KXX/F7439oB8q1c3r2F5xP+oRBU5fsIVXN9+BOhhVi0Hwpz0/6BP0AVR59/OXvT82xAbAj/Y+eyzoA6gNdPDzfcYpudYHvPx0zwc0B/34lAgP1ezjpUZ9arRjxS93NbKtw4+s0SvoA3i6tosDPUFd/auaxv/bFKa6p/cveFebyhN7E1UJJYqmadS8ECbQrKEp4KlUaVybOJ9JiyhEHtsdDfoAIiryCwdQO40Tj0oyOmyv7Yob9AH9Bn0Q1fC57m8fjIRbY4O/Ax6/EToqQA5A824IeaC7Fp6+DTqrx9rDJAbT+MMf4nt/PShK9D9NA0Wh+6mnaL/372Pt3ojx5v17hxX0AQQ8EV7483aDPRofBH1env/9L+hsrEcOhdj55qtsfv6psXZryCR84KccHNzNVqus02VH0zSIF9hpGlrjIV02RoNI2EPQ1zBgu67WDw2z2dSxo8++YLgLT2BgPwZDpSd24H/QsxOj0pl3dtf32fdhV40hfQPs7m5DPSkQ39GdmFLou7riD/J3dupTu+sOQYu//+u6qy2xFddkP4S7en82X0PifCat1Q+Rvv5q9Z5+WicZz7y1r1nX+SFFNez+O+Y07Yyt0qkpULdpdP1JMuIEtm6Lc2zrKHoyujRWdOs639Oh78XueKW1qhI51FuttGH/njHyZvgkfOAnTRlcwXGhrHDgRvHOFwRw58Zr0Vv1c5xitriwOgZOuXJnGSeO0l9Kp83sxmUvMKT/MldsoZUprtnRa2cAc1L7/obmuo1JIwWYlZqJeJKk49y0LMP6H01mu+1xj88Z4PhApFkhJ0bq4+ysxL6tmRxgSev92RKpeLuQ5QBTX3+FQtcYeJNED2fqVOS0SIJh998xJ29utEB7fwgiFCWXpU407AsWxD62cAA1+QQmrzxN1/kp6TaDPBlfZE8qx3RSem/+tBlj5M3wSZzRRAzEDDfC/AG++Iw0LOfqX39nvvxr4Ezve8DuwnTuzYjpibGGZf5pv8Zqjx3Els++DYdrcAH1YCjNW8W88k8iCFFlQoc1i3OW/ApRNGaJ6Zdm/ZQCR2mf/SXOKXx+5o8MsQHwo1mXkm89fkMssrn53oyLDOu/yOHi27OWkW21Y5dMXFs8nQvz9ZUhGSvunJPP/HQHIpBm7n2buazQzfQ0fYGfKAh8aYmF4pNE82Zlilw9M7Hy7U9GEARKLrJgyxFAAFeZSMGZifOZBIuE+erZcLRsg0nEdOFUxHR91zzJ6LOgOJ1rlhTFbSPFkH0XBXjo1uUj4dbY4MiAq/4J6aUgWiB7Bpgd4CqAy/8a3Z9kQpH/4x/hWL48qhAvitH/SxKpl19O5q23jLV7I8ZZN8wkp3R4L+rsKWYu/sI8gz0aH9hSUrj4y9/EnZuPZDYz+8yzWXrJlWPt1pBJqnomSZIkSZJxQ1LVc2gkn49JkiRJ8tEhqeoJqA0tyG9uQOv2RN/IKCoEgtGFuA4bpivORSqMl6Y5SDt1+1AObUFtOATNVaCp4ExDOvt/ME1OnGl/RQ6yZ/PPaG98F8lkJyN3OXZnPvmlF2N3GpN+CeAPtvPaljtp794PAmSlzSQ/YwEIIlMLL8Sdon9WsSlQx5NV/6AlUE+6NZv2UDOpZjfXl3+BQmep7v6P0hH28XzjdoJKmAvz5qGi8VLTThyShUvy55Nu0a9gddjbzUM1e/mws4UMi43bpyxgQfrIFT9WNY1XG5p4pakJmyRxdUkxizL6mdEeBjs7/bzd1EO9P0xbSKYrrBBSVGak2fn5oiLMI1QHaUuTwp42hbI0kVOLpIRURJ0oqJ0BlO1NCCYRaUE+QsrELno8Ualo9fDdp3ZxoNmDoql4AwrKkWNOi0RxhoMMp5kddd1EFA2LJJBmN3Pe7Dy+uGYqbscEuu6NO2DXE5CSCws/lazT9xHH++57+N55B+v06ThPX0n3M8+gen2kXXYp1vLEzNaBqKbFgU3N7H+/kUhExeo00VTRTcgXFewy20QiYRVUECVwplsJ+WSsDhPLLi5nximJkf32USXhZ/zUlnYi/xpYVcd8y9WIme5h+6Ds/wD5hb/EPG66+ItI05YOu//R5L2Xribo7StKYjKnsvzc/2Bz6A+SNU3lXy+vQlHD/R43SXY+tvI+3CmThm2jOVDPNzZdR1gN9TkmCSZ+vfQhChzD7/8ofjnMJzbdS1MouuDZJprRNI3QEZXSQpub/yy9VVdZh4OeTm7d9CoRrbcoxt+WnMPsEVrn98f9B3i8prfo0ffmzOK8/Dxd/b7b4uG7W+v66MUeJcMi8cxZ03TZ6I8XDkV4cPdxpdjzyiQ+PW8CDToTCLUzQPjvWyB0JERwWbHetgTBNvC7xuSM39AYyRm/mnY/q3/zFsowhwklGXZe/9qZWPpZ85lw1HwA/74I1CMKu3nz4DNroymAST5ydD7yKE0/+tGxbcHpRPP5ov+22yl77FGsU6eOkXf6WP9MBVtfHr5K7YrLy1l8fqlxDiXphd5nZMLfsZR3twyqnbxOn+KW8uFr8fvf8Iyu/kcLX8/hfoM+ADnSQ1PNK4bYOVj/UsygD0BWAuyvfV6XjXVNL/Qb9AEomswbDc/o6v8o77QfPBb0AQTVyLGgD6A+2MV77foUXZ9rqOgT9AH8o3Knrn5jIasqz9T2VSl9qlaf+i3AU9WdMYM+gI6wgjeixGkxPF6p7N3nm9VKTKn5JCOLurP5eNAH4Amh7G8bO4eSDIsHN1YPO+gDqOkI8M7BxFQm7sPmfx4P+gCadkDN+rHzJ8mY0vngf3ptHw36ALRAgK4nnhxtlwxjx5v6ynltf0P/OCLJyJHwgR+DLZxo1pnVahpg5sCUGOILohS/4Kg0wPHBYjGlDNjGpNOWRYqvHGWVjBGTsA1ChMaqU6jGJkr99yv1v18vgiBg7keUwWrA22ubNHB6pTQCKZiWk74qkwjJRM8xoj9Vz4kw6/MRw27Wf/+xGdDHuMDcz/PEPDHVC5MMjGCLP74QbIn72zBZ9N2rJVPyyTueSfgnsbRq6aBSLUyrV+iyY1p2CcRJ5TOt+oSu/kcLu7MAd9biGMeKyJt0gSF2SvNWYTXHlgR2WLOZUXK5Lhtn5l1Mmjmj32N2yck5BVfo6v8op2ZOYabreM56piWFDLPj2Pac1EJWZOgr5XFF0VTSzL0DYRH4/JSRWTsqCQI3nrQGQRIEPlVWqrvv68oyscZQ+gOY7LJiH4Eg4Irppl6B3uXTTDEVB5OMLNL8vGjNjSMIeSmI0xOzNMlHmU+umITz5DcqQ2BJiZtTyjMN9GgMWXE72E54pk09Dwr7f5Ymmfhk3f5ZMB1/4WvKO75EQsrOIv3j146FW4aw7GJ96xNXXD7+S5t9lEn4NX4Aqj+A/O5WtM6uaD0dTYO2LgiFID8b8+XnINr1z2RpPW2oVTtRu5pR92+EsB/yyjGv+R9Ed7bu/kcLTdNoqHyWmgMPYXHkkFt0FiaTg+zCVUix6hQNA0WV2bj3zxxuegtRMFGefxaZqdNQtAiluWdgMQ88KzgQAdnHm43P0eCvYpJzGtW+A7gtmVxUfD2OQcw6DpaIqvBu+0ECSoRVWdPQ0FjbdgCnZGFl5lRMMWbshkJPJMxrTVV80N5IttXBzZPnkGEZWQn8fd09vN7UjMMkcUFBPvl2Y+y1BCN80OqlJ6xQ7QvhV1Sa/RHOyHPxqckj97dS71HZ26ZS5haZnJ7w77USGi0kox5oB0lEnJY56Bm/5Bq/oTHSqp7ekMwfXj/A1upORAEaOv20esNYTSJFGU7mFaVRlG7nxZ1NBMMKqQ4TboeFKxcWctG8AkzSBPo79LXB/pcgJQemnB1VtkjykSVcXY1v/Qas06ZhnzsHz9tvo3p9uNachZSa2MI/rbUeDmxsRlVUbE4TDQc7aazowWSWcOfZ8XQECXllnGkW8srddDT6cKZbWXFZOVlFyZqtI4neZ+SECPwAlEAAZcseNBGErAyEUAQEkMqKEJ2OuOcOBdXTAZ4OxIIphvXZx4YcRAm0Y0opQA17UCM+UBVMKfkIBj1o5IgPX08l4bAHTQnjSp+Bt/sQDlcJTgNr+LV270eRA0SUIAgCJtGKIIjkZYxMnRdPpBtFlQmrIdIsGVgHSAcdDrKq0hTqJs+ahmmEFvZHVIXtXa3MTs3EbnAacUcojCiA2zJywieKprG/209bUMYfUcmym5iSasdtMU5IWNM0drXIdAQ0IirMyZHISxmdgZjXq2K1CpjNxs0oygGVYJuGs0icOEWviV4nrTOIkGZFGEQQkAz8hsZolXNQVY0H1ldRlGFndmEaoYhKTyCML6zgCym0e4NkuWwsLHaT7jRmycC4o6s2Out3oprnifsCXRDxQ6px6thJxhZN04jU1WHKyUG09v1dRxoaEFPT0CJh1J4eBJMJc2HhGHhqLKFghOpdHcjBCFW7Oiiemc6cM4roavbT1eIHNBoO9eDvDqABhdMyEICyednYXRNPVC3k9xHy+0nNOv7iWlUUelpbSM3OQRyhZTn9kSznAISeeR32Hz62rR35D0AFhKmTsFxxrm474ef+H9qhI2IyFhvmT/zY8KLt3qo3aXnv/1DDHkRrGmrIQ/RTgMmZS/6aX2HNnK7LRtW++6nYGVuh1OEqY9k59+la7+cNNPP0uzcQDHf1e9wsOfjY6feR5jQuyPz3wd/ySv0TaEe+L7vk5Kap3+D0PGPSVwF2dNfx3d1P0Rb2kmN18fPZVzA71dib/KtNVfx09wYUNATgi1MXcm3JDN39yqrKz3fv5fWmZkRB4NLCAr46Y5rhQcbBniCf31BFsB9hlQsK0/j2XP2Dol2tMr9YH6G3CYXSNIGfnzlyaysCAY233wjR3q5hMsHipWamTtN/G61/M0zH9qgYiiBB2VUWnAWJP5ugNnmJPL4brTsITjPmy2cilRlTMiTJ6PH01jq++tj2Qbe/ZkkRv7pq/gh6NMoEOuGRT0D1e2Cyw5rvw4Lr4eHroeb96L5Jp0LVO6CEo7OB19wPBpT5STJ2hKuqqP3c5wlXViKmpVHw85/hWrMGAKWri9rPf4HAli0gSaCq0WwzwDZvHsV3/xVTRv9LUcY7m1+q4oNnK3vtO/xhG+sePhjznIMfREWc3mI/U5bmcN7Nc0bUx9Fk47NPsP7xh5AjYYpnz+OyO75Le10tz//+//B2tJOSkcklX/0WBdNmjrWrgyLhczA0r79X0Ndvm4PVqNV9FQyHgtJw4HjQBxAOIr/4V119nowqh44FfQBqqJujQR+A7GumdcNvdNkIBlqo2HlX3DZ+z2FqDz6qy867O38RM+gDiCh+3tz2A102TmRX52Zern/sWNAHEFB8/P3AL/HLXsPs/PLAS7SFo/21hDz86sDLhvV9lF/t24Ry5NWFBtx16EOMmJl/s7mF15qa0YjOyD1dV8/G9g7d/Z7ML3c29Bv0AbxU382Wdl+/x4bCXVtODvqiVHVrbGmU+x4wiJ3bI7S3Rw3LMmz6IEIoqO/aRLzqsaAPQFOg9qXYiriJROTlg9GgD8AXQX7hgCG/5SSjyzee3DGk9o9trmNrTecIeTMGvPf/okEfgByAV78Hb/wkGvQd3VfxRjToAzj0Omz6+9j4msQwmn/1a8KV0QBI7e6m8XvfRwtHr3H73/8eDfoAFOVY0AcQ3LGDtrvvHnV/jUBRVD54rnLghnE4tKmFpsPdAzdMALqaGnnn4fuQI9HrXrt7B1teeIbX//4XvB3tAHg72nn93tiTKeONxA/8unoG1669S5+dhoq++7rbdfV5Mkqg/VjQF4tw1/BrqwAEPLUQV2w/iqdjry47Xd6qAdt4A026bJxIvb//4D+kBmgPtRhmp9rXW5K+ym/sbwAgoPQOXGRNI6joD2aqfX0DrmqfX3e/J1Pjix+0VHn7L8ExFLxxTOxt61sWwyi6u3v/7agqeLz6AplAS9/zZeMvy5igtff+IFpXEF31AZKMCfIwrtmhFuNeuI05rQd6b2sqNO0a2jlJEo5wRe9xn9LZidzZBUCoIn5wFB7g+Hgl0BMZzBBxQDobJ8ZDrKOxrldQD9BeX0dHfW2ffYlCwgd+Qt7ghCLEsiJddsSZp/TdN2m2rj5PxuwqwOKOr4bkLF6py0Zq5mwk08BrHvNKL9RlpzR/9YBtCrOMK3g/P30FktA35S7PXkSho9QwO6dl9S7Ielqm8Ws9822904PSzFZD1vmdkpXVS/VSEgRWZBmfinJ6buyF3QKwLEu/6E5JWuz01LPLRy6DvbCo9y3T4RDIyNCXKusqFfvciR15E2ONnzi1t6KjWJaeLOuQgGQ4h3b/EYDTp04gFdfp5/fetmfAvGvinzPtvJHzJ8mokLK69zjGNmsW5tycI8fOjH/umfGPj1dS0q2Yrfrv0cUzEzPN9WQKp8/G6uw9Jpu8aCnli5f12le+yLjx7EgzIcRdIpV1qE+83CcqB8BkwnTxmUjTy3T7Ie9bj/L2gxAOIBTPxnzZlw0TWzlKxNNA+5a7CHcdxpI+BdnbSLi7BkEykzJpFZmLb0c061s34Ok6wM4N3yfgqab3qx0BUTQzaeanKZ91iy4bqiqzbsfPqGh4DVWL9DomCBJFWcs5d8lvEQ0UR9nesYGnq/5NS7AOQRCZ7JrFdeWfI99h3DrCnkiAuyrfYmdPPfNSi/hc+WpcBtdyagv5+dq2t6nxe8i1OfnV/NOZ5IxdGmMovNnUzOM1tUiCyCdKSzgl2/jBmV9W+N/tDaxv9fb6dWVYJO6ck88pOfoVv/wRlZ++F6LqhGwSAbh+lomLpo5cTU1N09i9U6a6SsGZIrBgkRm3W/9v2FOjUPdKGCUA9lyB0issSObED5C0sIL81mHUqi7E/BRMa8oRnPEX/ifFXYbGaIi7dPlDnPGrt+kJRjMPLCYQEQnJap/JgQyHmd9du4Azp+eMqE+jzvq/wPZHwJUHq78LBQvg/T/DjkfBlQ+zLoWdT0CwCxbdAEtuGmuPk+hEDYdp++Mf8a57B+vUqeR8/WuYC6Jr1DVNo+Nf/6b7v88jmMyoPh9yaytiSgrp132czFtuSViRrrY6D8/+4UOC3t5jN9EUHWZrSowTAckicv5n5lA6Z+K8+Gk6dID3Hn8Qf3cXs1etYdEFlxL0ennnoX/TcGAvBdNmcvr1N2JLMU5JPh5JVc8kSZIkSTJhSAZ+QyP5fEySJEmSjw5JVU9ArmtCefD5/g9azJg+dSmSzpQ2LeBFfvN+1Nq9YLaCzQG+LlBUhMx8TGdch5inr+jliUQ8DXTuuB850Iqr/Hxc5ecY1rcc8bHhlesJBZoAAZuzEJsjl8zcZZRM/wSiaMyMSUT2s2n/3eyveRZZPSLwgEBp7irOXvwLQ96GVfbs50cf3kpYDSEgkm3Lxy45mOleyGUlnybdauxbp9099TxatwlV07i6aAnz04oN7X8seLellRcaGkkzm7m+tIQSp34lureaenissp1qf4igoqFpYJUEzilI4wszcrEaUNur3qPy6J4Ih7tV0q0CH5thZmHuyCphejwqu3fKBAIa5ZNNTCo13p63TqHh9QhKSCNtukTBmYklja0FZeT3a9CavYjlGUhLCxHExHzznQSq23189dEPOdzmw2k10eELEQj3nekTAKtJIKxoCILAouI0fv/xhRSlG1dOaUzY8m/Y9wJkTIayM6IzfP72aB1fbzOoEXBkga8Fgt2QWgjXPwrZ+tS3kyQZS4LeMK/cu5u6g50nagwCYLFJKIqGKqt9Eu3sqWau+fYyUtITv6RLe30tm557kqDXy9yzziW3bDIfPPM43S1NTFt+GkUz57Dx2cfx93Qz64yzmLb8tLF2eVBMiBm/0C/vjd+BAJY7bkbQkVYYevDH0NxX4OUYkgnLjb9ESNNfnFpTIlQ/dTWy97j4Sd7qn5NSepbuvgHWPnsOcrh/UZzCyVcyY9E3DbHz2pZvUdX0Vr/HphSez+oFP9Zt47q3V6DFWIlc4pzCL5f8x7B0i7pAJ5/YdC9hNZruZBYkHlh6C5McmQOcOX7Z1N7B17Z+eGw73WLmkdNOwWEa/juhtU09fP/D2Cq6q/Nc/HiBvjW3/ojGV14P9hF5+f5pFmZmjUzwpygazz4Vwu8//ntbtdpCcYlx9pSwyp67Qr0ysDMXSRSsSpzgL/zQDtTK44qO0soSzGcOPtU+OeM3NEZyxi+iqCz6yWt4gsMTl8pOsbD+22sSt4j7hrvh5TtP2CEwKOULyQLfqOhd7y9JkgTige+9T09bcOCG/WBLMXPTr1Ym9Au/kN/PP750CwHPkbGyIJCamU1P23GxQKvDSch/XDTvsm98nylLlo+4b3qfkQl6Nz6OUlEzcCMNtMbWYdvQvF3xgz4ARUap2DpsGycSaNnRK+gD8FS8YkjfqirHDPoAmmteNcSOrISoano75vGqprW6bezv/DBm0AdQ4ztEnc84Za21rfuPBX0AEU3hrdZ9hvU/Frze1NxruzMcYXOHPhn21xvjK+2ubY6vXDsYdrWq/Sp7vl8fZ/GBTlqa1V5BH0DVYWPtdexU+owru/eP3GcyGi0Q6RX0Aai7jVPVTTK6bK3uHHbQB9DqDbOttss4h0abnY+ftGOQL8qVMFT2/9IzSZLxTsATHnbQBxD0RmirS2xV35qdHx4P+gA0rVfQB/QK+gD2vad/XDsaJHzgR6Z7UM2EFB3pJlY7SAOnPwopxqgYmZx9F8X3t284CEL82Qmr3Rg7kmjGZnHHPG4x618Em22PXzhdEkykWYxTlsrt5+1tjjWx3+hmW/umY+T0s28o5Nji/624zfpnyDJs/b9JzIyx3wgcjr5997dPD7bMvv2ZDLYxolgksJ00W+xK/JSfjyp5afqFq/JSjRW/GlXS4j9j4pKq49wkScYQs01C0BkdONISJ0ulP1Iy+8nkGiB7zJWZGII2CR/4Se5USB1gTVJeFkLa8JUEBbMVadV18dtMmoM4ZdGwbZyIJbUY95xPwhHxfXNqMelzP2VI34IgUDi5fxlqyeRg6oIvG2RH5NTZdyDEuHusnq8/zTPDlk2Rvf91lQIi15R+hlRLum47RzkzazqnZBwvt7E0vZSzc2Ya1v9YcFVJEeUpx/9+Li0sYEaavmD2urIMiuz9B38CcMfsPF39A0zJEFk9qXcAWeyCs8tGbtlymltkxqzjNlNTBWbONtaeq9SEPfeEh4sIheeMnEqp0QiSiOmcySAd+Qx2E+Y1xq19TjK6TMp0cvnC4Qcwt5xeSnFGAq/xO/M7UcVOAERIH+RvefJZUJTMVk6SmJjMEosvKB32+QvPKcGZltgv/PKnTGfumuMlWbJLSll++dXHxrSuzGxmnXF8+VVGQRFLLv7YqPs5HCbEGj+A8N5KtLc3QCAIogTFuRCWEU9bjLkkP+65g0XzdaEe3g4ZhQiCgBbyga8HckqQso0rGXCUiKcB2d+GLXu24WUj/N5aDu28C4erlLzis4mEu3G5p2EyYCbuRILhbmpbN1DT/B7+YAvZ7tksnnYrZpNxb4E/bNvAc7X3cUr22RQ4SxGAXHsRmbZcw2ycyCFvC6qmMc01Mv2PNqqmsbenh1STmWKnMYM0RdPY2xWgNRSh2R8hpGpkWU2ckZeKy4AZv6M0elWqulSyHAJT0sVRkc/2eFSCAY3MLBFxhNYweOsUQh0q6bMlxARcH6X5wmhtfoQCF8IQr3dyjd/QGA1VzwPNPWyo6GDVtGzWHWqlyxdha007zV1h5hanEpRVpua4mJztZHttNxaTwNVLShI76DuKHIL6LZBeCqkF0LgdBCmazulvg3AgGhwKAux9FuZcDQXzx9rrJEl009Me5PCHLdQf6CLgDZM/xQ0alM3PoqWqh3BQprvVT82+DuSQSmqWg4tun4crI4Fn+U+io6GekM9L3pRpCIJAT1srPW0t5E+ZjmQy0dXUiL+ni/wp03XpiAyFpKrnEYRgCM1yZGo5FIH2HnC7EAabkz8INFVF7WgGXzea04225SVwpiNpGlpaDoLFuB+7EvJEa/m5ywwP+gDsziJKpl4LgKqqtNStpaXubTJyl5CVf7pxgiitG+jx1ZKVNh3RPQtZCVLb8j5l+WfGnA0cKguyVrAgawVtwWaqvQdpCzbwTtNLrC64lGlp8wyxAXDA08QjdZvoDvs4K3smLaEeZqcWkG7Rr4J5MpXeLta21rEoPZf5bv2CQUfRNI1d3T3Iqsr8dDeiICAKArPTjKkTeBRfRKU5EKE5GKEzrOCQBNY1e+gIy1xXloXJgIBJ1TQOdqjsaVM5p8yENwIHOxQmpQlk2o27Aft8Kp0dGtnZIlabgMsl4tJfirAXmqbhqZHpOaThyBdIn2kipWhkFUpHFKsJrSeEUtOFkG5HKs9AcCTOzGWS4wTCCg1dQU6ZnImsanxQ2U5dh4+p2S7avGG2VHdSnuVkU1UHr+xqJMdlozDDTn1XYGIEfiYrTDr1+LYqQ8OWaODnyo++aO6qAncJrPkx7HoMDq+DpTeDZQJ8/kFS2V1JvaeexbmLcZgn3ucO19UROnQIx6JFaLJMz4svIqa5ST3vXERLYqc19oen08+Lf91BwCMjmjQy8l2013kI+mRUVcXbESTgjeDrCmE2m3DnWHE4zbTXeydM4NfT2kJXUwMF02YeGxOnZmWTmnV8TObOy8edZ8zk0mgxIWb8Qn95ELz+2B2UF2O9+nxdPsi71qG8+vfYDUwWzNf9ANGAmb9A83YaXvsqWsQPCGQt+wru2dfq7vcoihJi29ov0N2+o9/jDlcpy865H0nSN1X/8JuX4w009nvMZS/gyjMewmyy67JxlDcbn+Pv+3+BSm8hjCWZq7hj7q909//bA6/wRMOWPvstoolfzL6SUzIn93PW8PjLwW08VHNcNOa0rAJ+NX+V7n5lVeWObdvZckS8ZbrLxR+XLNSl4NkfW9p93LmlhrDa/3GLKPDEqim4rcO3649o3PFGkK7Q8X1H9fZEAW6eb2b1JP2f69BBmQ/WR9A0kCQ48ywL+QXGBmSaonHo0SDBE3R2TA6YfpMN0ZxA6/uOoHUFCf19C5woCiIKmK+dgzR54DW3yRm/oTGSM34VrV6uvWcDbd7QwI374ZxZOdx7w1KDvRojNA0e/STs+2/sNpIlGhACiGa4bR3kzhod/8aQP279I/fujKqrZ9gy+Me5/2BK+pQx9so4Ou5/gOZf/AJUFcFmQwuFOFrHQHSnUf7UU8cKu08E9rzXwFsPDF+4LrMwhWu+syQhs1WO8uErL/Dmv+5B01TMNjtX3PlDimbNGWu3gKSqJ0pVffygD6CyFq1bn5Kgsu6R+A3kMPL7T+qycZSOrfccCfoANNq33o0qD19h6WRaat+IGfQB+D1VtNS9ocvG/tr/xgz6ADyBBg7UvajLxlEUVeahij/1CfoANrevpcZ7SFf/ASXMk/0EfQBhVebPlW/q6v9EeiIhHqnZ32vfe20NHPDoU9oEeKe17VjQB7Df4+GVxqY4ZwyPew60xAz6AMKqxl379Sk9rqtRegV9cFxvT9Xg4d0RFFXfSy1V1di6JXKsTpGiwLYtEV199kdPhdor6AOQ/dC+ffhqimNJZH1t76APQNWQ3zBOYTfJ6PCXNw8NO+gDeG1PCy09xj27xpTD6+IHfXA86INofb8XvjayPo0DWv2t/HPXP49tdwQ7+NuOv42hR8aiBgK0/OEPoEYfalowyInF69Subtr++a8x8m5kWPvQ/oEbxaG93kvVznaDvBl95HCYdx7+N5oWveaRYIB3Hrl/jL0yjoQP/OiOLx1/FM2v8+EjD/zw03zd+mwcQQn2HuRrcgBNDhjSN0A41DFwm6C+QMMTaBiwTSDUpsvGUWRNxifHlg7uDg/8eeMRUMJxE4Y7w744R4eGR47QtzQydIb1D566wn3rH3T2s0+3ndDA5QfaQ/qCmp5w/KDOF4FInOBzMKgqRE76eoIjMIaV/f1/lnDP+M/G6Bdf/78pLcb+JOOXNgOuWZtv+IHjuMI3jJJQ/sQd/A6WrlAXitb7nt8enDifWw0G0fzxJxeUtuGXCxuPqDpfmkK0JESiIofDhE962Ad6usbGmREg4QM/cfa0gRtZLQh5+mRWxdKB14qZ5uhPxwNwTbmw17aj6FQkm3HqlDlFZyFJsVMsBUEip0hfsfg5pR9HiPPzEhCZUqgv/fYoVsnGiuz+/U0xpTLTvVBX/xmWFIrtsb//i/KMW0dYaE+hzNl7vV2qycLCdP1lNk7PySblhLROiyiyJs94gZrzCwdeL3h9mb6i96cWxk+3XF4oYTPpS5M0mQRKTlIOLZ9i/Lq71ClSv3fizAWJucZPWtC/aqs0X7+aa5LR5arFRbrOT3eYmZVv7PrhMWPqOeAc4jhi2WdGxpdxxNT0qczK7J3OetmUy8bIG+MxpaeTsir+2M59xRWj5M3oUDjdret8URIom2+cNsFoY0tJYfLi3oXYZ686e4y8MZ4JscZPaWxFfvRFCPXzhiE7HfM1FyLqqeN3hMjr/0I9sBEQIBIC5UjaV0om0mlXYJp9um4bR+k5+F/8deuxpE/GPfvjiAYvlvZ0HaDu0BMoSoSQv4mezr2AhjO1nBmL7iQ1Y4ZuG80dO3hv96/xBpoAAQEBBIEUex6nzP4qeenGKZ+FlSAv1T3K9s4PqPVWEFKCTE6dwRdn/YQMq/6gyRsJ8oM9z7Kp6zCKppJmsjMrtYBTM6dwecFCJIOEagA8kTC/3b+Znd2tlDrSuHPmMnJsxlz/w14fT9bUImsalxcV6i7d0B+apvF8XRfP1XbS6I8gaxqyoqEADpPI12blcXaB/sHg/jaZu7bK9IQ1StMElhaIHOyAsjSB8yebsEj618cpisbePTId7Rp5+SJTp0kjohwabFOpey1MqF3D5BQoWGPGVZKYgR+AvL8NZW0VmicEKRakxQWYFhcM6rtLrvEbGiOt6vnK7ib+u6OR/FQrext7eL+iA2WAcYPVJDC/KJ0/X7+QnESu43cyHZWw7tdQswHkMFhTQLIBKuTNgeIV8ME9EPHBstvglM+NtcejQlewi/v33E+dp45zSs/hnEnnjLVLhqL6fHTcfz/BAwdwnrYSpa2N7meeQbDZyP7SF3Gdpe9F+XjkyV9vpqmi/4w6QeiV7dprvzvfwfm3ziUj33jRu9EkEgyy5cVnaa0+TOn8RcxZfc6oqIYPBr3PyBEL/ARBmA48esKucuAHwP1H9pcCVcA1mqbFzSscDbnqJEmSJEky9nxUAj+jnpHJ52OSJEmSfHQYt+UcNE3bDywAEARBAuqBp4FvAW9omvYLQRC+dWT7Tj22Qg88Cw2xxSLERbMwn3OaHhNoXS1EXv07Wl3/SkfCjFOwXHi7LhsAasRP26Y/4a1+C02JIFlT0eQgSqgHyZZO3uqfY8/Vl1rY0bKZXeu/RyTcRVQLUQJkQEMUrcxYfCf5pRfp/iy1Let5dfM3UbXeM7FmycHCqTcxf7IxRel/vPWz7O3ZdmzbJFj40qz/ZVn2akP6l1WVvx1ey6vNuwiqMiFVJqIqiILAsowy/nfm5ThM+uWcq3zd/OngNqp9PZyWVcjnpizAKhk/6yOrKn87VMnTdXWEFBWTIHBBQT5fnzkd0aA3Wjs7/dxzoIUD3UHCqoZGVHxFAC4oTONbc/UroG1pkrl7SwSfHM2UdFnBKgmsLJa4YrrJkM/i86ps3hShrVVFEAABiookFi0xY9KZSnoinXtl2jZH1z1mLTGRPnPCVNpJEoPRfEbqYW9jD996agfba4+vYT+qoBsPSYArFhXxq6vmjZs35cPmyVtg5xMc+9SufMgoh/ZD0amPYHdU2EWQol+OaILpF8Jlf/lIlXSYiMgdHTT//P8IbN2KfcECHMuX0/nIIyDLpF11Jf7NW/C99x5oGo4lS8j74Q+wFOlLkR5r5IjCf/+0nfoDXcM6f8rSbM67ea6xTo0Rmqry/hMPse/dtaRkZHL69TdSMC2aEdfd0sRb9/2d1upKJs1dwJk33ILFPv7/3kcl1VMQhHOBH2qadpogCPuBMzVNaxQEIR94W9O06fHOj/dGU95zCOX5twb0wXzTlYjZA0uJxyL8wPfQWmvitpGuvBPTpNnDtgHQ8v4v6dn/dMzjgslG+SffGvaDVFVl1j69GlWNv/B2xfmP4XRNGpYNiBZu/89r56MRW2HjvCW/pSR35bBtADxXfR8PHb6rz34BgftPX4dZ0h+Q3Vf9Pncffjvm8Qtz5/L9mZfosqFqGtet/y91geMiNdeVzOALU/WtT+yPB6uquftgRZ/9X5g2hWsn6S9H4pMVrn77EF459rX/1eIiVmQPvxheT0jj9peDMQefN841c265/uDp5ReDtLX2tTJjpsSSZcbUbvI3qVQ83FsAY/J1Vhx5Cb8Ee1h8VGb8TkTPM3IkZ/xkReX0X71FY/fwVY1+ePEs/mdlmYFejTLv/xle/e7wzl36Gbjo18b6k2RUqf3s7XjffnvQ7a2zZlL+1FMj59AosPahfexaN7BAXzyu/d5SsooMLng7Bmx98Vneuu/eY9s2ZwqfuevfmG02/vPtr9BceVw1fs7qcznvs18acZ8SpZzDx4GHj/w7V9O0ozr/TYAudQnlg+2Daidv2T1sG5q/Z8CgD0DZ+vKwbRzFX/9BfF/kILI3dpmEAfv3VA8Y9AF0Nm8atg2A5s6dcYM+gLq2+J91MLzV9EK/+zU0tneu190/wAcd8WXo13f0DaKGSkPA2yvoA9jYMfzrHI+N7f2rnK5rNkaZbE9XIG7QB/BEtT7V2P0d/WmfHmdH68DKogMRiWj9Bn0ADQ06JUNPwFvd11dvjX7/kyQUI/aM1MPBFq+uoA/ghZ0jcx8bNXbHfhE7IAf1jwmSjC2+994bUvvQnr3IHfqUxMeayu36xwLbXh14zJwIVO3Y1ms76PPSVHGAgKenV9AXbbt1NF0bNiMe+AmCYAEuBR4/+ZgWnW7sd2QlCMJnBEHYLAjC5tbW2D9CYfLgZiikQbbrF1sKpAysqimULxi+jSNYM6YOYETC5Bi+QqnNmc9gLnuKW1/x1QxX+SDaDPBZB8H01Nhpr1NdxqQaTE2JLw4zZYDjgyHb6iD1pHTRKYP4zQ2HKSkp/e6faZDQS1mKlYF0VZZn6lv4XZIa30BJqv5bm8kEKSn920lPN+7Wacvq21d/+5JMTIbzjBzs81EvJRkOUqz6Zs4XlriNcWasKFw0/HPzjBMwSzI2WKfHTUjrgykvDyktsZVssw2YqStfqE9Jf7yQXVLaa1uUTGQUFmNzpuDK6q1cmjMpMTIbRmN0cQGwVdO0oyWKm4+kr3Dk//0uztM07W+api3RNG1JdnZsWVjLGUvBHP/BJGRnIE0dftqiIIqYz78NrHFyd1OzMc/Tr+yUtezLWDNPvNGIcFQxUhDJWvZlBB3piyaTgynzPk90IUL/FJReijtrwbBtALgcBSyccnPM45NyVzGt6MKYxwfLZ2Z8B4ep703qwqLrSbMOP7X3RG4qXclid/T3c/K3lmN18e1p+j+HVZL43uwVZFqiCnizUzO5ffLIDBo+XV7KfHfvB9PUlBRuLDfmppVlM/O1WXk4YtxdJjnNXK2znEOuU+Syqb3XPx69NgtyRS6Zoj/NUxAETl1pxukUjmxH92dmCSxaYtwaPFe5SOZCCUGMLhHKXCjhKksGfh8hhvyMHOzzUS9Oq4lfXTUPh2V4a42nZDv52jlDGziPO877OaSf9CJTkOBoiZ9Yis7pZXDBL0bWtyQjTv5P/hfLpOjz3zJpEmmXX4ZgsYDZjOu8c5HyjpepkTIzKfjF/yGMwNr80WT1DTOxpZiHfX5KuoXJC8csUcFQll1+NaULFgNgdTo559bP43SnI4giF3zuq7gyo/ff7NJyVn86Mcq3jPgaP0EQHgFe0TTtX0e2fw20n7BwPUPTtG/G62MwaxjCHV1oO/aD0wlOO1K6C80fRMzPRnLErlk3FDRVRQv0IDdXoakKRCIgSUh5UzClGjs7owQ7QbQgAILZQbi7CrOrCFEa/h9jr/6VCEFfPSZLKqIooWkaAV8jKallSCbj5LcVJUxr9z5Mkh2rOQXQsJpTsZj7n3UaLo2+Wup8h0mzuJnkmoZVMl5CvDvixyaa8SthBARCikyu3dhyCLKq4pUjuC1WQ/vtj55IBF9ExiqJZFiNtxdWVUKKhl9WsEkibcEIaWYTWXZjfsMAYUWjxafisgo4TAIhBVIsxgpJaJpGKAgWK4TDYLONjFCFcqQovWSw/4nGR22Nn95n5GioekYUlS5fmH1NPZRlp+CymWj1hHCYTbR7Q3hCYSbnuAhHNBRNJayouO2WiVXKobsBvC3RDKC0EhAlCHSCNRXCXgj1gD0DIkHQFEjNH2uPkxiEpmkoHR1IGRkIgoDq96OpGlKK89gxBAEpLS3hg74T6W7zE/bLWJ0mulr8tDd4sVglUrPsdLYEsNol8svc7N/YSCgk40y1MXVxDiluY8bc44mA14PFZkMy9R6/qKpC0OvFkTp6s7zjVtUTQBAEJ3AOcNsJu38BPCYIws1ANXCNXjuqx4f22EvQfXyNlBJ1APW0RUin6UjVOAF59zrUdx6DcAisNnCmQfFMBFVBcy5BkPR/naGuSjo//BdKyANoSPZ0RJMDNIWU0rNwFC4fsI/BEPDV0lD5HL6eKno696JEvFgdecxd8XNSM4x5Q9vlqeaNbd+lx1eLIEikOgspylpOfuZiinNOMcRGtecgv9r5dbrCbYhIaIKKWbCSZy/iopJPsDL3PEPsVHhb+Gf1uzQEuljqLqVHCRJWFa4pXMIMgx7wXjnMG03V7Ohuo9bvoS3kRxJEVmTk89mpC3CajAmYKjxeNrS1EVY1rJJIod1OQyBIqdPBiqxMQxT41jb18EBFKzW+CKCRZzNxcXEGV5caMwsLcLBd4dmDMr6IxrwcAYskkmIRWFEgYTVQcVMQBGxHnmM2GzQ3KbS1qeTkSmRnGzczJ1kEIj6Nzt0ykhXSpkmIBn6O0ULrCaHsa0WwmxFnZiOYkrOXsRitZ6Qe6jr83PbAZg63+Ul3mOkOhPGGe69xFQVItZn4zoUzWViSzp/frMBmEvnKuVMpSBv/KndxqX4f1v8F3MWw+rvgaYaN90BqIchBCHlg1uWQXgrV6+HDB0GywNKbIVef2FuSsSXS3k7bn/6E0t1N5s23INpsdL/8CmooSOoFFwBOBEHAlKkvg2U8smtdHWsfOcBRqQbRDOqR0tUIYDKLyOG+a92bKrtZff1MbE7jXvCOFVXbt9JafZhJ8xaSU9r/8iVRlPC0tfHGP/6KNSWF0675BM60kVmmYxQJX8Bd9fiI3PVQ/A5mlmO9dI0uHyJvPYi67ZWYx4XimViu/rYuG/7GbTS8/DniCWW753yCrKVf1GWnrfFdtr/7DYghvjL/tN+SVaBPbbPbW8tja6+KeXxO2XWcMusrumxU9uzjO1s/HbfNmvyPcev0b+mys7Z1P9/a/WTM4z+ZdTln58zSZcMrh/mfja/QcJLAy1FSJBNPrbxcd/C3trmFH+zYFVN254riQr46Q1/g/9f9zTx8uP/F7QsyHPxx2fDTro/yXq3MX7ZG+j1Wkirw01VWTKLxQdPunRG2bZWPbS9dbmb6DGPen4W6ouqeyhEtDXuOwOTrrAgj8DlGCrXNR/hf2yAUFacRilKxfHrBkF4mfNRm/PQykjN+1e0+Vv367WGfbxIF3vj6KibpXNM7Zmy5H54/4XlrSTkyoyf3bmdPhyU3wzu/OWGnANc+ADoVn5OMDZGWFirOORctdFxx2ZSfh9zYBICUlUXZk09iztW/xn+88dZ/9rLn3eGLMokmgVt/fwYmc+LOfq79zz/Z/PwRdVZB4KIvfYMZp57Rp13l1s08/csfHds2WSzc8qd/4HSPXPCXKKqeI4b8ziAeeHvjqzIOBvXD1+Ie12r3ojYc1GWjfevdDFQdqXvP46iRgC471fv+Q6ygD+DQzr7lEYbKup0/i3t8T9XjhGWfLht/OxDfBsDbTc/rsgHwn9oNcY//o+pd3TZeb6qJGfQBeBWZV5oO67bzYFVNXK3VZ+sa6In0H1ANlqfjKHZ+2OGnOyzHPD5YHt8Xu4+aHo1tTcapbh5F0zR27+ptd/dOfd/ViXTsUI4FfQCBFg1PtfGfYyRRNjUcC/oAtLoe1OruOGckGc/830t7dZ0vqxp/fuvQwA3HK2v/r/d22Ns36INoyuf6P5+0U4N3/zBSniUZYTruf6BX0AccC/oAlLY2up+K/UI4kdET9AGossa21xJX1TMcDLDtpeeO79A0Nj77RL9t33n437225XCYLS88M3LOGUDCB36o42hgpOn0RRtYwj1aIkHfLO1AZRa0QfgxoI0BvgsNLVr4VgfqoM7XP6OtDvBZBjo+GLRB+Kmo+j/LQHY0TdN7WQb8JEbkGAz0VYzUXeHk78aAS3JC5/3sG0e3t0HR348nAbJKkvSPEY9XWUng6z+kL6C/336yLEvCog5iPKYk2g169NAS+e9e0zg5G1KLcS/oL2tSHU9xST8kfOBnOn0Qs51TinXbEWf3neI9ESF/MkLBNF02MhYOrAiUNu1yRLO+NRMlU6+Le3zynNviHh8MK+fcGff4jOLLdAu83DT1GwO2OTXnXF02AK4rjr+u8oZJp+q2sSa3hJw4qrF2UeL8fP2qm9eWFMfRc4ULCvJJs+hLJ72o0B3z2Mw0G26L/tTIj02L3Ud+isDCXONvbYIgMGNWb7uzZhu3TDpjroR4gmCvNVMgpTSxbtHS4gIwH/dZyE9BnOQeO4eS6OLO82foOl8SBD6/Wl9poDFl5dd6b5vs9DtssrhgyS1995/yhRFxK8nIk/GpTyGYez8LpazjJQqktDTcV3xstN0aFaYs1Ze+Kkiw8FwdJdTGGIvdwdw15/fat+Ti/q/1qVdf32tbMplYfNFlI+abEST8Gj8AtaObyAPPQjDU9+CiWVjPOc0QPyIbn0fd8BzIETCbwe6CwumYiqYjzjgFwaxfGTHQspvOHf9CCXahaRqSNQ3R4gRNI6VsDSmTzjREfKOnYy91FU/h6a7E31OBqoSw2DKYvfx/ychZrLt/gJbOPby57Xt4A82IoojDmkNh1lKKspdRmncmQiwZ7CGwt2sbv911Jz65BwER0JAEE1nWPM4ruobzi67W/0GA3T0N3FP5Nq1hD/NcRXjVMIqqcE3xUha59a9ZA+gKh3ihsZIdnS3UBbx0hYOIgsii9By+Mn0x6RZjFPJ2d3ezvrWNgKLikCTy7Daag0HKUlI4IycbyYDf139ru3iwso2WYARNgwyrxAVF6dw4JcuQ/gG2Nys8dzBCQIZZmQI2k0iqVWBlsYTDPHLr4urrjoi75IjkFxi7hiHco9K1T0GyCrhnSgmp8Kl2BFD3tIDDjDQnF2GIpQCSa/yGxkireh5o6uEzD2ymoSuI3SIRCCuE+3mb7zCLfOnsqawoz+KPbxzEahK549zpTM4xVsF51Nn30hExlwI456fgqYd9L4ArD+RQNP1zzlWQPgkOvg7b7gfJCstvg6LkzziRCdc30Pq736H09JB56y3Ypk+n+7nn0UJBUi+5BHPuxChZ0B8fPHeIzS+ekK4p0isDRZCEfmf1Cqe7OfvGWaSkJ7air6aqHNq0gZbqw5TOX0Th9Jkx29bu2cnGZ57A6nRyxvU3kpo9sus+9T4jJ0TgB6AqCpGW9qjEsiyDLwhuB6bMDCQD5XUjna2oqoJoNgEigigh2Z2GKHqeiCoHAQFNlZEsxi+MV5Qw3R37sdjcWG0ZoKmocgTJYsNkMk6FTdM0AqEOTJINVZNR1DBWkwuTgSUjQkqQsBLGYXLgl31oaFhEKzaTsZLCQSWChEBAjZBqthNUIlhFkyGB+FEUTUU58jcZURUUVSPFbEE00MaJBBUF2wjJT+9s8yCiUZLmRJajKcomScRlwIzfUUKySkRVCUdlfEm3iYQVDFX1HE3UiIZoPvJAFUgoYZejaJoGijZsNc9k4Dc0RqOcgycQpt0XxiyKWMwCnb4IJimaxeuymLFbowFhhzeE3Woiy2lBEwRSbImv7NcHJRJNAZX9UVGXcAAiflBlsKVFj0sWMOBFcJKxR1MUNEVBtFji7puIHN7dit1pQoloaApYHCI2hwW/N4SnI0hBeTqiWcTXFeBoJd30XCeSKXFFXfojHAwS9HlJSU9HFMf+s43rcg6jRfiJV9Aq+l9IKgPK5BIsV+mT9VcaDiI/8pNj2ydm8CqAMOt0zOfehKDzRyH722h6+3sEmz88ts/kzKPgvD9iSTNm6nzDK5/A1xN7wb3DVcrycx/S/QPfW/0U7+36db9rCjNd07hs5T+RRH0Dgx9vvY29PR/2e6zYMZlfLv0Pos6ZxY6wjx/ueZbNXVXH9lkEibCmkGdN5ZvTLuCUzMm6bAA8XXeQuw9tx6v0FgwRgFvL5/Lpsjm6bRxlT3cPP9u1hxq/nzlpqfxw7mzy7MYEys9Ud/C7vc0xj6eaRR48fTJpOgJAWdX40TshKrv6f3FVkirw+cUWilMTI1Uy1KVS+2KYQLOGZIvKZgsiZC0xkbsicQbPysF2Ii8eBE8IcUoG5stnItgmxGPmI8uyn71Giyc8rHMnZTp45nOnke6cIAPkt/4P3v0dKEe/j5OmQY4hwKzL4Jr7RtG5JEbT+dhjtP72dyg+H2mXXEL+j39E9/P/peU3v0HxeEi98ALyf/rTCRcAvvqP3RzcFPsZPhDlC7O44LZ5Bno0djxw55dpqao4tr300is54xP/M4Ye6ScxRkVxUNu7YgZ9R9EqalB8w1eQ1DQN+bH/i99mzzuou9YN28ZR2jb9sVfQByD7mmhe92PdfQN0tu2IG/QB+D1VHPzw97rsyEooZtAH0O45wIeH9D0UX6h9OGbQB1Drr+D5mgd02QC4q/KtXkEfQPjIov2mUA8/3PssQUWfumONv4ff7t/cJ+iDqGTA3yp30hkO9j1xGGiaxk927abG7wdgV3cPv993wJC+gbhBH0BPROV72+p02Xhsrxwz6IOosuc924Y3WB0LGt6IEGiOfh7lSP1nNQIt62V8dYkhEKGFFSLP7AVPNOVePdSBvLZqbJ1Koov/9/qBYQd9ANXtfr7xxHYDPRpDDq+Dtb84IeiD2OpLGux5Bva9OAqOJRkJwrW1NP3wRyjd3SDLdD/9NG33/I3GH/wApbMTZJme556n84H/jLWrhqJpmq6gD6ByWxuNlYmv5rz+yYd7BX0Am557kq4mfaqnY03iB36HawfVTtNT0iEcjKZxDORLc9XwbRwh1Lav//0d+kpFHKWp6oVBtetu36nLjsffMKB6aEP7Fl02dnVuGrDNlvb3dNkA2OuJ/0fukYM0BLt02TjQ0zmg2uXe7nZdNo7ikxXq/L1Lguzr8RjS92Cp9PSzHncI7G8fOBg6HCcwHG/4m2P/rcQ7Np7QOvy9SjkAqI2j+7tKYiwv79I/wNnd0GOAJ+OAhm1DP+fgq8b7kWRUCO7e00eR2L9pEyjKSe12jaZbI46vS9+z+Sj1+2KXdUoUanf3Pw6u3aNvfDzWJHzgJ04bnNKhMG/46mSC1Q7mgdekiSWxF38OFnt+/8IqjryFuvsGKJ4WX9HzKHoLuKc5ixGF+ClepXmrdNlYkbNmwDar8i7SZQNg8QDiLVmWFErsmbpszHVnYYqTkioC89ONWTCcYjYx1dVbcGFxxsgVG+2Peen61pEuyhs4DXlWVuLc3lKKY/uaUjT2awoGg5DlBGfvtFSx1D02ziQxhBtOKdXdx6mT9d0bxw2lw3gmzrvWeD+SjAr2RQv7qHqmrFmDYO29dtOxfMVoujXiGCXKUrYga+BG45ypy/pXbC9ftHSUPTGWxBkZxUBMTUFYOjd+myWzkXRK1Js/8b8QS8BFEBBPuQJpuv4bQNaSL5BSfgFRXXcBELFmzyHnjB/o7hsgJbWUrIIz47bJyF1O+exbddkRRRPnLPk1ktT/TaQk53TmlOp7KK7Ku4hVORchxChQsDDjVNYU6JfV/WzZmVyUNw+baEI4Ys1ttpNmsjM3tYhfz70ak6jvTynX5uSnc0+jzJGKTZQQT/hMdlHiu7NW4DQZt9brx3PnsCQjnTSzmbNyc/jKDH2lSE7k/y0tinu8xGnhRwsKddm4dKqJpfn9f+dWCRbminx2UeKsuyhcYyF1iohkA0uGgDkFLG6BonPN2EegNMVIIJhELNfMQSh0gdOMtLgA00pjFG+TjA3XLZ/EnMLUYZ0rAMvLMvjp5fGfzwlD4WK49M+QkhtdgAsQSwhNssCpX4ZJp4yef0kMxZyTQ+Ef/x/WadMw5eSQ9bnbybjhUxT96Y9YZ8zAlJ1N5m234b76qrF21XBWfEyfZsHiCyaRWZDgar7AwvMvZsoJwZ8giqy5+XM43aP7otxoJoyqZ5IkSZIkSXySqp5DI/l8TJIkSZKPDklVTyC0bTe8+n7M48LNV2DJ0p9uIu9+B+WN+0A+abG7ZEG66k5MhVN12ziZ9m1/x1v5KqaUfHJWfgezU3/dmICvgQ/XfRW/t6rXfsmUQmbeKZTNupGUNP1Fdz3+Rp59/2YCoaNr00REQcLlKOCCZf8PlyNftw1VU/n59i+zu2vzsTWFAiJ2ycHk1Nl8bsYPSLfqTzl4s2Uv91W/T48cQBJEMixObpq0khUGqHke5Tf7NvFcfQUKGgLRN+YpJjNfmLKQiwqNsdMWDPFkbR1eWWZ1bjbP1zewr9vDgox0vjpjGhadM5dH2dzm4y/7mqj1R5DV46s9JeCz07O5tkz/NdnZovD8IZl6j4o3BJEj77AyrPDJuWZWFBpze1MUjYMHFDo7VPLyRcrKR+62GWxXadsi03NYQY2APUdg0iUWTPbEmPU7EWV3C2plJ0KuE2lRwbDLOyQZW17b3cT3ntlF8xDX5drMIr+6Yi6XLoyfAZAQNO2Ct/8PGj4EixOmXwit+6KCL5oareFXujI6NnBmwrLPROv+TUDaAm08vO9hOoOdXDr5UhbkLBhrl0YE1eej8+GHCR0+jGvN2dhmz6bl178muHcv9oULyfn61zClR2d+VL+fzoceOtJ2Da6zzhpj7/UhRxTu/857BDwDa1v0x8prJjP/rMTN9lBVhdfvvYvaPTvInlRGSnomNbt3kJaTyxnX34hktvDhqy+gyjLz1pxHVknpWLs8JBJ+xk/p9iDf/ciAfVjv1Je6KFfvRnnyl3HbmD9/D6LVuNpxLet/Tc++J49tC2Yn5Z94XVfduEi4m3eevxhNjaPUJlg45bwHcbj0lY+494VTiKV6Jgombr5Qv/DKNzZeR60/tnCPQ0rh7ytf01XS4e3WfXx791P9HvvVnKs4PUt/muQf9m3m8frYAj5fn76EK4r0vVgIKQqfeH8DzcH+B3AzU1P523L9Ey2HegLc9H5V3DbfmJ3HJcXDT5fY3Kjwu43x1QY/NcfMBZP1B2nvrgtTdfj4gv6Fi0zMnmt8iYVwl8rB/4RQTxJ2lWww63Zja1KONPL6WuQ3jv9dirOysVwxa1DnJmf8hsZIzvi9vb+FG/81sIhWPP7+6SWcPTOBC1237oe7V56k5jkAqYXwhU3RIHECEVEiXPbsZdR6oqJ6kiDxz/P+yaLcRWPsmfHU3HQTvvfXH9sWnE60E9ThzcXFTH7lZQRRpObmW/C9d3w8k/+zn+K+8spR9ddI/vblt4mE9ImKXfWtJeSWDi9NfKx55AffpH7/nn6PiSYTZquNkM8LgMlq5YZf/pH0fH3LV4aC3mdkwr+ClZ9+bVDtIvsP67KjrBs4uFQ2PKPLxsl4K17pta1FfPjrYs9sDobW+rXxgz4ALUxTzcu67NS0vEdsqWtQNZmaZn2fBYgb9AH4Fe+g1D/j8Z/aDTGPPTMcpbd+eK4h/ud4rKZ/tdeh8EF7R8ygD2BvTw+eiL6yFAD3VwysPnr/oTZdNt6qHvhN5JuDaDMQkYhGdVVvFbeDB0emvELXfqVP0AfR8g6BlsRQ9jyKsq23GqS6txUtqP96JBld7l5bMXCjgfp4O375oHHPjkeHFvQB9NTDwcGNTRKJD5o+OBb0ASiawtOHnh5Dj0aGcF19r6AP6BX0AURqawls20akoaFX0AfR+n+JSsAb1h30AbxxX/+BUyJQv39vzGOqLB8L+gDkUIi97749Cl4ZR8IHfrgG+UYtzaXLjGAbWIVQcBmrXiaYrH32STrVI02Wwb2BMZn1fV92y8B+Ouz60/1iCbucSKpZ30LcVFPs2ZZ4x4aCWYr/p5hq7vtbGCouU/zZLxEMSfV0WwZWoXSa9dlxmge+7oNpMxCiCCd/bSNVq1eyxvZX0n/5Rxf7SV+aWYJkqmfC4Xbo/7FnOBPtx3sStrThnWd3G+rGeCC1n/FDf/sSHdHp6Hvj7wcpNRXBboeT1D+l1GH+ZsYBJrMxKtIOV+KIq52MKA3tO7A5E0vIJuGfxObLzh5cuzx9QYZ0/mfjNxBNSAvP0WXjZDKXfKHXtjVjOras4ZelAMjKX4k9JX4Kpz1lEvmlF+uyk+2egcMau/xAij2PrFT9KZJn5V8e9/hk1yxKXfrsfGnymn5LLdhEMzcYpNr2nRnLYh4TgM9NWaDbxoJ0N6ecsNbVelKQd3lxIdYh3vD649Zp2dil+EHXd+fqW9956VRTn9jiZK6aoT/NU5IE5i04/lAXRViw0Pg0TwD3TAlbVt/vzVEoYklLrFu16YxSOOE3YDpjUnKNXwLyrfNnYB7gbzkeAvDN8/U9s8achZ+C9NKhnTPlbCjTV65oPDIvex5nlxwfc+XYc/jkzE+OoUcjgyk9ncybbjq2LTocWGf1TlV3nXsu1qlTo21v7t0263O3j5qvRmO2SuRO1h/MX/DZxFXzXXThpTGPpebkkT91+rHtzKISZq0auLTYeCLh1/gBqKpK5N7HoKufYsEl+Viv0xfEHEWJhJBfvhfq9kLAB6jREg8zV2I55390rb2LRaSnjq69T2DLmoFr8vmG9KlpKg1VL1Kx869Ewl4kkx2zxUl6zlKyC04jM28FomjM4PbDQw+w6/DDgEC6azKKGqY073TmlX/CkP4Bdndu4b6Dv8Mb6UYTIM9WQqY9m0UZp3Fq7rmG2PDJIR6t20hYUZBEkVSznYvz5uHsZ1Z2uDT4vfxw13t0hEPkWu34FZlZaZncOnke6RZjautomsaHnV14ZZllmRns7Orm/dY2zsrNZU66cW8pw4rKo1Ud7O7041cU2oMyHRGF2S4rP1hYRKrO8ioA/ojGBw0KjV6VVr/C4a7oQPPMEoEzJ1lJsxn399jdrdLZoZKTK+FwGP93fhRN0fDUqHirZUKdGumzTLinJ6YGl+YNo1Z3IeQ6EbMGv9YpucZvaIy0qqc3JPO3tRU8trmWDl8Iq0ki1W6mJxDGJkkEFRVV01A1DUXVMIsiNovEqZMz+fkV83DZRuZFyagih2HfC1C3EaypMPdq6KiAzf8ETYCylVByCnibosdLV8IIjAfGC1ubt9IZ7OTUwlOxG5T1Mh4J7t1LuKoKx4oVSG433nXv4N+0iZQzTse5rPfL2uC+fYQPH8axYsUx0ZdEZs+79ax95ABoGqoADDJTPz3fwdXfXoLZkpjPraM0HNzPvnffZvLiZVidKRzatJ6sklKmLjsVQRSo2bUDVZaZNG8BkoGltgZDUtUTEEURYcFMtK27o6/kVQAFIirkZRtnx2RGnLoYVZVBkBBLZqMFPQhyGE1VEGLV+Rsi4a7DgIgqB7C4S8la+gVCHYdQQh4kq74UTABBECksu5icwjOo2HEPbU0bsNnzAQ1HarlhQZ+sBMlwTSbHPQcNmFZ0IekppbR7DqKqMqJozPeVbctnYcapRLQIizNXomoqhzy7meE2pug9gFU0sdA9iUM9TXjUMCE5zLttB5iVWkixI8MQGwWOFO5ddh4ArUE/D1fvJdtqJ8XAm4ogCCw8Uqy90usl3WLmvII8ALrCYdwG5TF6IgqNvhARVcEuCphFSDeJXFmeaUjQB9FsQpdZQ3IJXDzFRoNHpc6jsiBXMjTo83hUPB6V7JyRDfrkoIq3SsVRKJJaltjpcao3hLypHiE/FXOWE607iBZWELMnltjFR4EUq4mZeS6uXFxIqs1EY3cIm0lib0MXFW1+rl9YyPrKLjRBw2E24bRKlGW5WF6WgSPBB3/HkMyQNRWsKRDogoMvgz0H5l4Dk06Lqn627YeZl0bbTHAmophLf1hnzABRQgsECDY0YC0rRe7sILh/P+biYiz50cyVcHU1osNB6gUXjLHHxjF9eT573m+gq8WHM9WKCvS0BnCl246UsRTQNA2LzYSmqfS0+5FDUDInPeGDPoCCqdPJKCiku7mJ7Ell5E0+Lq4XCQWxp7jIKCoe9aDPCBJ+xk+RZeTf/mvAPix33ISgI41N7Wkj8q9vghL7tYd0xR2YSucN30bER8NrXyfY/OGxfaIlBQQJNdSNIFnJOe3bhsz81Vc8zb6tv+j3WE7xOcxd8VN9/bdt5uWNX0HV+hcLEQUTFyz7IwVZi3XZ+ePu7/F+a+xF9OcWXMVN076hy8Yhbwuf2/YAHqV/YZQzsqbxs1lX6C7ifpRf793EMw29BRHuXnw2c93GvMToiUS4Y+uH7O3pPUNuEgS+MG0qV5bok1//894mHqvujHncIcDjZ03DpWMtQZtf5RtvhgjF0FlZVSxy2yJ9wZOqaryzNkxtzfGF7tNnSCxdbvzahfYdMg1vHP9byVwoUXBmYq6RCL9Rgbq+7vgOUQA1+pwRitOwfHwOgjX2wCA54zc0RnLGLxBWWPqz1/DG+kMbAJfVxPNfXEnpEGZ8xx2eJnjgY9AyGLEKAT52D8y/dsTdSjKyyB0d1NxyC6E9sYU+3Nddh9zagvf1NwBwnXcehb/9DcIg1geOZw5ubebVv+3W1cfn7lqNICburPfutW/w+t/vQg6HcGVmc8W3f0RW8SSqdmzjv3/4BSGfD1uKi0u/9m2KZw9/3D8cPvKqnsqzbw6qXfgZfQpb8mv/ihv0ASj//bMuG937nukV9AGoYS9qqBsATQnRuuG3qPLQ6imdjCIH2bftVzGPt9S+hiwHdNl4f/evYwZ9EFX1XLdDX3C5t2tb3KAP4NWGJ/BF+kkBHgJ/qngjZtAHsK7tAG+36VfdBGgIePsEfQDf36VfAfUoj1XX9gn6AGRN466Dh+jRqewZL+gD8Gvw70Otumz8fXskZtAHsLZW5WCHPmWy+jq1V9AHsH+fQke7sQqbmqrR+Hbv77x9m0LEN/5fyp2MFlF6B31wLOgD0Gq7UbY2kiQx+Ml/9ww76APwhGR+/HziqvsB8O7vBxn0AWjw4h0j6k6S0aHjn/+MG/QBdD388LGgD8Dzyit4TthOVPQGfQBrH9lvgCdjQyQc4s1/3YMcjo77PO2tvPPQvwF4859/JXRE4TXo9fDmv+4ZKzeHTcIHflp7/EHmMZoGlpiPa6dnEAPViL6ALOKtH7CNGvaghr0DtotrJ9wdLTobh1BA38Dc428YsE0w3KXLRktwYBsAXWF9pQPqAwP/xuoDXbpsHKUx4Ot3f1c4aEj/AA2B2EF9WFVpC+n7HQ+Gat8Q5dFPotU/cFDU6tcXoHk8/Z/v9RobkKkR0PoZW8sG2xkV/AO/NNA69b1USjJ67Gvq0d1HdUf/97SEobNqaO3DCf55kwAQrq0buFE/ROqHd95Eo+Fg91i7MGyCHg/hgL/Xvu6W5l7/P0pXS9Oo+WUUCR/4mU4bXK65ePapuuxIM08buFFuuS4bKZNWD9jGljMPk0NfSQebIxerIy/mcUEw4dRZvL0s76wB2xRkLdVlY37GCkTipwtaRTsFjlJdds7OiV94WhJEzsjSV1z9KHPdWf2WVDg927jioGfmxlZbneR0UObUl5blGIQK4KVFbl02VhbFv+5mEebm6FMoLSqW+ugzmMyQl2/sbVOyCljTexsSLWDLTrw0GSHNBtb437s407h110lGltvPnKy7jysWjl5h4xFh1mVDa583Z2T8SDKqpJ43sDCcYLfDiUuIzGZSVg889hnvuDL1LzNY/anpAzcap7gys8if0tv/qcujMcDUZb1jiWnLBxEbjDMSfo0fQOi512FvnALtpQVYr71Itx/h1+9D2xFjGj+rCMsnf4qgc52Xt+pNuvc9iexrQTDZcBSuQDDZCDRswpJeTsaCWzDZ9YuJhILtbHrjZkL+3mlXksnBktX/IMWtL4iNyAE+2Psn9tY8BRz/jVnMqaCpFGYt46yFP9Et8FLRs4df7fw63ZEOAAREBAQ0NDIs2Xx/wV3kOfStWZNVlb9XreOJus341OMzVQJQ5sjiK1PPYWl6mS4bJ1Lt6+HzW16n88gM8iJ3Dr9beCZm0Zj6OgCvNjbxdG0dbaEQqgZmUWR+upubysvItetTEG0NRPif9yrpkfufMbt1ajafmqy/huP9O0K8Wa2iapBph+5QVM8pxwlfWGylzK0/QGtuUti8KYLPp+FOE1m63Ex6hvHvy+SgRs3zIQItGpZUgeKLzNgyjLveo4naFSR83zbwhEEEYU4OQliFkIK0KB9pgMAvucZvaIy0quevX97HPesqkdWhjRWsksD/rCzjzvNnjIji9aiy5T5Y/xfoqgEldCRjRgDRDI5MCHWDqkDRMvjEo2BJ4DWNSY7R9fQzdD/zDEpXF5qqInd0oHZ1gaZhLiqi6O6/ojQ10XHf/SAIZNx4I84Vy8fabd3IEYW/f30tyjATc0rmpHPJF4wT1xsLfF2drH/iIdpqayhftJQll3wMUZQIBwOsf+JhGg/uo3D6LFZc+XHMVmNU1weL3mfkhAj8kiRJkiTJxCAZ+A2N5PMxSZIkST46JMs5AKF3t8B7W2Mely45C9MsfSkrWtBH+J4vgdL/GhZhyUVYztCv5BVo2UXj618/IugiIJjsCKIJR+Eysk+505ByDo3VL7J308/QtL5iNYJgYtKMG5g85zZdNhQlzLZD/6Si/nV6ArUnW2F26TWsmPVlREHfrMardU/yz0OxhWq+Mfs3LM4+XZcNWVX5xf4XeaVlF/JJayPtkpnvTruYNbkzddkA+MXeD3i5sQoVDadowq/KiILA6pwSvj9rhWFvzdtCIf5RUUmlx0tTMERXOIxFFPny9GlcXFSgu/9qb4hb3z9MMMYMwfQUC/eu1J9C9ocPQmxsOn49BMBhhsIUWF1qZlWJsbc3T4/K9u0yPq/GpFKJ6TMkQ65JxKtR9WyIYJuGIIDJCeYUgYw5JtJnJ9YtWlNU5HdrUCs7EHNTMK0qRXAmpjppkihfengLz20f+joWSYB/37iM06cneGrvK9+BLfeDHCCqYy+CEgRBitbsC3ujC3Uhug8tOiOYkgs3PAc5CV7A/iOK9/31NNxxB0pXF1gsiHY7gijiPH0l6dd+nM4HHiBcXQ2CgGCxYJ8/n3BNDarHg/vqq0m7xJj60WOBqmr88xvrCPmGJ+y04JwiTrtymsFejR5tNVWsf/IRfF2dzDrjLOaedS5bX3yW7a+/TMjvI7OomNmr1lC5ZdORNquZt8aYOtujQcLP+Km+AJE//2fAPsxf/CSiY/iFRkN//TwE4qtDSuffhmnW8PN91YifygfP6V/pAXAUnkLBub8fdv8Asuxj7dMD56DPWvpD8ksvHLad93f/lt1Vj8Vts2T67SyccuOwbfSEO/nM+wP/sf1z5Rs4TMOvrfTbA6/wRMOWuG1eOvUruC2OYdv49+Hd3Fu5I+bxKwqn8PUZ+tZEHuUzH2xmb0//og1PnX4q2bbhpy3Iqsa5r+4bsNbrpUVp3DFn+EHmo3vCPHsw/kPpK0stLCswJl1SVTWeezrUS9hl6XIz02foD8z2/T1ALOHZkksspE1JnJTPyOsVKBuOixsIJWlYb1gwpD6SM35DYyRn/P7xbiU/+W98ZcOB2P/T87GaEuc33Iv3/gSvfW/455ts8J0GMDBNP8nIo/r97F+yFNQYAmFmMwygfl38t3tIOeOMEfBu5Hn4Jx/QUa9PpOhTP19Basbwx0RjRSQU5N4v3Eyg57g4zczTV7P3nbfinnfhF77OzNMH1ukwgmQ5hw3bB9VO3TF8aVlNkQcM+gDUnfF/GAMRaNoWM+gD8NevR1MHGlLHp/7QU4NrV/m0LjtVTW8P2OZQ3Uu6bLxS/8Sg2m3v2KDLzlutA5dqeKl5py4bLzfGWaMKrG01RimsLRiKGfQBPF6jz86BnuCAQR/Aqw36FL/W1Qz8JnJjw/Bl6E+ms0Pro+ZZW62//4hHixn0AfQMENyON9R9vRV0tZputEEofSYZn9z3XpXuPjZWduh3ZKzY/rC+8+UgNMV+oZdkfNLz6quxgz4YMOgD8Lymr4TYWKI36AN47/G+ZakSgfp9e3oFfQBVH8Z/8Q9wcOP6kXLJcBI+8KMkf1DNhHwd6SaiRDSRbAAbGfrS5Myu+Opnkj0LQacYSlrWgkG1c7gm6bKTOghBlbQUfTZmpM0fVLtCnaqeeba0gX1Jia2SOhgK7fFnJHOsxrw5c5lNpMQpLjs7NVVX/3l286DaZcUp4D2o8x0D/z3mOo0TlHA6BU7WbUpx6e9fshP3LmxxJ5YohpB+0myxwzygymeS8cvknOFnShyl3IA+xowMfSJnAKQV6+8jyahim6E/Pddcok8ZfSzROcwEoHiWfhHCsSAtN4+T5byd7vTBnZcgJHzgZ546CQZKI8lKR5o0fElpQRAQz7tlAEesSKuuH7YNAIu7lJTy8/o/KFrIOV1HyskR3FlzBwzqTJY0pi34mi47K2Z9BactdrBtlhwsn/lFXTbmZiwjwxK7NAFAkb2ckpQpuux8d/pFWMXYAc30lDwWpusLYu+cuQxbjHQgqyjxvVnGKIVZJYmvz5iGXepra5LDzqq8+N/nQGRYTVxZ4h6w3R+Xleqy8/VlZuJVjZiSLnDBZOPWx9nsAouWmI8Ff2lugbnzBxfkxkM0CRSs6t9PR75I1sLEWuNnOnsyuKzRDYuE+YKpCFLCP2Y+svz2mgWYdFy+hcVpFLqHv8RizLnod2AfeNAXkyU3g1O/gnGS0cU2YwbO1f2n7QlWK6mXXhJN94RjQYLkdsORe51j6VLSr9M3HhxLLvrc4F6qx0I0wZzT9ampjxXpeQWcetX1iEfGSHmTp3L+579GekHvz5NbPgXhyJgtt3wqSy+9ctR9HS4Jv8bvKKEDlfD2ZggGICKDMwVcDkxnn4KUa8yNV4uECD/7/6CrBaw2kGwgiojLL8ZcNs8QGwARbxM9Fa9gy5qJyZ6JEuzAljMX0WScZGx3+26aa1/HlT6HcLgNuyOfgLeO1PTppOcsNsSGqsp0eg8TkQPsPvwYIiYQRaYWnU9h1hIEwZgB4Z7OrbxQ+wh2yU6q2U1LsAlPpJObp91JiUu/iAiAoqls7Kik2teBKAhkmJ20Rjwsdk9imsu4Nz3vtNQSUhWWZuaxvbMVSRA4NavQcDl0nyzTGAhSbLfx34ZGZqSlMjtt4JnNwdIRkrl3fzNWUSDDJlHVE6YhGGFFlpMbp+UaZuedmgh1HpVCl4CmCczOFgkpAoWukQk2QiGNgF8jzS0Yek3koIrnsILJKWBLF1EiYBuBshGjgaZqaK0+hHQ7gmXos33JNX5DYzRUPZ/ZWsure5oQBYFpuS58EYUuT4jdTR6m56QQUTWyXVZyXDZqO3y0+MJ889wZTMnVL0Y2LqhYGxVsCXugeAXseRrSJ4O7KLqv6l2wuCCjFCQHNH0Ic64El3H3uiSjT6imBt977+M87VRUrxctHMY2dSqi04nc2YnS3o6UmYnS1oZlyhTk1lZUnw9rmXHlncYKVdV47b7dtFR2Y7IIdLcHEQA5BJI1WtUEEVxuC440K45UM231Pk752BSmLkr8372/u4uAx0NmUXTGXtM02murUWQZR5obV2YW/p5uAj09x9qMFklVzyMIXV60YBACRwqPdPeAx4u8YTvCRasQ46S3DZbw7vegbm+0Xg8AIogi6vtPoabnI7r1q5dpSphQ+wFsGVOQrKl4Kl7AnFqCPVffG5iTqT7wEK11bxKtRWQBNQRopGUuYvHqRYYMart9NeysfITKxtdRVQVJNKNoETq8lZy/9NdxZwQHi6ZpbGx+iw873kVFI01Kp0tpR0DgmZp/8aXZPzXExre2P8G7XYcQABMiCippJjt7exr4ytRzyLDoT2eq8/fwdN1BGgM+HqvZj0WKpmVGVI0zcooQDQo0OkJhNnd0UGS382FXN1lWK1NSjE3HCioqrSGZgz1BAopKmlnCJIpsavezqidIWaoxLzEsEmxsUHGaIdUqsLVJZW62gICJAoOCP03TaGpUaWlW6e6WAZHMLJGp00xYLMZcE5NNxJYJwXYVMgQsqdB9SEGUIGWSiCAmTsqnWtGOsqcNIdWKNDMLMW+CDP4/ogTDCg9vrGVLdSca8N6hNgIRlaAcfWm8q8GDAJhFcNnNKIpGitXEn986xJ3nzyA/kWf8AHoa4eDL0LIffM0gh6FwERx6C4Jd4G2KKniu+T6UroRgN/gaof1QMvBLYLRIBM8rr6B0dCKdczamjAx869YRCIdxLluGKT0dU3o6mqbh37KFzkcfw3X2GpwrVoy164aw5916Dm1sObEM8zGU4NF/gKc9jKf9eMG/tf/ZR9H0dOwJrOasaRp71r1F1Y6tTF68jJbDlfS0tWBNcTFvzXnklk+ho6GObS//l+xJZWQUFiVUrdIJMeMXuvcx6IgjFiEIWL7yaQTL8FOzQg/+CJor47YxXfoVpCmLhm1DCXup++8tRLqr+hyTHNmUXP6QIeUc3nzydDQ1XmVOgTVX6xNE2XX4Udbv+V3cNhevuIf8zAW67Hx63WpCqj/mcQtW7j9znS4bp739c+Is8wbg3oWfZk7a8NOJ17XU8u2d78Y8Pictk78uPkd38Lezq5uvbdlG8KSF6/k2G/csX0K6Rf/Nen2Lhzu3xheJ+fbcfC4odOuy87uNITY3xr4yN883s6ZU3wsfTdN4640wDfV97UgmuPgSK65UAwrFr4/QsiEqiyNI0bV/sjd6zJ4vUH61FTFebus4IfzkbtS9vQVepNMnYV5VOug+kjN+Q2MkZ/w8wQhzf/Sqrj7uv2kZZ0xL0JIOlW/DAx87UrB9EMz/OBx8Dfzt0e05V8FV/xgx95KMDGogwMEzV6N2HxlXCgKiy4V6RBjNdf75FP0hqrBefcOn8W/ceOzctCuvpOBn+l84jyVP/mYzTYdii8ANhht+tgJXZuKpegLc+4Wb6GltiXk8f9pMGg8cVztOLyjipt/fPRquAUlVT9T2rvhBH4CmIb8z/Aej6usaMOgDkN8euKxEPDyHXuo36ANQ/K14Dr2gq38AX8/hAYI+AI26imeHbUNVZTYfuGfAdut2/mzYNgDWNr0YN+gDCBOixlMxbBvP1G8bMOgD+O3BV4ZtA+A3++P/Pnd1t7OpY+i1tE7mvsrDfYI+gMZgkGfr6nX3D/Cb3QP7+ac9+j6Lqmlxgz6Ax/ZG0Ptiq7lZ7TfoA1Bk2L1Lv2KlEtJo3XRcC1VTjgd9AIFGDU/FIAeeY4gWlPsEfQDKe9VoIX1qxEnGhl++pK+UA8D//ne3AZ6MEW/8ePBBH8D2R44HfQC7noCmXcb7lWRE6bjv/uNBH4CmHQv6ADwvv0xg924CO3f1CvoAup96Crm1dbRcHRH0Bn0AT//uQ/2OjAHVuz6MG/QBvYI+gM6GOqp3Dq7CwHgg4QM/LRgaXEN/cOA2sYgM0oY8UEAVHzUSX0J3oOODIRIe3B90yN84bBuqpiArA3/f4RNHt8OgJzw4mfDuQbbrj7bQwGU8AAKKvmsfVgeW7ffK+oMMnxx7AO77/+yddZxc1fmHnyvj6+67cfeEeEgIAYJLcXf6aylQpS2lSqGlpUChuBRpgeJugUAgCcR149lkJVn33bF7z++PTUJkRzJnVgb26aefsHPPve+ZuTP3nPec9/2+/uiUDvAEk8Heh0/SIQvndLe/0yiVo8IX4rZ6o1CpwPQHreICgOHt/ZEZ+APcdxPw9X7HtY8jqWuV/4K3uGPY6XeH9/wPSphjSB+9B6OhIWQbs6UVs6WTeysEZnt79DsVY3hj9HffHqTcVTDcLfLOcncR846flpsZWtUT0GZELliiJmVCGMW5tTHHR2wDIL7/CSiWAHZUC/GBFD+PgqS08HIF+4+8NmIbumZjcN4pIdtNHHRdxDYATsz9XljtRqVGXvj88qLpYbW7OH9qxDYAzskbHPR4ksXGtDS5ciEAZ+R1Ho5qVVXm50RHpOa8wtAyzidJhnlqqkJGiJ/k7EJNOjQ2J1clLi7wNQYPkc8dtrgUEgYc+ihWDnqk6U5IiIEi7kqcFSX1yHwudUgaSlzs5nt8l/nZiUOkr3HNzCiUROgpptxwdO3Th8HBomUZIyA/OorMfXQfKVdeyRH1ew762zpwAM6JE3BOmoSecagStm3EcKwxXMoBwOaUH2/mXjksCj3pfgZPno5mCZ4W5og/tOyVxW5n4KTYye38VuT4mW3t+J5/q/OQT6uOfs5JaGHW+wtow9OG7/nbOxQ9j0BBmXke1kmhnZ1QeBtKaNryJkJRQAjaK5ahu9JJm3Qj1qToKEW522tZ/O5ZCLOTnUxFY8Kcx0lKHS5lwzT9bCh5meWbH8NvHr6zp3LMsBsZ019e7riidRe/WXkNrcaRqy26YuX+ya+SIikis7lpL9eufBpfJ0Gf8ZqNmwYezynZ8uI7T+1Yz/O7i3EbfjQUFBTsus4xKVncOHgc6VGq5be0ppYvqqpJtlrxmiY+YXJyTg4D46Mn8PLc9mqe3VZD+2GPF6sKZ+Un84Nh8k6mKQR/+sLDlroOIxa1Yw2oIBFm5Fk4tkDe8QNobxdsLvZRWmrSvu8NJSYqjB2nk5kVHX0s0y+oW2fgqTWJ76dhTVKoX2+gaJAyWsMahTzC7kD4TXzvbMYsaUCx6ahjs9An5qIcRU2Avhy/o6OrVT2/2FLF5U8u42jjAZIcOj8/aSgXTZYrddPjrP0fLPwzNO/tkDQEsDgABXxuwADN0pHPd+q9ULES1r3cIewy8WpwxmY9s+867Rs3UvnnOzFbW0i96ioseXk0vfU2enoaSRdcgJ7cUebDX19P5V1/wb1xA67JU8j48S2oztjMbTuYZ3+zmKbqyCLlJpxcyJTTo6Oo3hM01Vbz1t//TP3ePbiSU/C2teJuaUG3WRkwcQpzr7qB1e+9xYbPPyEhLYN51/2Q+NTuK9siO0Z+Kxy/Pvroo48+vh30OX5HR9/42EcfffTx3aGvnAPg+dfz0BxY5EOZMALr8dOkbPhryzD+/avADVQNyw8eQrXIydQ3bnqVujVPY7TXHJpUrqi4CmeTOf3XqFaXlI3iFX+hYserAY+nZE5h3Kz7pGzUN+/klUWXIkTnOSJpiSM4c/rj0rX8Htt8Jwv2vN7psf6u4dwx8Ulpmd2XS5fz9+2Ble1uHTyfM3LGSdkAWFxTzj2bV7DHfWQup13VeG7KyWQ75HflNjU28as166j2dKxea4CuqszOzODHQwfjlCx90uj1c/onWwPm16XqCq8dP1TKhhCC2z93s72h8+NTclR+NMkmZWM/G9b72Ljej8/XUas3MVHB3VH9hGHDdYaNkPu8DK9g56se2vd08ompkDldJ2OifLH4Pvo4WvyGyfDb38MbYfrvveeN4czxsVnIuVNWPQef/RXa6jrq93WGPblj7B5+Opx8977dwdim0dPIn5b+iS/Lv2RQ8iBum3Ibg5IH9XS3uo3ap5+m7ul/o6gqqTdcT/J55wFQ+v3/o+Wzz0BRiJs9G7OpCXdxMa5p08j6/e8O7ArGGtWlTbx0R+SLSUnZdi7+rdycuycpWbuKN/92Bz5Px46npuuouoW8YSM49tKrWfrKC2xf8RWmYWD4/CgKKKpG4eixHbt/Kd23+xcJsRE/FATPph1BnT4AsWIDRkVwlZ5QGM/9NngD08D37G+kbLir1lO95K8YbVVHKokJk9aST6hZ8aCUjbaW8qBOH0Bd5VJq9nwpZeetxdcFdPoAaho38OX6u6VsrKpdHNDpA9jRupF3Sp+XsiGECOr0Ady15T22NFdK2an3uvnV2kWdOn0AbtPg+8s/lrIB4DdNfrxy9QGnD8CgQ5Dlgz17eWRbaPXaUFywcFtQUZVav+CZrXKqZ//d4Avo9AEsrTBZWymfXF5WZrBqhR+PB0wTDAPq6gRtrYK2NsGK5T72VMiJ4pQv8HXu9AGYULnIj6+5Txylj+7n9Ae+jNjpA7j5pTVUN4cpjtbb2bsO3vghNOwK7PQBuOvB0wirnoXP/tJ9/etC/rb8b7xf8j7NvmZWVq3kxwt/LK2YHCu0Ll5M1V1/wb93L76KCvbe/lva162j5pFHaPn00wMDQ8uCBbQtW4bZ0kLzhx9S+Sc51fKeRMbpA2jY46Z6d+yInRyMp62V1/7y+wNOH4Dh9+Nzt7Nz1XJevuM3bPryM3xuN4bPBwiEEJiGn52rlvPhw/f3XOfDJOYdPxatCKuZuXmnnB0jDHWzBrnJf3vlqpBt3HtDtwlGVdknYbUr2x7cOQyGECYef+gffUWt3MNlaVVoR+iLSrkyC1vDdOhWN+6WsrOhsTak0mWNV14prKK9neYgyp6r6+ulbbSaoScEb5c3SNlYVRXaEfpkl7xKadXe0HYqw2gTjNay0P1s3BIdxdU++jgaNlfKK1KuLm2Q70hvYNdijlonuERuAbW3sHzvoWN1SVMJNe1Hlm75NtK6bNkRr7UtW07Lws+CntfWyXmxgDsKSr4AS9+UX0TuCSp3bMMMMkdqqa0NeAygbGPvL98S+47fxJFhNVP7S4abqGGoHLnktvVtaaEFVWxpckpJadnhqVRm5UeuIKooKroWOhw1PVFOQGZsauhQgvGpM6Vs9I8LTxhmeLyc4uaQ+OSQP8ZEi3zoYpbDgUML/F0elpAQ8Fi42MJ4qszKlAtZHZoa2sjUXHllstS00HbCaRMMZ2bo8+P7935Vzz6+fRSkyIcpjsyVf6b0CnIjUAbPHR/9fvQAo9JGHfJ3jiuHFPt3Q7TGMWp0J6+NxDEpeIqVffSooMd7KzZndDLAxs2LTWXTtIKiIxVdD8KZmBj0/MwBvT8EOuYdP9u4YWAN8UUdXIhW2LmMfbho59waso3l0j9J2XBmTyBl3HWgdZ4n6MiaQNqkG6VsxCX2Jy17VvA2SUPIKjxBys78yfcBgXPr4p15zBz9aykbUzOOZ0Jq4PeSYcvlnKKrpGzoqsalecFlem/odywjE+W+X+l2J7cNn0K81nkul47C/eOOk7IBHWUb7hgzElcnzt+U1FRuGCSvxPX09ODy7Q4FfjhMTmX3ytEWMoLMSYelKkzOlR/ACgpVho/QDxkH4uIUdB10HUaO0skvkHPKck+wYksJ/FtJHa9hS475R3UfMcjbN86QOv+XJw0hOzH2c9wAyJsI8/4ItsRD660cjmoFFBhyCswJogsQQ/z8mJ8zObujLEW/xH78ZdZf0MJZDP8WEH/cHFKvvx7F6USNiyP9lltwTppExi234Bj7jZq3fexYrAM7xk/npElk3XZbT3VZCkVROOPmsVLXsMdr5A2JzYUBZ0Iip974U5SD5kj7dSKyBg7mjJ/+msLR4/a9fui4nDVwMCfe8KPu62yEfGtUPQ3DwL+3Cmz7nCavF+JcWONd0uIeB+NpbujwZ7yejpmfUFCsFqyO+KjZEMIEIRCmDyEEiqqjKAqKGj0tHiEEnvZ6FFXH8LfjN7zYrPHo1jg0LXp2vN5WWt0N2CxOFFVFGCZWmxNdi47wBoBhGrT6GhFCxarZ8JkeHLoTixbd2mE17U0oAlRVpdHTRpzNSYrNFZWSAfsRQmAIgSFMVBR8poEQ4LJGvw6axzDQFAVVUTCFQA+yyhUJdW4vze1e0lx2vD4/1R4/RYkOrEF2HI8Wn2Hi2Vd4vsXjx2XVcFp1tCi/F9MU7KuwgqoqCCEO/HfUbPhNFFVBmOLAv6gd37fvEn2qnkdHd6h6NrW6KW9oJc6mo6oaKOCw6AjA6/MTZ7PQ7PHh8fpxWHUUVSEjwRnVsbfXYJqA6KjX52kGzQqmH3wecCSCpnekhgRYxItlfKYPi/rte1/hIAwDFAXlsOex6fWCqqLuE0UTPh9KiDpwsUJddTPNtW1YdA3NoeNu8hKf5KCtpZ3WZj8J8TYUhwoG+Nw+VF0jd0BqT3c7Kggh8Pu8CFNgtdsx/H60g4Tv9v/t93pRdQ1hikOOdyV9qp6AUd+I/8lXwH9kHozXakH7wUXoUZg4e1Z+BAufPeJ1YbHjm3gKlqlnSNswvC1Ufnkn7eVfgzAQhh8w0RypZB3/Vxyp8gV1vZ4mlnxwAX7P4bHKClmFJzNw9A+w2eV/vO99dQtlNYs7OaIwqugipoyQXxlZXr2Ifxb/Gk8nNQltqp27J/yXDJdcGGajp5VbN77K6sbSQ15XgCJnKv8cczGptujUwNvrbuVXaxaxvbURgUBXVJKtduZn9+Oa/qOiMpH6eE8lL+8uxW+aZDnt2FUNXVXpHxfH/Jws4iUHLY9hcsPi7WxvPTROXgNSbRo/GZHN1Az5hZLPd3t5fr1Bu7/j2j5AwcCuG8zI07h0pC7tNLW1Cdau9tHUZOJwKCiqwDQ67kFmlsqAATq6JTqTW1VXadph0FDsx11roloUHFkKyUMtOLNjy/kzdtTh/6ocPH5IsqPoKmqiHXVkBmryt2QH6DvCu2vK+eELqwkjdfcQNAUeumQCJ4yQr9nZY3iaYc0L0FAKDSVQsxWaK8HX2rEKZPhAt8OQE2HgSfDhL6G9ARxJcNKdMOaCHn4D8iypWMKyvcsYnjqcuQVzafG28Ob2N2n0NnJyv5MpTIjxOo1h4N21i8a330ZLTCLh1FNoXbSIxrffwb1hA3pGBrl//xu2fh11lr8NTp9pmDz+k8/xuSPLX599yRBGzJCLgupJfB43i/77DOWbN2L6/VgcDvxuD03VldhccfQfP4lRx51A+ZZiNnzyIc31dVjtDgZNmsLE08/BmRA8HLSnifkdP7Pdg+/+Z0Jew/aLa6X64CtegvneQ0HbKMOmYZ1/Q8Q2hOFj54unYHoCC6MUnvMqloTIHRnT9PPpK8Hz/HRrIlNPegmrLSliOy9/diH1LcGTe4syj2PexDsjtrGudhl3rPthyHYvzP4qYht+0+S4RXfjE4HFNVQUFs76ORbJ0JdqTxtnfvFGwOPjkzL454S5Ujae2VHCY9sD35c8p4OnphyDXWJX7vgPivGGeKz8cmQ28/N2E/RXAAEAAElEQVSSIrbx/nYfz6wPrtpZmAB3zoncyWhvF7z5mhtfkFz3tDSFE0+2RcUhr1zqo2pJ5+8p/2QLSUNiY53OWLMX31ubOz9o1bBeNR41LXCB474dv6OjK3f8vtxazcVPfC11jScun8jcYZlR6lE3Yhrw6GzYuzbyaxz7i5gO93y++Hnu+vquA39fOvxSvtrzFVvqtwDg0B08O/9ZhqTIL0j3VtybN1NywYWI9g5xNTU+HrP5MNEjRWHQiuXo34LC7QAP3hCeCGAwTrtpDAXDYm/3TwjB4zdeTVN1ZJUAnIlJXHXvI9iccmXXgiE7RsbWMnInGF+Ep+rpL98rZcf86ImQbcSmpVI22iq+Cur0AVR9dY+UjZqKRSHb+L2NVJZ+JGUnlNMHUFIp93B5dGt4cslPb/l7xDY+qFwf1OkDMBG8XC4/8Xq1dGvQ4ysbqvCbcgqS/9tdGvR4WVs7i6sjV2vb1uQO6fQBPLNDThHu1c2hSzXsaoJWb+Sf184d/qBOH0BNjaC6OjqlFmpXBn5PtatiR9XT9+WuwAe9BsaqPd3XmT6kuOWlNdLX+M0bvV/lrlNKvpBz+gCWPhydvvQQz248NMLphU0vHHD6ANr97fxvy/+6u1vdSsOLLx1w+oAjnT4AIaj6c+SL2L2JaKl6fvBIbP7u92zdHLHTB9DW2MDWrzqLdOs9xLzjR7g7E7Lx9uEUGpdd9Q8jh0+VzFtT1PDOV6OYTxgYuc9LCzNS2a5FvgpnCzPf0RqFz8sSIiwxGgGFWhjfUZlcPz3MnDdN8s2E+1PTJJ5w4ebvRSvHM5heRDiPn15DqO+P7M3vo9sI9/ccDIvMj7AniUaOXowLoByez6d28iD6tuf8KZbwxnbVFj3dgp4kWmONEqPP+Wjk6andlOsXKTH6RP4GbWYYcskK6FlyW87qqaFDCtUxcmF4zuxJaM7g5QPSp/xEykZa9lQ6MqICY3Nkkpk/T8pOZvLYkG2G5p8lZeNHw8NTUb1gwPcjtnFc+jAcIQY2i6JxVo68bPfZeYOD3pmZ6XnSAiyX9y8KenxQfBxT0yL/rRTF2YgL44F//eCMiG0AXDYy9IN1aKqCXY/88+rXXzugFRWI7GyVtPToPEbTjwnwPVMgfVLvHkgOxjK7KPBBpwVtvFzObR/dxyOXRFDC4DD+9r0j5fBjgoKpUCinasqxv4hOX3qIa0dfi3LQkuPVo65mXMa4A38nWBO4YGjs5zEGI/nCC1EPkvDX0juZo6kqGbfG9r3ej81hiYrzd/rN40I36oVk9h/YUdIhFAEWfBMzsxh0zNTodirKxHyOH+zL83vyZWhpO/JgcgLWa8+LSg6OZ9cGePVuEAeFdikquBJRZ16AZZj8zRaGl5oVj9JSsgCEiWF4UQwPloQCsufdjSWEYxgOpunj6wXX0tpQfMjrquqgaNhl5A86H90iH5+8ZMM/WV/yH+DQUDhVtTF9xE8YWiAvhrOreSt3rrmJBv+RRTWTLencc8wLOCxywitew88dm99hYdUmvBgHhkENlYnJhfx5xDk49OiobjZ5Pfy5eAkr6qowBNg1jWy7i7PyB3FqjnypBYDVdfW8uKsj5DPLYcOh6WiKQr7LybEZ6dgkVTcNIbh9xW6+qGk7UO5YAVwq5Lis/HxkLoMTQ3hUYbCpxuDR1V7avKAq0G50rGQl2OD4fhqnDJS/J16vYFOxn8YGE1ecgqIoGIZAmJCZpZGXr0ZV2bNtj0nDVj/tVSaaVcGZrZA4QMeWEltrdEZlC8bXZQivgZLsRNEVFJcVbWgaiiv4fenL8Ts6ulrVc11ZA+c/uoS2AGHTGh1lzQ8/6rRqvHzDFIbnJHVZ37ocvxc2vwNNFdBYAVUbobEc2msABTwtYE+EMRfCkPnw5g86hGCSCuDUf0A/uTqyvYFNdZv4es/XjEgbwYTMCfgMHwt2L6DR08jcwrmkOdJ6uotdjr+mhuaPPkJLTCRu7lzali2necECWpd9jTU3j5y77kRPlqvj3Nt49vbFNFW5Izr3nJ+NI2tA7H4epmGw8t032b1hDaZpYnM4MPwGVSXbcSWlMOiYqQydfiyVO7ayYeECGqr2YHfFM2jyNEYfdyIWu/z8JhiyY+S3wvED8De3YGzcChXV4DM6nLMh/bAMG4hqi54Uvmf957B7M3jbIC2vY2BIzcY2anbUbLSWL0OgYHjqMH1udGcWmB7i8qdGraSD39fKnt0LaGveTXtbJe7WPeT2O4WcfqegRbEMQmnV15Ts+Qy/0U6cLRO30UR++mQKs2ZGTep7Z9MWFu19l2RrBrtatqApVgYnDmdG1onY9OgpCFa2NbC4bjsFjhReLF1Gti2BU3LHMjgheqp1bp+Pf2xeDqZCltPBsZkF+ITJoLjkqMn6721zU+luwy9gcEI8jV4fPmGSabfjjFKIgtcwWV7bwq7Gdio9Pkqa29EVjbOLUpiWlRQVGwD1boFNNdlYK6hv86GqkGTTGZulo0XRIWtvF/j9JggFi0WhtcUkPlHBao3OPRGGwN8OlriOUhGeBoFmBYsrthy+gzGb3B2q9/E2lKO4F32O39HRHeUcVpTUsq6sAbe3o5TB2oomThmVRXFFM4oiOGFEDh8XV7CurJH+qS4MFOaPzuGYfrEn7nAEfg9sfh90B2QMBW8ruNI6lD09rR3Knw2lYEuA9IEdcw97IsTJRTX0dmrbaxFCYNNtxFujV86qt+KrqkJPTkaxWBCmib+6Bj09DaO+HqOp6YCq57cFwzD54PG11O9tpaXeg2btSJ3wGR0/CUeiiq7qNNV5sVohLtmOogrmXDiCzH5JPd39qFG6cR26zQaiYzcP00SzWNmzfQsZhf1QNQ27Kzqq7uHynXf8hBB4n/gf1DYGPF8ZVIj1bLmC5EbFNvwv/CFoG+20m9EHRR7y52utYtdLZ3Lk2uk3pE68keRRF0dsA2DD139i7663Ah4vGnEdA4ZfLWWjtnErr35xSdA2c8ffSf/syIuSCyG4YtFsPGbgVakTcs7lqsE/jdjGfs5f+jC73XWdHrMrOu/NuAW7ZE7IL1Z/zhe15Z0e0xWFP42czsyM/Iivb5omly35il1t7Z0eV4DL+hVxzcDgBdhD8equOu4trgza5s05g0iyRe5k1rYL/vG1hx0NgZ9fV47WmddP7p60tws+/9RDdXXndgYN0Zg8RW6hpGmHQdmHXox2sKaA0QbGvq+0M1eh39k2VD128iXMuna8/10L9fvehMuC9dyRqHkJYZ3f5/gdHV3p+NU0e5hy58f4I9Qv0lXY/Mf5aLGa57fkX/DBLyM7d+DxcMkr0e1PL6DF28JPFv6ExXs6BCxUVM4dci6/nvzrb2XdRm9ZOWU33oinuBgtNZXUa6+l/rnn8JWVodjtCHfHc05LS6P/m2+gp8Rm4fKD+fCp9Wz9KnKBExT4vwfnHNWCX29j9/o1vPyn33TU1Q7B6Lkncfw1/3dEjceuok/Vc+O2oE4fgNi6C7OuQcqO/+W/hO7LO/+UslH+znUEc/oAapf/E2GGVjQMRGPtuqBOH0DJhkcRIZQsQ/H+sltCtlm4+rdSNl7a8WhQpw/gw4r/Ue+RU5BcULkxoNMH4BZ+/rzpHSkbftMM6PQB+IXgT8WRl6UAeHz7zoBOH3SEa/17Zwmbm4IrywZDCMF9IZw+gFu+LonYBsCLG31BnT6Af6/1Y0oubK1d7Qvo9AFs3WzQ3By5qqfpFwecPgBv3TdOH0BbuaB2beS/957A/+G2b5w+gFYfvrcDlHfoo1dz+VNfRez0AfhNuOKpZdHrUHfiaY7c6QPY9jFIjgu9kac2PHXA6QMwMXlx84ssLF3YY33qSqruvhtPcUdajFFbS9Xdd+MrKwM44PQBGDU1VPxS4vvSSxBCyDl9AAIWPLMxOh3qId78+5/DcvoA1i54n61f924lz4OJecdPlIeeZAKIPdVyhvxHFgg/AlPOWfK3H5mn1hlGe2AnJBQtjdvDauf1BHemQ9HuCd1Hw/RK2VhdvySsdhVtJVJ2FteF/szWNwV22sKhwRf6+9Xql5NZLg7Todve0hqxjWafQTiuVmmb3HspbQr9QDYBSTM01Id+NzLlHPxt4oDTFwh3VXTKRXQXZtWR3x9R04Y42grgffQ4u2o7yZs/StZXyI0lPUZ9kLIk4VLyhfw1ehlb6zsvO7S1IXg5oljFs2XLoS8Yged53iA1cmMFv0QJpIPZsy1Gf/f78LQf3bOvencUnhfdRMw7fuqwgeG1G1AgZygujO17u5wgii1teMg2imZDd0WeO5CSeUzoRoqGzS4XrpCWODRkG7s1ScrGmfmXhdVuQMIIKTsX5IX+zE7PHiNlI80WOhcxS/L7dWJ26FxEFZiQEnlSdoJVxx7GU2VGutx7GZMZWoDGpkGcVS7UJCc39JvJz4v8MWqJV7ClBO9jwsDYUfQE0AYe+exQ+yfHdNjPd5XZg+XFxM6fGHl4eo+SPhTCLH8UkLFyaRm9kRm5nSudTs+Z3s096R7iZh0q0KO6Ao9dcbNmdXV3uhyLLTolSEbPyYvKdXqKxPTMo2rfb6y8snt3EfOOn5afhTJpZPA282ei2OVqrFguuwOC1XRTdSxXhA4HDUb+KY+guYJ82TQbOSfLFYR1uHIYOfWvBK4KpzBxzmNSNgBOmfIgdktg51HXnJw1/dmAx8NhcuZxDEsI/GNTULh15D+wa3ICL4PiMzkvd1LA46Pjc7iiSFL2G/jTiGkBjxU443lgvFy5kJNysjknP++QO6/Q8RBQgDSblb+OG0OmpCLVPycXYQ9S0iFBg9vHyU0Gzxmic8oAnaQAXbVp8MdZ8iJFI0bpjBilY+3kUhYLzDzWgkVC4EVRFArPsBLfX8WapJA8WiWuUEHROuacGVN1EgfGVi0w/fgBqGOywKqBRUUdnIrl9NALQX30Pu6/cDwDMyJfpBmQ5uLWk4dFsUfdiKbDNR+BfvhDRukouhlQ814Faxyc8CfICj43iUXOHXwuPxr3IzIcGTh1J0UJRfx11l8ZkSa3wNpbSb/lFpIvuxRLYQFxc+eS/9STJJ5xOpaCAuwjR6K4XChWK3HHzSHzN7f1dHejwuk3yZVgScpxMGau5GZLD3PhHX8jLuVQcSpV07C54lD2KZ8rikpydi7zf/gTcgbHznOuS8VdFEVJAh4HRtKRQnQVsBl4ESgCSoDzhBD1wa7THaplffTRRx999DzfFXGXvvGxjz766KOPo0V2jOzqGKL7gPeFEN9TFMUKOIFfAQuEEHcpinIrcCsgVfnSv7MM4+X3IVAOyfCB2E6bI2MCAM8zv4aa0s4PJmZgu/pv0jbaq9ZT8eHNCF9LJ0c1ck95FEeG3Mpa+fY32bTyjgBHFcZMu4e03MC7T+FgGD5eXPg9Wt17Oz0+qt/FTBn+IykbAP9Yeytf1X3a6bFsewG/H/84CdbETo+HS62nhfO+epi2ADmJ01IG8PfR50vZANjd2sjP13xOafuR9z5Rt/LitNOIt8jtYq2oreO+zVtp8vnQFIV2w0BTIE63MCk1hSsH9CO5s+2to6Cqzct5n28PKFN0ef9UrpYs4A5QXGPw1Bov5S0cklfo1GFcpsLlo23SoZ5NjSbFG/20twva2kzq9qXhWixw3DwL6enyj9AOgRcfjdsMOCh9RLGBI02lYL4FS3xsBmcYJQ0Yq/ag2DS0yXmoqc6e7lJvolvGR1n+vXgnf3y7GH8EOZr/ung8J4/K7oJedRN+Dzx/Huxc+M1rig7C4MBTx5bQ8Z/efTnUigZxmTD0ZJh+U0dNvxhnScUSXtv6Ggm2BC4ffjn5CfmYwuSlzS+xpGIJQ1OHcvnwy3Favhu/b29JCbVPP43Z3ELcnDm0r1qFv66WpDPPJO7YY3u6e9I01rbx3K+XRnz+sRcOYuSxMRriDRh+P6vee5PyzRvJHjSUgpFj+PTpR6gtL8M0DAzDj6bpgMDn8YAQKJpG7pBhzP/BT0hIkw+R70q6bMdPUZREYDXQXxxkRFGUzcBsIcQeRVGygYVCiCHBrhW0nENDE95HXgzdoe+dgG1AYfhv4DA8//0j7AmRvJyag+3yuyK24W+roeTFU0O2G3hl5D/I9ta9LH43dOH0WWd8iEXCYXru41NoD6GmOWv0bxiSH/r9BuLt3c/z3I77g7Zx6fE8MePjiG0AzFh4J6EkS64qmMG1/SOP7zeEybyFL+MJIhBkVzUWzDkvYhuVbjfnLloc9J0MjHPx1NTJEdsAmPV+ccg2vxiRxSn5kecSljSa/GphcEGcokSFP8+OPGzV6xW88aobTxAzZ59rx+mUcy63v+ihrSJwQr1mg2Hft8ecVLpZ1oT336u+8cqdFmz/dwyKPbiz/F3Y8euu8VGWxduquejxr6Wu8ezVxzBzUO+eCAXk8eOhTEKVNCEXblwJlq4t6NyVLNu7jGs+vAZzn8Jhqj2Vd89+lyfXP8kjax850G5uwVzunXNvD/Wy+zCam9l+4kkYdZ0L2OU/9ihxM2d2eixWePCGT6Svcfld04gLlIvRy1nw5EOs/uAbRV5F6aivGw7OxCSu+9dTaLpcKalg9OZyDv2AauApRVFWKYryuKIoLiBTCLFnX5u9wNFlUB6Gf32YSlLvfC5jBvZsC92mtkLKRMuuhWG1a9rxUcQ2tq65N6x2uzb9N2IbQEinD2DFlkelbLxS8kTINq3+Zhq9kauglrTWhHT6AJ4vi9wZB1hWtzeo0wfgNg3ajcil/V/eXRrynWxraWV7c2e7zeHR5A1P2fa5neEp2AZiSVloOyWNguq2yBXKysuMoE4fQOluOSVf0y+COn0AhgfcQUpK9FaMDVWHbsW2+TC3Rf5b/JbRLeOjLPd8JK/U+MLXAaJkejumIef0ATSVx7yy5zs73jng9AHUumtZUrGEt3e8fUi7T3Z/QqsvckXoWKF10aKATh9A4xtvdmNvoo8vzDE8FF+8FLsqrxs/PzSK7Gg2yNoaGygr3hDtLkWVrnT8dGA88JAQYhzQSkfYygH2rXR2+okqinKdoijLFUVZXl0dpBRDfJiJ5wlyKoKoYQgsSK7I687wVkWtiUUR23AlhFec2ylhI1yc9jSp8+Ms4RWEdmiRh58kWsIThonT5MSDMsNU7LQEFBQITa4j9OegAknWyFeq7GEWGk+VKN4OkGQPbUdTwGWJ/DfpcIQ+N5w2wVC0jv+HQpfcVewJFFcn36O4rlsFjTG6Z3yUJDcKK/bZibG56o+qgSYvEEWcfFh7T5LmOHKcTnWkkuo4VPgi3hqPNRqfVy9HSws+b9HTY3R3ex+aHh23IDVPcs7dg7iSIo9GAohLllPF72q60vErA8qEEPurTr9Mx0BXuS+EhX3/dlopUgjxqBBiohBiYnqQH5I+YiCEMVHVLzrtKLt/KNrcS0O2UWdeKGXDlT8dzRVccl+xJmBPHRSxjf4jrg2iRtaBqjnILjgxYhsAI4ouCNlm3vjIw2IBfjsutMLp5LS5WLXIJx7JVhdD40KXQfjnGDnZ7n6uRMYlBR8wpqRko6uR/2RPzc0mK4Ri52X9i0i1Re7EWlWVrDCcul+PyonYBsCxBRpZruDO0NlDdJwSjl9mlkpBYWCvzOmCvHy5R6iiKGROD/55JQxUscTFnuOnTchBOUgRUh2WhlqY1HMd6l10y/goyx/PHIUuUYZDAa6bFd5iY6/k+N/LnT/+MsiWU0jsaS4adhH9Evsd+PuU/qcwNmMsN4+/GZel4/etKzo/mfgTLOq3f2HHdcwxxM8/6cDfasI3C9CWggJSrri8J7oVNVRVweqQV5KeOL9f6Ea9lGMvvQp9n56CZrGQlBX+fGXkcSeSmte783q7WtVzEXCNEGKzoii/A/bPAmoPSl5PEUL8PNh1wslh8K3aiLl4FbR7QFUABQw/ZKVjuzR0Tls4+FsaMV66Exr2hXS6ksHTDnGJqN/7JZaE6Hj5TTs+pn7N0/g9TejONEDB37KXlNGXkDxSzrncT/GKu6nY8QbwTYVr1RJP4ZDL6D8svPp4oahvLuHjFbfS1FqBiQ+LFo+qquSnTeXYsbehhrOLGgJTmNy+8lrKWncwNGEcXuHGqtpRVIWzC65kUGJ05LS/rNnO3ZvfpdrXgrlvEV5HYVhcNg+MuxSrFh3J/ZW1e/lP6Sa2N9fT7jdQFUiy2vn5sImMTQ7tgIbDp3urqPa6KXQ62dTUTLbdjiFgVHIiec7oJOe/X1rL3zZU4QX2rwE7dZiXk8T3h2ZKObD7MYVgTaXJuiofG2sFwoQxmQpOi8rUPI1MV3TuSV2dic8rsNoExRsMGhtNhg3XKeoXvUmOp8mkYYOf1koDby0kDAXdouPKV3Flx1Y5h4MRpkCUNoJNR82KC+uc70KOH3Tv+CiDEIJ7P97CS8t209DqRSgKcTadNm9H2LndopGd6GBgRhzFFY1sqe4ofHzz3H788Lih6FpsChMdoKEUPrwdarZC5vAOsZbWaqjfAX43zPoFNJbBprc7wkNTBkDRdMgYChmxI/EeDMM0WFm1kgRrAkNSvkk5bfY2s7Z6LQOTBpIZrBTVtxB3cTFmSwuO8ePx7tiBv7YO54TxKJZvh/O74qNdLH1l+1GfN3B8KideJ1fXuDfQ1tRI1Y5tZPQbgDMxidINa6nYugWbw0FTdSWOhESsThcVWzbh87ix2u1MOu3sbnH6eruq543A8/sUy3YAV9Kxy/iSoihXA7uAyNUqDkLJTOsI+7Ro4PYACowchj56cDQuD4BZUwpNBy3AttaDqoPXg/C2R8WGEAJ/WyUCA8WejK+5HASomooWZihoOCiKzjdV3ABUTF8L1WWfRc3x0zQriqKjqVZsWiJeow3D76WmeRPNbRUkxsmrPqmKSoY1l53Nm1jd8CUuNR4FHatmod3fHIV30cGi6mJqDnL6APwIdrTWYGIC8pPzVr+PNY017GlrIc1qZ4+/FQOYlJzJgLjohQ7MycrAYxh8UV2D1zBZVd/AWfm5UXP6ANIcVpJsKqZh4kXBMARNfviwvIELilJId8qFxgK4/YKyZoNGL2gCajywpFwwLNVEieKjLSVFpbbWT3GxH4uukJmlUrLTxGr1kZMbpUFedMwZ43JUPE4BQkWzgade4MwSMSXsIvwmZllTx+NFgJqXgBKl8KFvGd02Psrg9Zms3lWP3xT0S4+jvL6dmlYfGhBvV9E0leZ2D++tb2Z/epDTovBxcQ1XTfeT4Izx8D/N3pGrJwwYdELHv2VfgSUeGsrgrZthxFmQNQa2fwLNFbDmeZh1a8hLxwqaqjEpaxLra9azoXYDCZYEylrKAMiPz6fF18KuPbvY3rCdLFcWcwrkVdR7A/76etwbNiD8fqwFhdj6f7OLZR/W4dQL08S7Zw+tX36JZ9cuXOPHYRsUeVRWbyF3QPyBZ/jRUFXW1CX96U5M06B40ae0NjRQXbabuooyrDYHrsQkvF4PiVk5WO12dq9fg6qpTDnrPDKKYieyoUt3/KJFqBVNzysfwLbdAY8rRblYzj0JRWKXwfPc7VBVErzRiFnYTrwmYhumr52d/z0JYQRWlNBcOfQ779WIbQgh+OTlqYT6Nc8550tUNfLJ84rNj7JyW3DxlVFFFzNlROQlHVq8TVyzeF7QNv3jhvLnif+O2AbAtIV/Dvnse3DURYxPLYrYxur6Kn6wckHQNveMnc3kVHlp9J0trdzw9XLajEOTuE/IzOQ3o+WL8F6/eCfFTe6gba4ekMrlgyLPfVlXbXDXYm/Q+3LeMJ0zB8s7Zos+97BrZ+cCLElJcOoZ4eWBBqJyiZeqpYET6lUbDLnShu7o/c6TWdeO99k10HzQMyzeivXSMagp4S0sfFd2/KJFV+74rdxVz9kPLZa6xiOXjefE4TFa0uGrR+C9oBuuwRkwFy6NfLzuLXgMDzd8dAPLK8P7nuXF5fHeOe91ca+6luZPPqH8lh8jDlL4Sr7oIrJu/82Bv42mJnacdTb+8vJDzk04/TRy//rXbutrtHnjvpWUFTdIXePqe2Zid8be7mdzXS1P3HgNht8XuvFBDJ4yg9Nu6Z7Fnt6s6tktCLcnqNMHIErKMUO0CXq+4Q/t9AFskFMOrV/3bFCnD8BorcDwRL6iUrHzbcJZwln92U0R2wBYue3JkG3WlfxHysa9G38Vss2Olk20SyiNfVJVHNaC143r5N7LPZtXhGxzZ7Gccuh+Htu2/QinD+DDykraO3n9aAnl9AE8sV1O1fOJ1b6Q9+V/xX5MyYWt1hYzoNMH0NAAVZWRf2ZCCKq+Cn6+6YG9iyJXc+1OjC92Her0ATR78S+K/PnbR89x3bPyDuWNz6+KQk96iPd/KXf+9gVQvTk6felB3tv5XthOH0BZSxmvbHmlC3vU9VTeedchTh9A/X/+g3vLlgN/N7z00hFOH0DTm2/RtnJll/exq5B1+gBevlNSEbeH+PTpR47a6QPYsvQL6vcc+V3ojcS840d76EkmAC1tEZsQvhCa7lHC2xTe5Mhoj1wSvaUxPInd1pZdEdsIIkZ3eMuIbQBUt+8J3QhoMSJ3lIsbwyvREXnRgA5qwwgVbvR2XkD+aKlyB/4+t/rlHIzuiiBo9YW2IwCfpB/bHkYEd3u7xHs2Cetn4Gvu/ZEZAKI5wHe0pXueoX1Elxa3/IKDz4iN726niChI2zeHN071ZqraOtUYCkpJY0n0O9KN+Ks6f8/+qm9UdH0B2gD4Kyuj3qdYoqUxOvOV7qa5JnKV5Jb62ChXFPOOn5KcCHqI/CpdQx0UefF2NUypfcKU/g9E8sjQyqEA1qSiiG30G3ZVWO1GTL4jYhuKohBnDy1E4rTJ5Sye3/+G0H1BJd0eeZjRVf3DK8Q6IUEuoffk7NAKWPPDaBMOp+Z2rlAVr+ukSSh6Qse9D+ehkm6Vy1mbnBM6pzI/QcEWZnmJQKSmKYTK1c8Ooy+BUDQFW0roPqaO7+p07Oigjeo8fFcd+d0Sfvi2cPa4XOlrTB/Yu6XNg5IhGfqu2qBgWnT60oPMK5yHVQ0/V1NB4dIR4c1neisJp516xGt6VhbOYyYd+Dvx5JM7PVdLTsYVy0Xco5BSPuuC2MxznHDqWRGdZ3E4yBkcG2JOMe/4AViuvwCcAWTqczOwXHIGSrj1/gKgX3tfiE7YsfzgX1I27GlDSJ95e+DCXopK3tkvS9mw2pMYOun2oG0y8k4gJUNOlenc2S/hCuL8OW3pXDDnNSkb0zLncXJOYJVTC1bunyxnw6FZ+dXA+UHbJKh2Hhh/iZSdGwaO4bKCYQGft/OzivjxkOikPZ2Zn8stQwaTYbWi0iFLU+Ry8ty0yVG5/uuzBxKsioIDeOW4oVI2rh5j4cR+KrYAP5VByfD7mfICMoqicNqZdpKSjnxDdjuccpoFq6QTO+AiK858hQN6S3T8q1jAkgC5x1tI6Bcbyp7a6CwsZw5DGZCMkulC7Z+M5cyh6GOio0jbR/fy53NGM3NQauiGARiS6eK5a6ZGsUfdzPWfQ+pBAnGqBcKt2ZqQAzcuAz3GxW2Afon9ePKkJzml/ynMK5zHSUUnMTJ1JCNTR3Jq/1M5pd8pDEwcSJItiX6J/Xj4+IfJcMZ2/cKs228n/ZZbsI8ciXXgQBLPO5fC555DtX5zPx1jx1Lw9FPoOTlgsaDGxRE/fz6Fzz+PFheeinFv5Pr7j5U6P3dIIsOnyS8a9QRDp81i1iVXYXU6UTUNZb9iu6Kg6jq61YbV6cRit4OioCgKaQVFXH73A2h6bCzQfivEXfroo48++vh20CfucnT0jY999NFHH98dens5h27BqKzB/9yb4O88Hl8ZPRjrfLkVDNPTiu+hG8EMnPOg3/AAmjMh4PFwqFpyN02bXqWzxB/VnkzeKY9hTciTsrH6y19RWxFYQdIRV8i0+S9J2SitWsb7y34Y8LhVj+fcY1/EaY98NRngqs/n0ma2BDx+ev4VXDTg+1I2/rn1Y/5T/nXA45OSirh/7EVSNgDO/fJNKtydC9Fk2508PPEE0mxy4cQAa+rr+dP6Yird7kO+ZQpw6/ChnBwgFDRcqtq9XPzZdgJldVmBD08ciipRosAUgn+v9fJRSeDsyt/OsDAkVf4Rt3mTn21b/FhtCi4XlOw0MU1wueDEk204ndELnKj41EvdegNFgZTRGtmzYnu3wLdqD8bCneAxUDJdWE4dgpouF33RR/cy8Ffv4I8wiTnOpvH1r4/HaY3RqUZzFdw3GvwRlGuyJ8KFL0BhbId6vrvjXZ5Y/wR7W/fi0B2c3P9kbhx7Ixbtmxj4enc9J796Mi2+FhQULhx6Ib+cLCmM00sQfj/VDz5I05tvYba2oiYn45w0Ce+WLZjtbQifH19FBcI0wNcxP3SMHUvh889JKcn3JNtWVPHBY+sjPj+9II7zfnVMFHvUvRR/uZD3HvwHIojYnWa1Ynh9HJirKwquxGSmnXcRo+ee1D0djZDY/FYehv/ZwE4fgFi7BaOyRsqG76lbgzp9AP6Hb5Sy0VK2hKZNrxBI7cF011P6duTlIgCa67cEdfoA2lt2UVn2mZSdYE4fgNffzCuLLpay8duV1wV1+gDeLH2aek/kCpJNXndQpw9gWUMJn1dvCdomFLev+zKg0wewx93GD1Z8LGUDoMnn45aVq9l7mNMHHd+6OzduklbCvG7xjoBOH4AX+O2qUikbH+00gjp9AL//4uiVuQ5n9y6DZV/5qK8XVO412bG9w+kDaG2FD96LnmhJ3QY/tasNhB9MH9SsMGjYHBtqnp1h7KzHeGcLtPrAbyLKm/H+Zy3C7P1RJn10cPaDiyJ2+gBaPAYn/ENO7bpHuX98ZE4fgLsRnjkD/LErbLSmeg23LrqVLfVbaPI2UdlWyVPrn+KhNQ8d0u6010+jxdcxFgsE/9n0HzbXxb6aKUDt409Q+9DD+MrLMRoa8O3cSeNLL9G+ejWezVvw7tiBcLvB6wMhQAjaV62i4tbYdXxlnD6A6t0trPwgcoHAnqStsYF37/9bUKcPwPB6OWSuLgStDXV89OgD7FzVuyMwYt7xEz4/hCFB71+6Rs5QW2M4vZEy0bjhv6EteBrwt0fuyOza/HxY7bau+nvENny+8BRU3d76iG0AbGlaF1a7t0ufi9jGE7sWhdXuyV1fRGwDYHFNaPXQsvYW2g05R2B1fQO+EBPvTyXUyNr8BnVhKG5+VhV5iQ2AryvC+xz2tsjprZaXB3+2tAZfdzgqGjYeaau+k9diBXNbJwpnzV5Etdy976P7WFkqX4y5rD5Cx6k34GuWO9/wQsXqqHSlJ/ii/AtEJ/Oaz8sOdeYbPUfOjx5f+3iX9as7afksskXwSM/rafze6Iw56z8ri8p1upvdG9ZKX2PHqt5dyiLmHb+Qip77UAbky9mRKGYeLo6sCaEbKTqaLTFiG6nZ4YWdpGZPj9iGxRJeoWZVkQtjS7AkhdVufOqMiG3MTQtPpWlyspziZrYjdPibU9Oxq3IiH0Wu0PdmbFJyxNe3a2pY8eOZwdRfwqAgMbxHV6pkZGxiYvB+RjOX25FxpC1nZhTk1XoIJa2T75quoiQGEOLqo9cRb5P//jkssSFM1CmBhNaOhpT+8tfoIQYkDuj89aRDX9eVIx+Es/JmdUmfuhvbwIERnWctkJxz9hCaJTpuQXqhXNpTT5GaJ6fQ3nGNyKsIdAcx7/gpioI6M4TD5HJgGSEnLauc8ePQjeaGVyohEMmjL0OPC156IGPGr1EknNDswhNR1dCz4WETfxGxDYCijLkh28wac5uUjbsnhS6anmbNYkRyGA51AEYn55FjTwraxoLK9f1nR2wD4MHxxwVVUFaAP46cjiKRFwdQ4HJxZf+igLYmJieTao9cDVNVFH47NrSa12MzIxtM93P2EAupIbp5Un8Fiyb3iBs8RCcvv+MamgaOw346M6KYg5c1w4I1+Zs7Y0tVyJgSopZEL0YbnYky+KAcXk3BcspgFHuM5nt9B/nyF8dLX+PfV04K3ai3cuaDcufP+hnEyZUt6knmFc7jzIFnohw0YgxNHsrN428+pN1dM+865O9cVy6nDTytO7rY5aT/6Ebso0cf8polL69j1U9ROgaGw1DsdvIelPzu9BCKopA5MF76OidcPTwKvel+0guKGDApciXiQZOmMnLOvCj2KPp8a1Q9Tb8fo3gbJMZjtrTBzjJwOlBHDcaSFp06QkIIvCs/gPVfgKcdVLUj7y9/CNaTrpeelO/H01CCp66E5l0L0F15ODNHoKgKrpxjULToTASb6raz4evfIhQbdlcK8YmDaKxdR/7A88jMi079Ga+vlaUb7kfXXQj8mKZJnD2NBFc+/XOOi9rn9Un5m3y6521MwyDLlQcC/IqPi/v/kAynnFDJfkpba3lzz1rW1+/GFAKhKDg0C9cPmM3wxOjYAPiispQNTbV4DD8+02RYQgrpDifjkrPQo5go3ub3U9rWRrvPIN1h48vqauZlZZEsWcdvP35T8H5pLR+WN+I1/GQ4rOxs9XNSdjwXD46etP/eFoMlZT48hqCmDdLsYLeonDTQgl2P3ufV3i7QdbBYFFpaDJqaIDtbjdp3+GA89SYoYEuK+XU5AESrF9HmQ0myo4Sx+9On6nl0dIeq5wMfb+G9dRXkJTtIi7ezp7EdU5hUNflIdVlIcFrolxZPRoKVVrefmhYvQ7ITOHdifpf8RroVIWD5U2DZF5WhWcGRBI2l4PdC1kiwx0NjBdRs65gTpA+Foqlgi11J/4NpcDfgN/34hZ8sV+fPb8M0eH/n+4xIG0FRYlH3drAb8O3dC7oFBYGelobR2IgwTTSXC29pKVpiIr66OsyWFlzjx/d0d6Vxt/l4/R/Lad4Xqq3bdTAEbQ1Gx0q0CuzLuLDGdUQ1OxJ05l46nLwhaT3W72jR1tTEzlXLSc3LJy45hd0b1pKam8/uDWspGjuRlJwc9mzZhM3lorWhnviUdBzx8TgTk7q8b32qnoDpN/C99Sls3dXxkLbokJQAqopityMSE1As8m/V+/Y/YWsnA2zxYnyZ/bCOP1HahuFpomrxX/DUFKNanLR7P6d5gw9b+igcGWPQouD4udtrWP7pVQjTDUB7E9Tv6YjZb6z+Gue8F4hPki8WvmzLI2wuf4PDcx8zk8eRmz4Ju1U+FGBn42ae2PpXDDqEPLa3f5OU3OJr4Jdj7kNX5T6zNp+Xa1c+Q6NxZK7KhrX/4cGxlzAkXt6Z2dJUx7+2r2GPuxW/MDEBZc928h1x/HbkNIYmyCmg7qeirZ3nS3axtqGBFp8fp6YxKCGBqWn+qDl+N321k3WN34gabGzt+K59Vd/O6T6D+CiEf9W3m7xU7Gdng8AUYNdhXQ1oiolN9zN/oPxunBCCjet9FBcbaBrEuaDd3fGIaRqgM3iIjqrKT2xbSg08tQJvs0nLLpO4QpX4Qg1PnSCuSI05J1C0ejE216I4ddRBqaiu2FYn/S7z6aa93PfJVnwmbKgMlp9ZdchfTotCktPCCSOCR7H0enYtgTUvgHtfTnp9CVjjof9s2LMamvZ0qDEpCh0zYqWjdt/4y+DEO3qs29EkyZ7ErqZdLK5YzIDEAWS6Mvmg5AMa3A1Mzp5MTlwOy/YuI8GawOKKxdS01zAxK7bXbky3m+aPF2C621EdTszmJpzTZ9D4yiu0rVyJouvoyUk4Jk7C39RI2xdfYhswgNRr5AT4egtfvbmd2tJv5jzeloPy6gVwUPq8d1+ue0uNnzf+sZZ5Vw1h8DGxWcdvP86EBEYcexyfP/cUxYs/IzWvgH5jJ5A7ZDjp+QWs//RjFr/8H4QQZA8aRFNVFf3GTmTKOeej6b07Uifmd/yEEHjveSqoqifxLqzXnifl/Hke/D54QogSDJqE7bTIlT0NTxM7/3MiAUViFJV+F7yHZo88x8/nbebzN0KH70ya9zwJSZGH473y+SXUNW8N0kLhshM+xmaJfEV0Xd0y7lgbXD1UQ+P52YsjtiGEYNpnd4Zs96+xFzMuKfK47sU15fxsTXD1uztGTmd2plz8+fLaOn6ycjWBJE8emDCOMSmR5/gBzP2gmGD6LgrwyuyBpNkjfzhWtZj8eIEn4PsAGJmm8Kvpcvlk777tpq428JtJTlY4+TSb1K5GxWdealcGfn4pKhSeYSW+KDZypcy6drxPrYT2jomCUpCI9dIxYX9GfTt+R0dX7vg9v7SEX7++QeoaPzthMD84Ti7VosdY+hC8f2vk56cOght7t8JfOHxe9jk3fXITfhG+uNi1o67lR+N/1IW96jpMj4eS8y/As2nT0Z+sqhQ8/RSuY2K3nMGLdy6lZld4In2BmHPlEIZPjm3n76kf30Bd+ZEiNSl5BdSV7e70nPi0dK795xNdWspDdoyMrWXkTjA37Qju9AE0t2Ju3hm5jYaq0E4fwFY5JZ+6VU8QVBlUmDRs+p+UjbVf/iyq7QIR3OkDECzb9C8pGw9svD1kGwODRXvej9jGvdvCK6Hwmw2vR2wD4O+bQk8O7t2yUsoGwNM7SoI6Sw9u3SZ1/XqPP6jTBx3f8HfKw1HJDcx/N/qCvg+A9TUCtz/yha2WZjOo0wdQXy+oropcOdRwC2pXB39+CROqv46dsg7G8vIDTh+A2N2IuUvufvfRM/zurY3S17h3QaixoBfz2V/lzq/dCu0NUelKT/L4usePyukD+PeGf9MWpsJ3b6P5448jc/oATJPaxx6Lboe6EcNvSjt9AJ8+FdvlPDxtrZ06fUBApw+guaaa3evllUG7kph3/PYXzAxJGCUfAuL3Rn7uUWCGUe9HSPbFb4RXU8g0uv49+w231PlGiLqK+/GYkcuJt4f5efmFXNkAfxg777I2AHxm8GuEKvUQ8vpGeH0M1Y/Q54fXTubthPlWpB4twoSQHixgGr0/MuMAnRV+C/fD7KNXEY2IoJgu2yiiIG1vxm5Jlv34jKOviWoIAzMKY1ZPIHxyNWCFp3vmjF1BLEQBdgemxMBu+OVrCHclMe/4qSMHEVQOEcBmRR0Sec6ampYH4eTWZcspFaaMuzpkm6Rh35OyMXrqXaEbASMm/07KjtMWWsls0tD/k7Jx5eCfhmyjoHBczhkR2/j54JPDavezgSdEbAPg2v6jQra5pt9IKRsAFxQFDxW9ckCR1PUznNaQP0eA+blJUna+NzR02HZhQkeeUaQkJqo4Q1TZcLogMyvyx6juVEgaGjqEM21c7KRja+Nz4CBhHSXdhdpPLny4j57h+lnypQgunBSbsvYATJRT6saVDq7o5Gb3JBcNu+iozzlz4JnEWWNT3Cb++OPRcyLPTU25/LIo9qZ70S0ariT5HLWJp/bukgahcMQn4AxQ2sqVFFgw0uaKo3D02C7qVXSI+Rw/ALO1Hd9/34Lag8KJbFbQNNR+uehzJqOEUb8sGKbPg++ZX0FjdecNBkzEdoZ8PLunfiflH96E2VbdUUNoX3iF6kglb/4jWBPzpG3U7l3G6kWBc+OGTfo9OUUnSdt5bdGV1DQdGSrktKZz0jH3kRqgRtDR8HH5Gzy+9c+dHkuxZvCn8U+RYpdTmNrRXMUlKx7vNAhXQeHWgSdyep68iteHe3byt83LaTP8h9hyKCo/GTqJ+TnRqQe1qq6eJ7fvYFtLCz5ToCsKBU4n1wzszzFp8pMUr2FyzqdbaOwkzDLZovLQ1H7kOOXFPrbXGzy5xseelo4SwyrgMUBTYUqOyvXjraiSioKGIfjyCw/lpQJFAYulY4dP0yC/QGXseCtWq5wNYQoaNhm015h4qk3ctQJbmkLiQA1fI8T3U3HlxUZ+337MmjaM9ZUoTgva6KyjKuHQl+N3dHS1qued72zkkUWRpUrccGx/bp0fXi3UXsuKZ+CzO8HbBoYPfK2gWjrq8zWWg6/lyHMUDQqmwWWvgxY7izbBWL53OZ+Xf87ApIFkOjN5c/ubNHoamZYzjZy4HFZWrURTNPymnyEpQ5hfNB9Nsu5sT+Kvq6Px1VcxWlpQrFaEx4tz8mTqX3oRz/oNCEVBS0zEOWE8/upq3OvXo2fnkHHzzTjHje3p7kshTMF//7SU+orIoqUGTUrjhKtHh27YyzENg1fv+h0Vm4txJCTSf/wk8oaNYMDEySz6z9OsW/ABpoCE1DS8bjfZAwdz4vdvwu7q2gUP2THyW+H47cfYtzUrhEDXdfx+P5qmRVVO2u/3YHg9HeqhmNDWAAkZ2GyhC3CHixACr7cVRdFQFBVN0xBCREXR82BaWqqwWBx4vR503YGigM3mjPLn5QZUWlsbsNs7PiNdt0b1vfh8PjyGp+NzMgVtnjZ0i06SIylqNgCqW1pQhcA0TZx2Oz7DwGW1YoliFW+vYdDu9WLXdcS+shEWVUXvpFaQDIZhYAIWTcNvGGhq9EsT+A2DJrcbXVUxhcCq6+iqijWaVc/3sf855vb7sem6tMN3OKZpoqrqATumaaJF+Z7AN+8j5iXwJehz/I6O7ijn4HZ7EULB6/PhsFtxe30gwBQCi6aB0rHgE++wUdfShl3XcNgsWKKgpt0r2L/aA+D3A2ZHnLai7ft3X2knvw+sDlC1jnJP3yJMYaIq6iH/ffBrByOE+FY/w/aPB3DkexWm2aXCHt1J895mfH5fR71sRcXAQJgCW5wNd5MbZ6ITd6sbHR2P34OqqSRmJqJ3wRjfUwghEPtSU1RNw/T7UVQVYZoIQNP1jv8WArUL5gSd0VfOATDWbcH/3uf7nLF9rx30rzKkH9Yz5QrR+rcsw3j7nwGPewD17J9hKQodshcIYRrs+O98hLcpQAuFrLl3E1cwI2IbAJ++ehymEVisxubIZMapb0rZWL/zRZZsvCdIC42L5r6Fyx75DpPX7+WyL4LXHEyzZvHAtDcitgFw+hf3Ue0PLu7z6cyfYZdwZsvbmjhvyTsBj+so/GfqKeQ65QqrvllWzt+LN3eaVjYoPo5Hj5koXS+wtNXDxYt2BG3zwqz+5DjlS0cYpuDptT4W7Do4Ht9PXhz84Vg7dl1u8rFqpZeN6w2E6Jj3HR72P2qUzpjx0VnEqPraR/VyPwhIm6CTGcPF2/v4drC9spm5/wiuNhyK1bfPIykKO/w9woY34fUbOnb5FHVfUm6YONPgJ5tjfsdvScUS/rj0j5S3lDMmbQxV7VVUtFQQZ42j2dvM+Izx3DnzTnLicnhp80s8uPpB2nxtfG/w9/jZpJ916hjGKuW//CVNr78BQmAbMhjXjJnU//e/qBYLCaefRuviJXh37MA1ayY5d92FnhybIe5vPrCS0vUNUtf4wcPHRaczPcTqD97hixefxdPayY5+AFRNY+ZFVzDx1LO6sGfyxPwvUjQ04X/3s0OcviPabN6JsS2wCk9IG8LEePuBkO3MV++O2AZA1eK/BnH6AAR7P5GQlgbKd74X1OkD8LRXsm39I1J2gjt9AAZvLblOysaNS0Pn7tV491JcvzpiGxsaykI6fQDnffVwxDYArv76w6DH/Qi+vzw8hdFAlLe1cXcApw9ga3MLT2wP7rCFw/eXloRsc+WXkavsHsyCEuMwp6+Dshb4X7FcgnV1lcGGdcaBR0tnud7r1vmpqZYXMGgpNaj80o/pAdMLVUv8NJfEvihEH7HNiffKOX0AJ0fhGj1Cez28clWH0wdH5/QBtNXA/y6Pfr+6Ebffzc8+/xmlzaWYwmRV9SrKW8oRCJq9zQCsrFrJH5b8gR0NO/jT0j9R567Dbbh5rvg53tr+Vg+/g+jR+uViml57/cBc07N5C3VPPIFoa8NobKT+2efwbt8OQtD62edU/VVuPthTCCGknT6A//5xqXxneojq3SUsePKho3L6oCM09LNnn6C2rLSLehYdYt7xM/cEyLk7vN32yB0/WhoIWmYhSrSVhVFvTvjDUv8MROnmZ8NqV122IGIb3jAcJYCW9r0R2wBo9NeF1e6d0ucjtvHfsq/DalezbxCMlOYwVNNqfXIqqMWNwRYVOlhWWy9lA6ApDMnN9iipVG6rD2yruFbOIaupDq+PNTXyjl/bniOv0dlrffTRnUhUQznA3ubIx6sepXJjR2F2GXbH7uQXYFfTLho9oUuxrK1Zy9qatYjD5knratZ1Vde6naaPj27htX1t75b0D0RTTeQq6AdTvyc2S3kA7NkaYSmPfezdviVKPekaYt7xU3MzQ6t6gpSqJ3HJHWEeXYyraE7oRqoFVY88RK5o5PVhtcsuPDViG1bdRTg3JcEpJ1STas0Iq905haHVUgNxWcG0sNpl25IitgGQpIcOhcqyyQkUjUxKDNlmerqcEA5AsjV0nLtLi07+x5DUwL/LUelyv9mMzPDOz8iQfza48o68Rmev9dFHd2KJwu80L8kehZ70AFmjQJMMR+8fxpjei+mX2I8Ue2AFw/1MyJjAuIxxR4R1js+QFz3rLSScEp7C936cEyZ0UU+6lsR0uXnGftIL5dJSepLcISNAIkc1Z0jvFrSK+ZmFkhCHfvrcDim/QG1GD0Eryo3chqKgn/2TkO3U80MXFA9G+uRbUB1ByiAoGtnz7pWykZV3LJol+IPcEVdE0TA5OeLZo39LMOdPVaycPu1xKRv/nPo6SggHM8fRj36JQyO2MTghiwJb8Dh9BXhxcngOdSD+PfnkoO/Epqg8PHGelI0sh4PfjhyOHuCBNiYpkcv6F0nZAHh0alHQ96IAz8+UV3QFmFOocerAI3NoBiTBOUPlcuRS01TGjtfZL0xnscLBInWKAuMm6KQEcT7DxZWjkT3Hgu4C3QnZx1qIy49dRbw+vh0s+tlsqfNV4L2bj41KX7odewJc8Dw49o2X6lHm6iXkwdmPRr9f3YhVs/KP2f9gaMpQnLqT6TnTGZQ0CLtmJ9Weil2zMzN3JrdPvZ3ChELumHEHuXG5JNmSuH709czvN7+n30LUcE2cSPIll3QkeysK9rFjSbvpJrTUVPTsbFJvuAH7qFEoTifx808i46eh54y9lYFTQpfjCsW5v5gUhZ70DKl5+Zz0/ZuJSwmtQXGwkI9utTLv2h+SnJXTld2T5lul6tlHH3300Uds06fqeXT0jY999NFHH98d+lQ9Af/23RhvLACf/8iD/fOwnjgTJUG+robn3qsDx/znDsF2/q+lbRieZmqWP0jz1rcP1PDbjzV9BHkn/hPVIrcV31hXzPIFV/ON9umhZPc7i+ET5URkAF7/4kqqG4+s46eg0T/7eI4b/wdpG39b+3OW130W8Phd45+hKGGIlI2NTXu4ZuVTAbM8ry+axRVFckqrACvrK7l19ee0mkd+jyckZXD/hLnSNqCj5MHdxZv5tLIKnxAowIiEeP48dgzJNnn1Pa9h8r2FW2kIkOs3Pd3FnROCF5IPh+fWe/l0l4G7QwgThY5duEQr/HSKlX5J8jtmzc0ma1f72b3bwDjstsTFw8mnWrGGEdoaCiEEexZ6adhkYpod78MSr5BzrIW4gtja+RNCYK6txKxoRi1IxPT6MZdXgMuK5aRBqCmOnu5iH0fBI59t4873Nh/1eXaLyl1nj+bMcZFH2/Q4QsDXj8KKp6F2a0cdv3BxpsGlr0N25ErfPU1JYwmvbnuVuvY61lavpcnbRF5cHu1GO5nOTH55zC/JT8hnQ+0G3tr2FtXt1Th1J5NzJnNKv1NivqSDv66OumeeofmDDzFaW9DT0kk47VR8NbU0/e9/YJrYRgzvGIAMAz0zE0t6GgmnnY5j5Iie7n7EeNv9PHZL5KJMgydnMu/K2H3/AMVfLuTjx/6Ft70NRVFIzsnD3dKMu6UZFKVjPigEmm7BYrUy/Ni5zL408rSi7iTmd/zMvTX4/v1a8AtYdKw3XIjijDzXwPOPq0GEeOin5GC74q6IbQhhsvv1i/E1BFY8VKyJDLj4g4ht+P1uPnstdOjNgFE3UTT0oojt/GfB6bS6K4O2yU6ZwKlT/xWxjYeK/8hnlW+HbPfcrC/Q1cjC/oQQTPvszpDtftT/eC4sOCYiGwBrG6r5/orgyeND4pN58piTIraxn4u+XEJp25EJ3E5F4YPj5XNSjvugOKQoxLEZcfxxfH7ENh5a4WFRWXDxk/vm2Uh3Rh6G2dYmePN1N/4gP3tNgwsvkXdkSt5w07yj8w+t//lWXDmx4/z5PtyG8XV55wc1Bdst04IWdO/b8Ts6unLH79NNlVz5tNy1H7l0AieOyIpSj7qZD26DJYHLOIXFb2ogyjV4u4PS5lLOfetcWn2BxdqsqpV7Zt/DzZ/ejP+wheprRl3DTeNv6upudhnC62XHaafj3bXr6E+2WCh85t84x42Lfse6gQdv+ET6GjMuGMiY2fILvD1B8Ref8u4//37U5w2Zfiyn/uhnXdCjQ5EdI2M+x8//WRiqiz4/5hZJ+fhQTh9AXYWUCXfV+qBOH4DwNuIN0SYY29eFLktxNO0CEcrpA9hTt1LKRjhOH8Dru/4dsY0Htof3AHxq9xcR2wB4dteRO6OHs7lZXnGz2u3p1OkDaBOCr2pqpa7f4jPCUgL8vOroZJIPZ0lFaMXLd7Z2EgFwFOzaaQR1+qCjxENjo5wdgOadgT+0qq/kr99dCCEwVu4J3MAQ+IMd76NX8dP/rZG+xt0fyCnk9SgrnpK/xoI/yl+jB3hnxztBnT4Ar+nl4bUPH+H0Aby46cWu6lq30Lp0aWROH4DPR8PLL0e3Q91EQ1V01Di/fGlbVK7TEyx95YWIztu69Mso96RriHnHj3BD06y9f8Ut3BBORY98h8EaZsF0Rev6gruhhFlCnx/e1zfZGnmicoY9PGUq29Em/h+Gq5tWhG1BRJAAEi1y/bCo4d1T2QCgcMQGnVY5K3qYH4XFEoXduCC3pRt+ilFDURQIEfqqOL4VGQbfCVw2+XsVjWv0GHoUFEnjw1Of7m049fDmIy6Lq/PzJVNSehrVKdd/1dX559LbsdiiE12ihjkX6I1YHJHde1WLjcicmHf89OPDkNtPTkAdXCRnKCk7ZBNl8GQpE7aUgbgKgodhWlKGYomLPGym37Arw2o3dvrRb3MfTE5qaEWn4UXnStm4alB4eYhzc0MXeg/E+XnhhW/eNiTy8hcA1/QPnQdySpZESZJ9JFgsTE3r3PkvcDoYmpggdX2bppISRs7bdYPlykZ8b0jwyaSuwMkD5CacRf004kP4/XFx4HTKD3AZEwN8Zipkzuj9i1YHox9bFPigy4I2OrPb+tKHHM9eFXn4+n7+cvboKPSkh5j3e7nzVQtM/WF0+tLNnDHwDAoTCoO2yXBk8ItJvzii5IOCwg/Hxeb73o9jwgRcM2dGdK6WmkrKpZdGuUfdgyvRhm6TH9PO+ElshrkCHHf5dRGdN+17F0a5J13DUeX4KYriFEJ0e1XGUDkMpseL79UPoLIO/H4w9oWBZaSgjRuBNmowSoidjnDwfPI8rO4kv85iRz3+SizDpkrbEELQVr6UmhUP46vbAfgBAXo8qRNuIHn4OdI2TNNk+afX01zXSYFRxcrkef8hLjHy/Kv9bNr9Jl+uvxtTeL+5vGIh3pHFtJE/Iz9dzlEG2Nqwnt+v/j5+vEccy7EV8rfJL6CqcvdeCMElXz3GDnfNEceSNAePT7iCXGfwkg/h0OL3cuf6pXxRW4F/n5SMCjg0nduGTWFWpvw92c+ne6t4Ydcudre1YVc1LirM59yi4IP80XDfxj28truBwwMyLcA/JuUzOlVebGlbvcF/1vto8Ag8frBp4DNhVLrCFWNsWKNQg8wwBCU7DXbu8FFbC6oKpgEoMHSYypixknW+DqK1zE/lVwYoJoqqYEtWyZiso9tjb33OrG7tEHfJTwBFwVhaBkl29Ml5KCFWgmM1x6+3jo+y1DS7mX/fImpbvZhhThesGozLT+bBS8aTFhejdfz2U7UJlj0Be9dC+SowvbBf6kt3gSMJ/O0du4PNewETVCuMOAvOerjjoRGjuP1uPi/7HFOYrK5aza7mXRybeyzbG7dTkFDABUMvwKJaaPY283nZ53gMDyoqYzPGUpRY1NPdl0aYJq2Ll9D8yScYdXVYigqJP/ZYQKH6gQcQHjdJ3/sevoo9oChYsrNQNJ242ceihVo17OW898gadqyKLPXjkj9OJjE9Nnc899NcV8tHj/yTii3F2FxxjJhzPPV7KtizpRhXUgp+rxfD78OZmISiKsw471KyB8kJCYZLt6h6KooyDXgciAMKFEUZA1wvhPi/SA1HE9VmxXrmPLxrN8OucuhfAHurUYcPRMtKi4rTB6BNOBFj2zJoqTv0QHoh6uDozFMURUFzpGBLGYSeUIDFlY1AIDz1xBXIK0cCqKrK8Im3sXbxL/C4m1AVFaszHWG4ye53alScPoBBeSfT7q2nvHI5Hn8zja2laKqVycNuiYrTBzAoaSS/HvNP3i39L6UtOxHCwCd8ZDlzuGHIb6WdPui4J/8cdxE3r36B8vZ6FEwMBBZFZ27GsKg4fQBxupUfDZmAa7uFXS2NNHjdeAXk2B2MTpavq3Mw/V0uTs7JYUJKEnZNJ80ePQcGYH5OAh9VNKD6oR0OuOUTUqxRcfoABiZr3DZDZXWlQWWzH11T2dVg0C9FQ4/SXEvTFAoKNYQQ9B9gkpikUlsraG8VZGRGN6zDnqGRM1sFzaRhvYnmEnjqBHrvLgl0BEIIUEAblo5o9SLafOgzC1HiYihm9Sjo7eOjLGnxdh66eAJ//aCY2mY3iU4rWYl2NpY3oekKI7MSqG3zUtXkIdFhwRSCZo/BoEwXibbY2q3ulNQBMPB4SBsCcRkdRd2byjsKbnqbYPRFsOsLqN8FeZMhZyzkT4L8yTHt9AHYdTsnFJ1Ag7uB4anDKUj4Rqyj0dNIRUsFPsNHcW0xx+YfS4ItgdKmUlzW2J7078dfXY1t4ADiZkzHX12N8Hqx5OZitLSQcvFFOI85BkXXafn8c7SkZFzHxG7tusMZPTuPHWtrA4m/B2TEsdkx7/QBxKekMvPiKyhZs4qEjEwKR46mpnQXM867hMSMTNqaGqku2UFjTTWqohCflk5t2W5ScvIOqe3XGwlrx09RlK+A7wFvCiHG7XttvRBiZBf3Dwi9ould+BXiq052r/ahTRuHPlPOMfM891uoCi6qohx7MdYJJ0ZsQ5gGu189H19zWcA2jryZ5M67O2IbAF++dwHuluDvZfbZi9Akkot27lnIxyt/EfC4qli4dN77WC2ROwFew8MPl55Bky+w6MmghNH8cfxjEdsAuHXNy3xWvyVom7en/ohUm5xDc9vaL/i0ujTg8XkZBfxu1HQpGwDf/3o56xubDnnt5JxsfjF8KGoU5LdP+3gzjf7g4iuPTi1iaKKcGmZFs8kvF3rorGqEAtw120p+opxztnWLj6+WBBZXsdrgnHNtaJKLSw2b/JR/7Ou0WozmhCFX2tCsvXswATBr2/C9sB5R395xEw4aXrTJeVjmDQh5jVjb8evt46MMrR4/0+5cQKM7coGhv39vNOdMjF60QrdSthyePClwGadgWJxw9YeQFbvlHAAeWfNIh4CL6Wds+lgemPsAL295mQdWPXCEqEtuXC7lLeXois6VI6/kR+N/1EO9lkMYBhW//CVNb70NQmApLMRXWgqmiXXQILzbtnWU+lCUjn/3oSYmMuDDD9ElUyZ6mod++AmdVJU6Kq6//1j0KJQ66gkMv4/nfnkLNbtLOj2ekJ5JU3XnAoaJmVmc9Yvfkprbdc+8blP1FEIcPiM9ynWArkE0Ngd1+gCMxaswq+uCtgl6vt8X0ukDEJ89H7ENgJadC4I6fQDtZYvwuxsjttHavCuk0wew+oubI7YBsHDN74IeN4WPNdufkbLx5u5ngjp9AFub1tLmj1xBssXvDun0AVwtqf5W62kP6vQBfFS1G9nyK5saG49w+gDerdjDUklFT4BmnxHS6QP4vyUl0rYeXuXt1OmDDn/j7q+ODP89Gvx+wbIQippeD6xaKTdCmj5B+YLOnT4Aow0qPo1g4tkD+Bfs6HD6gMMLXxpflWGWH/nd+zbQW8dHWf7y/iYppw/gF68GH597Na9eF5nTB+Brg9d/EN3+dDO7mnbx4OoH8e/zAlZXr+aBVQ9w/6r7O1XyLG/pKOPiF34eW/cYm+uOvv5jb6D5k09oevOtA06db9cuMDsGG+/Wrd84e4eNx2ZjI5V/jE0V1/14PX5ppw/g5b8uk79ID7Hmo/cCOn1AQKcPoLFyL58/HwU14C4kXMevdF84i1AUxaIoyk+B4i7sV9iI+vAmEuG265TWhsjPPQo8daEdDABfU4QSw0B7c3DnYj/NDXJSvH7DHbJNdaPcV2h7c3jnV7sjl4+v9jSH1a7WG1z2OhQ7W8Nz5n0itFMVjOLGwO+nLECZh6Nhb3t4zlY0ChRUtQZ3ghs9ctd3u8X+sT4o9fVyzri/TXSkDQXBU9f7660CiLrg36FQx2OUXjs+yrKlMrznXzDCWAfqvTSGN14GpCHysbo3sLtpN+KwFZxtDdswwxyHdjfv7opudTm+SMs4AJ6dO6LYk+6nfq/cXGY/DZWx+6yvKpG7hw175Eq7dTXhOn43AD8AcoFyYOy+v3scJTcT9BCpilYLamHkiTJaYpj5VbpcDkvCoFPCaufIiFwlLSk9PKWlASOuj9gGQKIrdOHOYQVnS9mYn3d+WO0KXAMjtlHkDE998oTM4RHbABifnBmyxIECWFW50IkTcjpXhNUVJaDa59EwID48IYf+Lvncn8khipqPyZALjYyLUwlH0XvIELl7Yk1UsacHv/vJI2NDEl8dEuT3oiuo/aOTD9vL6LXjoyznT5QvwJyZEN384W5lSHhjckCGSp7fw0zInECSLemQ184ccOYRKp6dEWeJ45gseVXYniBu9uzQ88oAJJ15VnQ7081kFiZG5Tpj50VPLK67GTVnntT5AydNiVJPuoawZkZCiBohxMVCiEwhRIYQ4hIhhHxcWBRQLDr6paeDI8CEMysNy4WnoIRb7y8A6nm/CtUT9Bvkip5bk/qROvmnBKxypmjknPSQlA3d4mLklLuCtolLHkb+QDn10LNnPIPLHrjsxNC8M+mXPUfKxuiUyZxVELw8xW9GP9BRWyxCFEXh6QnBbaToTn4z7PSIbQCoisID4+eiBXH/np9yspQNAJeu89uRI7DvSz62qirjk5O4e9wY8l3ydZdUReHXI4LL9WvA0zMjd8b3c+koC5OyO68G2S9R4aZJ8mIiJ55sIz4h8D0ZNkKloFDeKSs8w0rSMA1LAof+/BVInaCROio2HD99ViH6rEKU7HiU/ARIsoNdR8mNx3rJGBTXt0/gpTePj7KcNT6XG2b1j/h8l01jwY+Dlyjq1Zz5IAycx1FXvlI0GHUenHJPl3Sru3BanDx2wmMcl38cY9LH8Jspv+GMQWfw2AmPcXzB8eTG5WJRLaio5LpyuXn8zYzLGMfsvNk8dsJjJNqi40R0N7aBA8l/6F+4pk3FOWUK6T++BdfMmTgnTSLzt7djGzIExW7HOnAg1uHDQdNQLBaSL76YlEsv6enuSzP9e5H/5gEciTpTTpe7Rk+SO3QEx115A5rlm/HKFheHzekiMTOLmRddQXpR/0NEXKwOJ2kFRUw550Kmnde7vwPhirvc38nLjcByIcQbUe/VYXS1XHUfffTRRx+9gxgUd+kbH/voo48++ugWuqWcA2AHhgL/2/f3OcBOYIyiKHOEEDdH2oFoYFbW4vvfe9DaSUxxWhKWK85G1eTCsbw1ZYhngu/6WW95GkWRCy8r/eBmPBVLAxzVKDjvDawuueLXZdveYPOqPwc8rmpxzDl7gZQNUxi88Mk5tAbIr9NVB1ec9KnUbhzATUvPodIdWBDnxJwLuHLwLVI2ntm5mId2LQx4PFGz8f7Mn0jZAChurOWG5R92mv+WarXz8rTTsGpyOz/P7Cjhpd2luA0Dh6YhAK9h4NA1ZqSn8/1BA4mzyNl4r7SeOzfsDXi80GXl2Zmh1R1DsavB4P7lXvZ0kpLgssBf5lhJccj97mtrTD5b6KGtExuZWQpz59lQQ9SlC4eGLX4qFvgw3IACtmSwJqsIHyQO1kiJkR0/AGEK/J+VYKzZC14DnBa0oWnoMwpR7LHzPo6CXj0+ynL540v5bFtkG5iJdp3ltx2PRY9NdT/a6uHfp0NlBAI1iXlwxTuQXBT1bnUHQgieL36ehaULKUos4vrR15Pu7Eh72VS3iZs/vZmKlgo0RWNU+iisqpX8hHxuGH0Dma7gUR+xgGf7dir/9jfc6zegp6SQfOklNL31Nu4NG0BREIqCJSUFLSsL365dqHY7iWecTurVV6NYYruMyc41lbz70IaIz7c4VK77x+zodaibKf7iMz55+hHczYdqgyiqekDNVVVVFE3D7/lGTEC32ph1yZWMO/HU7u7yURHujt9SYLoQwtj3tw4sAmYA64QQcglOIQi1oum5+wmCqjBkpmG7Qi7u2nPPZaEbaRZsNz0RsY3a1U9Sv+rR4I0UjYFXfBmxDa+nkUVvnhCyXXL6VMbPvjdiO698fgl1zVuDtnHa0rn4+LcjtnHf+ttYUvNRyHYPTn6LVEdGRDY8hp/Zi/4ast2MpAHcPTa8nMPOaPR5OPnzV4O2ybI5eWXGGRHbeL9iD3dsCK45MTUtlb+OGxOxDUMI5nywKWS7SalO/j4p8hwAUwiuetuNN8jP3qrC06dFXjKivV3w6v/chwu3HUJ+gcqxc+RymFp2G+x8Jbi6S+7xlphx/nyflWAsOlIcQR2civW80BUOYnDHr1ePjzLc8+Fm7v9ETugrO8HGkl8dH6UedTP3joGGksjPtyfBz7aD5IJdT/Dk+if5x4p/HPh7WMowXjrtJZq8Tcx5cQ7eAIpUg5IH8cppr0gv6vYkZlsbW4+fh1l39GrwKVdeSeYvft4Fveo+HrzhE+lrDJ2RxdxLuvTR1yVU7y7hmZ/9UOoaZ/zsNwycGJ1a1Z3RXeUckukoTrsfF5Cyb6CT1M6Tw9xdEdzpA6iskbMRrratISe53rDxpdCNhIGQUHYs3/FaWO3qq5dEbAMI6fQBtHmqpWwsrQlvV/LxrcFzGoPxdMkXYbX7omF7xDYAvqoNrTy619MmZeP1svKQbZbU1NJuRK5E/05p8PIa+1lZK/deNlabQZ0+IOTxUJSXGUGdvo428pKFjVtCf97htOktmOs6l7o2t9QifLHzPo6CXjs+yvLcUnlVyj1NMfoRuJvknD4AdwNUrIpGb7qdD0o+OOTv4rpiSptKWVKxJKDTB7C1fis7GmNb2bL1668jcvoAmt5/P8q96V7aZOWw97Hpi8BRP72Z1R9Evhmxn+JFn0ahJ11HuI7fX4HViqI8pSjK08Aq4G5FUVzAx13VubBISQrdRjJ0TVW7Z7XOEhdYDOVgZMJJ45OHhNdQkRNhUJRwQh3kVgQdmiusdiMSJ0RsY0KYYTpW5EKZsu2h30sw4ZdwyHGE3v1KtliwqpF/v4YnhbfD5tDlQqKz4rp+NTkuDBu2KAgWWoKIxxxNm96CkhxAaCveCpL3vZfSe8dHSXISw1PpDUYUIqF7BosTojH2J+bKX6MHyI07tN8O3UGyPfmI1w/HqlpJc8ilo/Q01tzI75klN3IF+d6A1RWd+a5mi80fflqevBppUlZ2FHrSdYSr6vkEMB3YBLwK3AZsEUK0CiF+1oX9C4ka50QZ0i9oG23+LHlDzjDUqabIhZNmz/1L6G7kyymkpWVNBSX0YD7lxBel7Bw39g8h28wYeauUjTsnhFcA/tTCiyO2MTGlKKx2z028JmIbAKOS0hmfHDwc9cZB4ZXiCMTNQwcTH0SiWlcUbhk2BE0iRGdggoNwnvd/HpcXsQ2ANKfKlJzgj6+Z+XJORmaWSm5e8DczfZa8SmXqGB1rkCoH1iSFjMmxEyqmzxsAtsMWQnQVy4mDYjr8KxC9eXyU5YGLI180288fTg8d3tsr0XQ4/vdy15h2EyTEpiPww3E/JMvVsRhtUS38dOJPibPGMTJtJPOL5nd6jq7q/Hjij2NWzXM/tkGDSLnqqkNe09LTIcTzS01KIvPnsR3mqeua7Jo8AFfeNV3+Ij3A6HnzSc6O3PF3JCQx4ZQzo9ehLiDcHL9rgJuAPGA1MAVYIoQ4rkt7t49wchjM2nqMtZsRKIjkBNhdAQ4blmOPQbVGR0LcU7oZ/nfHkQd0O9p196HbI88n2o8QJlVL/k7ztvdB0VDsSWiqhlA1cub+BVtCdFYPy0veZfOKvyBML/BNuJrd1Y/pJ78QFRs+w81nq/9AfdNO2r3NWDQr7d46Elz5nD79Eay6fPkAgD+vupkNjctRABsOfHjx4eWM3Cu4YJBcPcL9PLX9cx4tPTLsc5A9jWemXBcVGwA7mxv444bF1LnduIWBqiiMSUrn1yOmEGeJTj2sRVXVGKYgzW7Fbwpa/X40VWFEYiLxUUpKf3d3LQ9sqiJRh2YD/AbYdJiQFscvR+dikdhVPJjyJpO1lT421ZrUtkN2HGiqylmDNTLjo+MsNTb4KSkxcblUdF2wZYufjAyVUaOtaFr0HJnWvQZN2ww0u0LSIA1FU/C1CBwZCkqMbZsIw8TcWY8wQXHoqOmusIVdYjDHr9ePjzKYpuD3b67ntVXl+EwDrw/2B+zqfDN6JNpVPIbAMAUKMDovkaeumozLFttCF7TWwLInwfBAw26wJcGOTyAhF3InQMZw+OoRaKnscPJMP2QMheNug4TevfIfCp/pY3PdZnLico6o3beraRdvbnuTnLgcThtwGlvqt5DtyibVIV8Ptrfgq6jAs3UrWloa9uHDMRoaaPnkE2wjRuDdsQPbgIFoSYl4S0pQrFbsw4ejRiMMpBew/ssyPnt2y1GfF5dq5fI7ZnRBj7qX0o3rKC9ej6pbqSrZTuHosQgTPO2txKek4WlrJW/YcHasXE5TdTUg6DduIv3GTujyBc7uUvW8CZgELBVCzFEUZSgQWBayB1AS4jucvt0VULoH6htB1/E7XVimjY3OjVi/sPPX/W6Myh3ohSOkTfjbamkt/QKMDhlB0erBLzygWGirXBM1x2/35v8iTPcRr3vdNbjb67E75Astr9n6DDv3LqRjmqDj8XfkSja1leH1tkTF8WvxNrOrZTMGHfmV/n3/KihUuyukr7+fJbWd5/C1ml6q3U2k2xOkbTT6PLxWtpUKdxuaouA3TFAVPKZJVJbg9lHgcvJOWQUlFa2MSExgeV09JoKbBw8hPjE6k7QWw8RjQvlBqSBtflhR1YLbMKPi+LX5BJ/t9rOt3gQB9R5o8MGp/QUpzuioCAohqNxrsnOngek3yM6BvFwdm03B64UwomfDonGHn4b1BvYsaNphUL3cjzUekkfoODJiZ7dvP4qmog1Mxahvx1y1B2NjNdroTLTs+J7uWlfQ68dHGVRVwe03MYXA8H/j9AGHKBDXuw/Nd924t5mtVS2MzZcfS3qUXV/Assc6cv5ME4QfENBQCpUbQJhg+kDQ8XrKgA5nsXwlJMR2AXcFhZWVK3ls7WPkuHIYljqMAckDGJE6gsKEQm4cfyN7Wvbw3s73WF+9HlMxObX/qYzLkItO6S1YcnLwbN9B42uv0/Da6+D3gxB4du3Cs2MnWkICeloans2bcE6YSPu69agWnfh589DTYjvc1dMWXHAsEC21Xlqb3bji5cPEe5KW2lpqykrZvXEdfo+byh3biEtOYej0Y2lvbqK5thpV09j69RL8Pi8p2TnsWruKrAGDcCb07h3vcHf8lgkhJimKshqYLITwKIqyQQgh7+mEQagVTdHYjPfRlwKLvNitWH90mZTz5/nHVfse+EEYNgPb/Mh3f5pLv6Dy458GbaMnDaborPBCHAOx4H+h1YbGzXqIlMzxEdt47sP5tPuCJ0fPHfcX+ufMjthGSfM2bl0RPIxTReM/sxdHbANg6sLQc7h7Rp7P1LTISxSsa6jmhhXB04GenHQiQxJSgrYJxfMlu3h4a2Ahmiv7FXHVQLnCq+cv3MIed3ARjyem9WNQQuQDw+5Gk18u9BDo6eXQ4J7j7STaI//NCyF47WU3bQF0aFQVZh9nJSdXzsnc+bqHlp2BRWJUOwy92o5mja1dP9/qPRhvH7pirE7MwXrSoKDnxeCOX68eH2UQQjD4tvfwGaHnCYG4enoRvzmtWz6K6PPECVD6VeTnF82EK+TFInqCVl8r8/43j2Zf8xHHzh9yPrdNuY33dr7HrYtuxTxMcO74guP5x5x/HHFerLH7+hto/eyzoz9R18l/6F/EzZwZ/U51A8/8+kuaa+VEXs752TiyBsTmos/TP/k/ast2R3ayonDe7X8mf/io6HbqEBPdo+pZpihKEvA68JGiKG8A8nJfUcL/9brgyp5uL8bmnRFfXwgR2ukDKA5PATIQ1Z/9LmQbf8MWvI2lEdsoXhE6jxBgzeLgDmgoQjl9AJ+u/rWUjTvX3BiyjYnBF3s/CNkuEB/sXRdWu9uKw1NLDcRjO0Lb+fNGiQkI0Ob38+S24Gprz+4skbJR2e4N6fQB/GpFhA/VfTy/wRfQ6QNoN+DDnXIqu7t3GQGdPuh45KxeJWfD8JhBnT4A0w21a8JUFu4lCCEwPjpygcFcXoGIVZXHwPTq8VGGd9bskXL6AJ74siQ6neluGkrlnD6AkkUd4aExyKNrH+3U6QN4cfOLlDaV8o8V/zjC6QP4ePfHrKsOb+zsrfjKyyNz+gD8fqrvvS+6HepGZJ0+gFf+HptqtiVrV0fu9AEIwSdPPRK9DnUBYcUQCSH2q5b8TlGUT4FEoNdo1opgs7P9bZol5OPD2BWNBqYR3ta64a6HxPyIbLS3BC52fkhf/F0/OTOFnLS7xwjvntZ6QpdKCMSutvAKF3vDLfkRgEZf6M+7yR9Z6MV+PKaJN8R3WVZsv8Eb3hVa/XK/qWZv6PObwmgTjPb20Od7JX8mYf7k8bd2zzMoagg6ird3dsjjR+HbkQcDvX98lKGisb2nu9BzhPnsD+s6SQXRuVY3Ut0WvNxSo7eRRk9jwOMNnoYo96h7MZqaQjcKdn5DQ3Q60s2EEwUYFvKVjnqE1nr5372nrTUKPek6jjrRRgjxmRDiTSGE3Cw0iuhjQxeJ1EcPjvj6Srj5SM6kiG0AJAw5M3QjxYIjc3TENkZMDk+lLH/QeRHbCJeBOZ0rg4XLef1vCKvdSbmRF1a/uig8RdgzssZGbAPgzNyBIdtcViRXDDXZamVGevC8gxGJcrHpQxIdYWUjXjlQLv/h5AGh16xmF8jlK/YPw8aAQXJhntZ4FS2MVNe0sbGV56eoCurIzCMPZDhR08MrwxKL9MbxUYaLp8hLmw/OiNH7nTMWrHEhmwXFngQ5sZnvdvWoq1ECPM2HJA9hROoIzh50dqfHs5xZTM7uugLW3YFt6FA0iTy9pO+dE8XedB/REiYZOSc2hY2GTJ2JLikIOXbeyVHqTdfwrSiqpBbmoH7vRLB3crMcNvQrzkKxyd1I7YePBm/gSMB2w/1SNjKm/BhXvxMDN7AmUHiuXEihzZ7C0Em/DdomNXs2g8feJGXn0hM+RgmyoZyVPI4544L3IxQn51/IrPTTgrb507gnsemRK3BoqsoDoy4K2ubE9OH8dMhJEdsAOCtvELcNm4y1k5+kAtzQfxRn5QXPjQqH344awRX9Ckm0WLCqCk5NRQU0YHpqKv+aFHle535emz0IR5AnyzkFSZzbT075bUa+zg3jdBKsRz7EEq3w2+lWBiTLPd6sVoVTz7DiOmjeqigQFwcZmQrTZlgYNVpeDGfw5TacOQqqBdTDNsKsydD/fCvWpNh7VFtOHYw2sxDibeCyoI7LwnZZbE6Cv6u4bDqvf38q1gjVa0dkxfHhj2dHt1PdyY9WQdLROr8KaDYomAY3ruiSbnUHA5IG8Oi8RylKKMKm2UiwJjAqbRQ3jLmBx094HEVR+OnEn/KbKb9hdNpoEqwJJNuSOa3/aTx/yvNYteioqfcUiqLQ/803iJszBy0lBSUuruP/8fGoCQlgtYLD0fGa1YqaloZ14ADso0eT/ec7SL0hvIXp3sgND8iVDUvPd3Hs+cOi1JvuRbdauewv/yRv2AgU7bCFXUUlIT2DlNx8EtIzcCWlHNgYUnUdV1Iysy+7lmPOPLcHeh4+YYm79DRdLVfdRx999NFH7yDWxF16mr7xsY8++ujju0N3lXPo1fiWrMb8fFngBoP7YTvreCkbnpUfw8IQappX34MtMfLQAGEa7PjPiQhfS8A2OSc/ilMi1BPg8zdOweetCdpm7rlySe3N7Xt54ZMzIYAEx0mT7iM/Y4qUDYBfL7+K7S0bAh4fGj+W302QS7S96KuH2dkeXKxm0axfoKuRh/0ZwuSsRa9TGyDXz4LKyzNOJ80mVz/gLxuKeX/PXvydLPgowN/GjeGYNLnduJdLarl/U1XA4wrw0bwhWDW5XaxfL2xnZ4AUE4cOv5tpIz9Bzsb777ipqQm8ODZggMLUGfKy1VVfealc3HlOXNpEjeyZsbN6bja48b+/FXNPM2phEpaTBqE4Y7yW23cUIQRDfv0uXol8nU1/OBG7NUanGpUb4LG54I8g19GeBNcuhNR+0e5Vt9DibeEPS/7Ax7s/xr8vh92iWihIKMBv+mnztWHRLFS1VeEzvxG5Gpw0mCdPejLmi7gDVP7t79Q98cQhOg96Tg6KrmO2toIQmG43wu0GTSPhpBPJ+fOfUaJUD7enKC2u4c371kpd4wcPd0sZ0y7h69f/x6L//vuoz0sv6s8Fv7sLqyM6Naq7itiLHzoMs74xuNMHsGUn/g3b5AyFcvoAnvixlImyd68P6vQBVLwrV5C8Zu/XIZ0+gIVvyIUuvrzwIgI5fQDvL5MLJQV4dtt9QZ0+gE3NqylriVzRtaytLqTTB3Dmkn9GbAPgV2sWBXT6AHyY3LRigZSN9yv28HbFnk6dPui4Wz9dtUbKhiFEUKdvv51rvgxcUiIc1u71BHT6ANr9cMeXcsorK5Z5gzp9ANu3C6qr5YR92ivNgE4fQM1yA19L7GTK+17biLmtDlp9mBur8b2/tae71EeEfO+hL6WcPoCZf/kkOp3pCZ48KTKnD8DdAM8ET0Xozdy9/G7eK3kPn+lD7Puf1/SyrWEbJU0lVLVXUd5SfojTB7ClYQs/XPDDHup19HBv3Urd448fIe7nr6jAt3s3Rm0tRl1dh7igaYLPR9Nbb1Pz2GM91OPoIev0Abz1wGr5jvQA21d8HZHTB1BdsoM3/t77S7jGvuO3MbwJpLkxcsevu8JhPbVbQjcKKmIfms0rwyvnYHjrpez4zdCqRm5vkJl7GKyoXRRWu5dLIn8Q37P1w7Da1fokVGOBlQ3BnSWAkvbOpbXD5eO9lSHbCKDZF3mJgg314X0Ou9rknKUXN4WejTZ5wZT47e7eHd6Md1OxnBZq8+7Qn0X9Jlm91e5B+AxE+aHfU3On3LOkj55jVZncMxqgulWu5EmPIQR45JQdkSi91NN8tSfyqJ9NdZui2JOeoemddyM6r+XThdHtSIyye33oBfPeyO71covfe7eHM4/vWWLe8VP7h1fWQC3MidhGtFSOQqHHdaKCF2XyBoapcKnIhZYphA51sFkSpGwMjA+vKPBxOWdGbOPi3KlhtXMocqFM/Vyhw2KSdbl7Mi45Kax2cXrk7yXcouwpFrnf1Nyi0I8uuwaqxG83LS28c4sK5ZQ9nZmhz4/vFxuPasWioaQeGuaiZsf3UG/6kCUvSS60HMAh+VvvMZR9Ii0yOFKi05ceYFhK5OIcuXG5UexJz+CaMT2i8xxjxkS5J7FJUqZ8CkRPkNlvgNT5SZm9X800NmYTQVCz01GGh7hRqYnox8jlxdE/DLXDk38gZSJv/qOEuiUpk38hZaNw8Hl0aDgGZ9YZcmWoTp4cvHjppME/lHaorxvySxL05KBtErQkRqccE7GNCWmFYTl1L035fsQ2AO4ZNxs9RCGE+yfI5aleVFTIqBDlGn40aJDUfXHoGidlh3boH5su93A9rshGfJC1BQW4cZJcnsWMWVbsIcau1DTIL5Rz+uMKNOKDVPOIK1RwpMo5l92J5YwhKCkdDoOSHYd+krwabR89w4e3hFfOJhif/GS2fEd6ivP+DWEVqOkMFc57Npq96VZ+ccwvGJ5yZAmheEs8Tt2JqqjY9SMfkEm2JO6dc2839LBrcU2ciHPWkd9/xeHoyOHTdVDVjgWCfdhHjiT9ph91Zze7hAmnyNedvPj306LQk+5n6IxjGTI9MlVTe3wCZ/zk11HuUfT51qh6mn4/Rn0jpt9A1S0oDhtGfT2WjHRUyVIOB+N590loqwfTD34/mAYMPgbbMXI5cQfjbijDXVuMYRrgc2NL6Y9i+nHlyEvt76e9rZqt656mtakciyUen78F09/OoJFXkJEnL7qyn8q6Yiob1mP4/DgdKbjsaeSmj4/qLmqzp4FVtV+yoWoVAkFOfCGKonB83lm4ZOswHbDRzqNbP2WPp5Ek3Y5AQ1MEp+SNY0xK9IrzVra38MXe3VhVnXiLlRafj1Ep6RTGJ0XNRqvfjxACj99PcUMTbtOgMC6OgQnxUbsvhmny+Z46Pi2rx6EIRqUnUekzmJOZQP/E6NX1avZ42VlvkhWn4zbA6zdJtKuku6InJtHe3hFm2dJi4PeZWG0qQkBioobFEj2HzPQL2qv9KFYDo11BURUcGRqaHjtO336EEOA1UGxHfx/6VD2Pju5Q9dy6t5EFG/fi9hi0eLzEOy0MSo9jT7ObFIeN5HgbjW1eSmtbqWvzYdEU5g3PYWJ/uXqdvYbqrYACNVs78rm8LZCYB+4mEH6o2QYFkyExH/ashtzxkBT7u14Arb5WTNNEURQURcGpO/ELP37Tj12z0+Zvw2f40BQNr+kl1SEnDtbbMNrb8ZaVYc3JQXg86CkpmB5Ph8MnBCgKwu0BVUGLi858o7ew+K1NrPq4grhEsNgVfG6B3wdeHwcKtOs2UBVQLSC8cNJ1o8npF/u/e5/XQ235bnSLDUdcAjUVu0lIzcDT1oKmW1FUOvwNRcWVnIxpmrgSk7qlb7JjZJc6foqilADNgAH4hRATFUVJAV4EioAS4DwhRNAkkHAGNqOiCv/Cr6GqBrx+QHQkLKUkoF90OppLLmTFNA1891/b4fB1Rlwqtuv+IWUDoGnHR1R9/jsQR+b0qHF59Dv7vyia3E5GS9MuvvogcIH2QWN/QUGAwqxHw3tf/Ziymi87OaIwLP8cZoz+mbSNj8te5/Ftd3Z6TEPn6VmfYlHlHP8WbzvzFge+t1fmTeO6gbOlbAC8VbaNuzZ3LlR0cf5Qvj9orLRj1uTz8ZMVq9nW0gJCYNCxnm1XVc4tzOfqAf2lbZhCMO+DTQTK7PnzmGxmZCdJ2QD4fLePp9b68ez7qahAkg0mZqt8b5iVOKu8E9vebvL1Ui97KgT+w376mVlw3PF2tAhrnB3M3sUeqr82v0nhVcESD9mzrCQOjD3HT4bvkuMXjTGyqx2/Jxft4A/vFEd07iWT8/nTWZLRNj2Jzw1PzYeKlYcdUEHVOib+IsCcIG0wXPUhOINHpfRmdjbu5NmNz7KhZgMO3cHQlKEMTxtOcW0xi8oXoaFx3ZjrGJ8xnmeLn6W8uZzjCo7jlP6noKsxquTaCUZzM41vvkn7ylUYDQ1oaWn4a2vxV1ZiHzEcLTMT/+5S3OvXo+g6yZdeQspFwev/9maEEPzrB58ecO6OlslnFTHxxP7R7VQ3Yvh9fPnic2z8YiHtzc1omoam6bhbWzhYZ0PRNFJz88kaMJjWhjosVhvTzr+E1NzwUtAiJRYcv4lCiJqDXvsrUCeEuEtRlFuBZCFE0PjFUAObsWUn/tc+DtoX60+vOrIY41Hgueey0I3s8dj+78GIbTRsep2aJXeFaKUx8MrOnKnw8PvdfPZa6G3s4ZN+T3ZR5LuYL356Hk1tu4K2yU6ZxKlTH4jYxhd7P+CBTbeHbPfCbLnSFFMXhlZpujx/GjcMmB2xjRd3b+b+rYdPLg5lYlIm902IXCK52efjtM++wAjymx+fnMR9E+V2lme9H3qSeO+kAsanRr7z99ZWL//dGFjwJN4C986zS+UX+Xwm/3vBgxlk8LNa4bwL5RaVdrzsprU08D3JmKaTOTm25cGPhu+g4yc1Rnal4/fskp385o2NUtc4b0IOfz13XJR61M38MQMMCXVgRYXb6w4JB4wVVlet5or3r8DoZBH6cDRFO6TdCYUn8PfZf+/K7nUbZlsbO886G++u4POZw0k443Ry/xKemF5v48Eb5JV4z/jxWPIGx2aO65M3X0/9nvKIzlUUhUv/cj/phV1XxkV2jOyJHL8zgP1aqf8GzpS9oLF4Veg2X0UuT2vU7gmvoVtOdbF2eThOkEF77eaIbaxfGl788cZlf4jYBhDS6QPYUxeiDEcIHt70x7Da7W6JXE7+ld3h9fHfpYsjtgHw8LbVIdssb6jEY0Suhrlgb2VQpw9gZX0DbYdvbR0FVe3esNrdtmJ3xDYAXt0cfDLS7IOv98gpYRZvNII6fQBeLzTUR653L0wR1OkDqFkup4DaR8wR9TEyUn7/lpzTB/DSiooo9KQH2PmFnNMHIExY9nh0+tPNPFf8XFhOH3BEuw93fUh5S2QT595G84IFR+30QeSqoD2Npz06Krxv3LM6Ktfpbqp3l0Ts9EHHbumXLz0fxR5Fn652/ATwoaIoKxRFuW7fa5lCiP2e1F6gUylLRVGuUxRluaIoy6urq0OYCWM1TWbBrdct1nXHm+l1b7oTwu2jxNe8m1Zqw7cSeX+Ubrin4X7S3fGxypoI+/yufi+x8FPsI1IiGiOPbnzsIyKi9ZBSYjNUW3a86I7xpo8+ok00vrXdVQkgUrra8ZshhBgPzAd+oCjKIRJJoiPOtNPlbiHEo0KIiUKIienp6UGNaNNDh5FoEqqeWkqY8qx2ufIE6ceEUdRc0XCkDo7Yxsgpfwqr3fDJv4vYBkCisyhkm5zUyVI2/m/ob8JqVxAXuYLkOfnh7aZflT8jYhsA3x84NmSbY5KzsUmEKx+XlYEW4oE0MSUZp0Q5hzRHePmUd06QE8T53tDgn0O8FY7JkZtwDRuhoYZ4QlqtkJQU+WNUURVcBcHvSfrEb0+uTB9HENEYeTTjowx/PGOk9DUunBSjIidF06ET1cqjQtFg4pXR6U83c8nwS8LO09MPU74+qegkcuIiL6HVm4g//nis/Y4+bC/xtFO7oDddj80RnbSCs34yNirX6W7SCopIyc2L+HxFVZl+/iVR7FH06TZVT0VRfge0ANcCs4UQexRFyQYWCiGGBDs3LHGXvTUYC79CVNaA56Ct6tRE9ItOQ3PIPcBN08D3z+vBCBDKlpSF7aq/StkAaC75jMqFv+40YVxP7E/hmc+gSCZNt7VUsOS9swIeHzLxdvL6nSJlA+DDZbeyq+rTTo4ojO53MZOH3yhtY1HFuzy45fedHtOx8u9Zn6JJfl6tXg/HLw6cr/D9gmO5rH9kNX8O5sOKHfy++Mh8RBW4vGgE1wyQF0lo9vn4xao1bGpqBiEw6ZhVOlSVi4oKuLR/P+nVKiEEJ3ywiUBBUn8fn8ekDPnabotL/Ty+xod7v7iLAsk2mJyjcfZQC84o1A9zu02+/spHRbmJ3/eNkBtATi7MPs6OqsrbqVzqoeor85tkeg2sCR3iLgn9Y3PHIFK+Szl+BxPpGNnV4i4vfLWLW19bH9G5180s4lenhFdvtVfi98HTp0LZ0sMOqKBZOkI5zX1icoeTMRyu/hBssVvHcnfTbp4vfp711euxW+wMSxnGiLQRbKzZyKLyRSiKwg/G/oBRaaP4T/F/KG0pZW7BXE4qOglN/fY8t4yWFpreeYe2Vasw6hvQ94u77N2LfeRILNnZeHfton3dOhRNI/myy0g579ye7nbECCF46IefdqYxGBYzzu/PmDlFUe1Td2L4/Sx55b9s/PwT2luaURUNzaLR3tz8zQQAUHWd9PwisgYNprWuFt1mZ9q5F5Oc3bWLHr1W3EVRFBegCiGa9/33R8AfgLlA7UGJ6ylCiJ8Hu1ZY5Rw8XkRLG8JiwWhuhspaSErEUpCFKrGDcTB+nxvjzQehfCe4EiApBRrqIKs/tlOuiYoNgJaKlbTXbgV0/C1lqPZ4rM5M4ouORbdFRy64tWUPG5f9jaa6ndjj0jGMNuLiC+k39HyS00dFxYYQgh1ln1BavQzT9GLVErDaHAwqOInkuMKo2ADY1lhMbdteNjauwKG5WFv1FenxhVw37Ge4LNH5vKpbm7h3ywfsaW8iTrPSJryoQuHCwqnMyYm80O3hrGuoosXjwQ/YFBWHxUJhXBIJliiWJDEMytvayHI4aPR62drUTLrdzqCEePRQW1xh4jcFd6/ZRbvfT4bTSrvXRFNVzihKY0CiM/QFwsQwBbVtJm0+k0a3H0VTGZpqxRoFpc39mKagrU2gaQKf18TjVUhL06IezuFp9tFaZhCXbwEBpmGiKhrWxNgstyqE4IDkqlVDCdNB/q44ftEaI7ujnMPykmreX1tOc6uPqhYvE4pSafX58RkmtU0+7FawW3QyEh3UtnoQpmD+6FwmFn0LpP2bqmDlM2CNg/Sh0Lyno5xDSzUYbkgdBJod4tM7FoZrd0DmcCiaBlrs79a7/W58po8mTxMWxQIqpNpTafG1kGBNoNnXfGDHr8nbhEW1kGBNwCKpPt4bED4fnpISrIWFqFYr7p070ZOT0ZOSOo4LgdHQgKKqqHFxmG1taPGx6+gfjN/v56N/r2XP9gY8nn1rkh5AB1UHuxUMA0wFfK0d5RzsDoXZFw6n38hOM7hiiramBjytbeg2G0011SSmp+N1t6MoKnHJqTRVV9JcV01yVh6qRaelrhZVQObAyCPywqU3O379gdf2/akD/xFC3KEoSirwElAA7KJDqrou2LVCDWzeVz9EbA2cfKuMHoJ1vlwhWs/jP4ammuCNppyDbdoZkdto2kPpK4F34gCs6aMpOPXRiG0ALPjfVELp9M484xOs1shVFzfvfpvP1wUWX1HQuOKkT9E1W8Q26t01/N/SUxGdRwsDkGnJ577pL0dsA2DWwrvwhfi8Ppz+Y+Itke8qr2+o5voVgZVpc+1x3Dt+DjkOOUf27o2beLM8sNjCjwYP5NxCuTDMm5fuYGVDcFGEN+YMIjmCGm8H80mJnyfX+jA7uf0n9FO4YrRkmBawfZufpYt9dPaYPGayzuCh0ZncbPhXO2aAj0y1woDzbdjTYscBNHbU43tzE7Tsi5BwWrCcMhhtSOj6Tt8hxy8qY2RXOn7VzW4m3bFA6hpPXjaB44ZnRalH3cxd/cAddHoSnJk/h7m9v6BzIP656p88ue5J/IdFICkoCARW1YrXPDIKSld0fjn5l5w3JHDZqN5O5b33UvfwI9+8oKrsV/uyDR9O1u9+R/lNN+Hfsy8dV9PAMHBOmULuPX9HT4lNRUuA1+5ZRsUWObHCHzwcuQJ5T2L4fTzz8x9RV14a2QUUhSvv+RcpOV1X0qHXqnoKIXYIIcbs+/8IIcQd+16vFULMFUIMEkIcH8rpC4WxfXdQpw9ArN2MWd8YsQ1/W3Nopw9g6SsR2wAoezN0XLC3ei2e5jBVRjuhpPgZwinO8tUH50dsQwgR1OkDEBgsWisndfzLFZcFdfoAKn2lbG3YELGND/auD+n0AZy1JPKyFAA3rgwun1zubuHeLSukbJT/P3vnHR5HdfXhd2a2qfdm2ZLce+/dxhjTQu+EHhJCCCEQSgjhSwiQEBJIaKEmlNBr6M3GNsYV995tWZLVu7R95vtDNmBbuzOaO1ppYd/vyfNhzZ177u7Mztxz7zm/09oa1ukDeGjHLloEVD2b/EFdpw/g16s6rpL2XTwBLaTTB/DpXo1NVWKqnj6fxvJl7Tt9ACtXBFBDDaADVKzwhnT6AFQf7H/PmFpqd0ALqkc6fQCtfvz/24bmE7sm3yci9Y4U4eR/Lhbu45qXwpep6bZs/UjM6QP48q/Q2mWXT4hV5at4csOTxzh9wDfv3facPoCAFuDu5XdT1hydiq7+ioojnT7guxLP3i1bKL3uum+dPmjb/gJaly+n6p8PRWKYnYao0wfw8t3LLBhJ5Fnx9uvmnT4ATeOl34cNYuxyomcJOQRqsTEnSC0pN29kd2ReXJq/xVC7lr3haxaG4+D+Dwy183lqTNsIBD2G2pVWH5030TEa/CFrGh/BsqrPTNt49+A6Q+1aQrwAjeLT9J3LnU31QjY21Btb/ChpbTVt40CLse+h2GC7UFS0aCGdvsPsbzBfZgGgqVFD77J4jN3qYWncrT9Of3NkcrEtodl3pNN3GF8Qrc4d+fHEME1Ns7i0uy8QRffud/n6GWv6qd5hTT8RZnut+bJR0OYc7qiLzs/u3aFfAipQWRnymGebfi3b7kpzgwUvNaC2JDqf9Qc2my/9dhhfi7G5fFcR9Y6fPMiYYqPSz3xOmTxUTLHRKEqCsXCYlCHmk4b7Dr/OULvE1LB6O2Gx2+KQDEhYDykUCwPJjzOmtHVyrwtM27imt36xe4BerlTTNgCSbfohg+PSxeLmp2Tqh9kpQJ9E8+GkfZOMhe6OzxDL88tPknDq3GJDs8TEBVLTJMKlB8syxMeL5/lljtUPeXVldm956CNIdiK1d32THEiZ1uV3xuh8+uWYD/c/TEpclOa5nWCsTmx4JMgVF+XqCibkTRAqyeBUnIzKGmXdgCJI3MgR6Ek6OweGzuVKmDLF6iFFjMQU8RQJgAGTsi3pJ9IMnj5buI/kTlRatoKod/yUvEzkGePC1txR5k1DElD1lGUFhs7Sb3iJsVIJoSg861WQwr8kU4ZehCIgMZ2dPx27K7y8tiQ7mTj3WdM2AE6fEv78eGc2YwZcLmTjvnEvEC+Hd1KOzz6LTJf5/JLhqb0odKXptnt54jWmbQC8OOlU7FLon+OszJ78asAYIRspDju3DB6ALcRvRQH+MWY0dgGBF6ci86sB4R3MBEXiT2PE4t9tssRtkx0khdC8uXaMjSJBURRFkZhzgoO4uGOPyTLMnWdNfl/aQDuuMBVjnBkSRWdaJ+7T2UiShP28oUi9U8Eug11G6pWC4/xhSErUv3J+UHz0q5nYBdZPFAne+2VkFk4tJ2cwFAiqNV/4Kjiic7FjQNoA7ptxHz2TeiJ/Z6ooIZFgTyDNmUaPhB4k2ZOIs8Vhl+3fHO+R0INH5zxKquCCaFehJCeT/89/IDkPLWQ6HEhpqW3/LcuknHMOvZ58koRp05AcDrDbUdLTseXkkHbpJWT+/OddNnYrmHqe+RJYh5l7uXgpmK5gxJx5DJg83XQdT0dcHFc8+IR+wy4kYuUcRIiEalmMGDFixOh6fijiLlYRez/GiBEjxg8H0XdklMZgHInW0ITvzU+g6qicL0mCfgU4Zk9ESksRsuFrqEV75obQDZKzcf7kb0I2AOq2vEnNivtDHs8/4xXi0oqEbBzY9TY71v4l5PG03GmMmR66bp0RNE3j6Q8n0259I6BX5lROGP9XZMEae7//+mp2NoeOyb5t6EOMyhIrFF/paeT05aHFWwqd6bwyWWzHD+DWdYtYUtN+MnyirPDm1NNJdJhXQQWo8Xi44KvleNRj88pS7TYeHjuWoiSx8K7WQIDT5+/EG2JNqTDOxgsz+wvZANhYGeSlzT6KG4+8yxwynDlA4UcD7MgWlFw4eDDIV4t9R+TzSTKMGasweIg1O3G+RpWDX/pxl6uogTZBF01tU4nPmWQjY2T0SaNrjV78n+1CLW9GzkvEPrcfksFQ4Bjdh5teWc2b68zlyA/KSeDjX8+ydDwRxdcCfxsIPhNiF4oTbtoG8dGp7qhpGu/seoclpUto8bewt2Evla2VBLQATtnJsKxhBNUgW2u34gv6SHYk86epf2J2gXioXHei/t13qX3qKVSfH7W1FbW5GdeQIeTd9xfqX3mFhvc/IFhdDZKEFBeHkp5G1jXXkHrGGV09dNM01bfy/G3mNRh6j87g5J+NtHBEkWfD/E9Y9N9n8B2leSBJMkigfWcOJckyfUaP5+Rf3oQjrvvv8Ef9jp/m9eF7+L/fKCq1S5wTx9XnCYV7eh+4VL9RZgHOS82He7YeXE3Zx7/QbdfvCvM/SL+vmcX/m6PbbtC4O8jv/SPTdp75cCpqO2pg36VX1hROnPCgaRuPbv0jX1Z8qNvu5ZnLTddcC6gq0xeHdpIPMy6liIdHX2TKBsDdm5fxUfm+sG0UJBbPMZ+vCDD9s/DqoQCfHTcTl2I+vmv2J1sJ6jxWJqTF8beJRaZtbKgM8pdl4QViTu5r48fDxBymhoYg770T2s60GXaKeostXgR9Gtuf8RBOEyl/ro10wc8SSbSAiveh5dD6HXGQRAfOX07UDfeM7fh1jM7c8Xtj9QF+87qY2MHsgVn854oJFo0owvwph7A/TD0kG/yfeaG0ruTx9Y/z6LpHO3zeP2b/gzkF+nOMaKDh448pu+HX7R+02SCMAnb+ww+RPHduJ42sc3n0Gv15gh7TLxzAiJk9LRhN5Fn9wTssfP7pDp+Xnt+LKx74VyeM6Ei6bTmHSKHuORDe6QNwe1F3FZu2EfAYVDmsNm8DoHrVw4batZaZf8lvWnGnoXbbVouVWtBz+gAOVC0VsvFlxUeG2n1Q/JJpGxsajMn6ft2wz7QNgM/K9csbBNFo8ptXwzxgUGnq8/IK0zZ8qqrr9AGsFFR3XFysXxZgwT7zZSkOs2VTeDubNoqrHjbvU3XnltVro6sMgrqv7kinD6DZh7q/vkvGE8Mcf3jXfCmcw3yxvcqCkXQBQb+Y0wegBaA5tPpjd+adXe+YO2+nufO6I3XPPhf6oE7Zo5pnLFKFjTCtjfrlmIyw9M1dlvTTFWyY/7Gp82pLD9BY3f2fd1Hv+EnxBnfxjLZrB8UeGWEFW4IxFSRbvHm1pKSUfobaKXaxQuFGkCSxHQybwfN7JfQxbSPF3o6yRzvIAupnAA6DO2wu2fxOXIrd2PeV7RT4rRjcWRUNwDQSMRhK+KUjJCSEH6nLJR5KqhiIDLFZYCeSSPHt32tSfPSI1MSA9HjxbBAlum7dbxFMQ/gGe/cP/WqPNKe+qFm75xkQQ4sWFANK2KGI1gLudpeYGvZhnHHW9NMVxCenmjtRknC0pwbXzYh+x6+gB+RkhG/Tuydyb/NbzpJi8AUw1XyZBYDsybcZGQyO1ALTNvqNuNZQu4nH/8e0DYCs5KG6baYMvVHIxq3DjOUhjsycbNpG38RsEiX9yert/U82bQPgjiGTdNv0S0jFLhCCmexwkKnj/GU5HUzINP/CUiSJ3on6DuZvh4qVpji5r40UHefvx8PEnYwhw2yE+8omTha3kZAvk1gUZnYsQY/joifME0DukYzc/8jnsjQoEzm38xeUYljH81eZf3Ye5m/nRmc5AyQJCgRl+TMHgjM67/lfjvklLqVji4BOxcmVw67spBFFnuwbb0Rytf8d2HuHLiclORzk/O6OzhpWp2J32PTE5Q1x5k1iKuRdydQLLkEyoW4+cu7JuBK6/+896nP8DuPfuQ91xXqob2z7gywj5WRimzgSuad5Of/v4n3j71C8/tgDkg3pkrtxZPYQtqEG/ZR+djPeg18Dh8O72q5RfJ959Jj5R2EbAEs/vhh307Fb8ZKSxMzTP0BRxEUYdh/4nAUbfne4Zw7v86Ql9uaEcX8jOUH8+2r01nPDinNoVY9Nvh+cNIb/G2tNvPXTOxbxTNlXx/zdjszrk35OjktMPAig2tPK9WsWUOpuRkIjQNs3Fi8r3DBwLCf1EJdYBnh5735eKy4m0+Gg3OPFqwZJszs4v3cBZ/USK7NwmA8P1HD/5kqODlB0AC/N7Ed2nLgj4wtqrKsI8MXeANVu8AZBBabkw0n9XKRZtEumaRpbt/gp3h/E7we/D3J7SIyf4MBut27trKU0SEuJimQHT62K6tVwpspkjbehOKJzjS54oAF1bx1y7zSUXsZ+I7Ecv47R2aqeHn+QGX+dT2XTkaG7Lhk8R2lExSngPvSjT3DIfP7rmeSlReeO1zdsfR9ev7JNcekbGSn50H/bgEDbv20uUFVQ3W27hac+BGMu7qpRW0Ktp5a1lWtJcaSwo24H66rWUdJYQv/U/pw14CwqWitYU7mGdZXrmFs4l4sGX0ScrfvveHQEtbWVujfeQJIkJJeLlq+WknrxRSSOH49n+3ZaVqyk9etVyK44HIUFSHYH6ZddiuyMbiGrBS9uYeuXJkSdFPjpAzOwO6NbO9Ld3MT6zz5g86IFeJubkGx24pNSyMjvhWSzUb5zG7JiQ1YkUrLzmHT2+eT2ERetM0JM1fMQSkIcWk4mWsahMAO/Hy0QRNUk67Y1c3q17/hpAXBY9LCTJFTfYec1DtRWUOJxZAwkY+RV1tgAJLn9VSybEm+J0weQkToAm5RIQGum7SXZ9tL0+VtxWBRKmuxMJdvZg33u7cccG5w0yhIbABWHr8lRpChxZDmSLLGhSBIjUrKo93poVv04ARWJwvgUJmWGr73YEYanpVDcmkm63Y5NkdnW2MTgpCRmZltXcDXRJh/j9AGk2CDVIifGJkNlC/hUiLND7xRoCkCiXcFhYZRJQ4NKfZ2GywXZ2QqyEqT0gEZpSZCi3tY5ZPZECXdlEBSNlAEKraWArInHxUYYrdmHVu+G9Dhw+5HS40DV0FQNSY6yDxMDCchOdFDZ5EcCEhRoDn7r9MmA45DOhTv47e2aFm8nTqQIYHfBlQrJPaC5AgKtIMe3vfPth96hsgQZg6GlCrz14Le1Hf8ekGRPotHbyO663aS6UilILODCQRcyOns0AAebD1LnrePKYVfS4mvh+s+vp95Xz83jb2ZCXpQK+hyFr6QEJTUV19Ch1L/1NvaiQjSPF/fGTajuVuLHjCH9kh/TvOQr3KtWkXbJJVHv9AE0VRvUtjgalah3+jRNY8+aVWxZvBDFZmfUCadSsn0LrQ0NtDTUoQaDuBITsMcloPr9NNXWsODZpykaMYqJZ5yLYuvenz/qd/w0TcP3/DtQXh26g7wsnJeeITQGQ6qew2bhPMF8mIOnehsl710etk1877n0mPUn0zY0TWXBG/rhO1NPfQ9XnHlH4LOvf8u+ivDKUGP7/YwxA81/X37VxyWLp+u2e2XWCtM2ACYvvFe3zQtjrqJfsvnwxVeLt/HQzrVh21zffzTnFwwybQPg6uUr2dbUHPL4dQP6cX6h+VBigDMXbKfGd2y5iO/y1zH5TMpONm2joiXIjZ/7QhQLaeOG8Q4m9BCbeC5a4OXAgdCfxeGAcy9wmVaNPUzpAi+160PbKTrTTlJR936ZAARWlhD4fA+o7VyZJAeOS0chp4VfJIvt+HWMztzxW7armgufFnt+3nh8f64/foBFI4owD4+Hmh3mz7clwB3tl+jp7myt2crFH16MXz1WwGpI+hBm9JzB4xseD3l+35S+vHPGO504ws5FCwY58LNraFmyRL+x3Q7+b7+n3D/fS9qZZ3bi6DoXK1Q9L757AqmZ3T/s8WhaGxt48hdXEvSZF7m56N5/kNfXmJ6GGWKqnnsOhHf6AA5WobaYVxH0Ner0f5hNC03bACj9SL+UQ+vezwi4zctDb/jKQB4hsOxDsXxFPacPYPWuJ4Rs/HGNsdp5m2vNT4o+PrjRULsr14jlRD62a51um4d1HEM9Njc0hHX6AJ7YuRtfOzX+jKJpmq7TB3DbmlLTNgAe/tof1ukD+Pd6HyILW3V1alinD8Dngz27xRQ3fY1qWKcP4MDH4uqhnY3m9hOYH8LpA2jyEfxSX702RvfhyudWCffxwOc7LRhJF3BwvZjTBxBogfIt1ownwvzf0v9r1+kD2FK7hSc2hH9/727Yze763Z0xtIjQvGixMacPjnD6ACruMr8439VUljRY0s+Ld6y0pJ9Is+Tl54WcPoAP/qFfAqwriXrHT6trPwTvGBpNFGA9TMU+8+d2AC1gzDkNthp0RNuhsdbYS0hVBWWsI8CBlr2G2u1oNOa8tceyuj2G2vkx7ywBBAw4KKJ786Wt+veXX9No0ZGpDnt+qEn/UYh9W1Dr1rfT6IOAgKGWFmOfpa5O7NP4m/TtqOareEQMrcWPXi0PzSKp8BiRweMX/aVGMXVi5Zm+oWKTNf1EmBpP+AVmzcAbaWddlDr9gP+g+Z1azRu9z7nSbXVdPYQupb5cfIfe3WTQL+kiot7xUwaGVlb6BgnkPPNhi47+RndUxcK94gtnGDBhx5FuPoF0xDRjSpg5BaeatgEgoR9i57SnCtn41eC7DbU7tcB8YfXbB51iqN3UNLFt/Z5x+iEROQ4xkYSpWfrS1EUJ8aQ5zCtVOnSKcx+mX6KYGubxhfr317hcCbuAlnxurowRYa9Bg8VCMOPzZGSdryOxoPvnxsmZ8Ug54e9jeYh1eaQxOp9JfcQl6VMskoePOH1nW9PP0DOs6SfCzCucF/KYhEROvH5qw7yi0H10d5JmzyaspHMYnIPEUjK6ktHHF1nST14/86kcXcmoE8XmvgADJk+zYCSdR9Q7flJSArYLT4WEEHkjDhvKZRbEWh+vL6xi+9W/hUz0OO4vyImhlS4lWyKFZ7+GJJm/bCnpA0nOCO/IKrYUhk38vWkbABfP+YBwt5ciu/jx8R8I2RiTPZXCuIFh21zV5xbssvlEa6ds44Ie48O2SVKc/G3keaZtADw/8SQK40KLxKTa7Lw4WaxkRILNxr/GjyHJ1v5EbFRqCo+OHytkA+CJiYVhj8dJ8O9pYgqlZw12MKuw/eqJEjA+T+LasWIJ9jabxMmnOghXlmfKdBuJiWKPUUmW6P9jJ7aE9o8nFskUnhYdYgGOC4ahjOuBVJQKRSmQaAeHAulxKCf3xzYmr6uHGKMDvPzTyeQlm1+kcSrw9R0nWDiiCOJMhJ8sQGiadP6LYIvO2pW3TLiFCwddSJzS9gCUkZElmay4LJ4+4WleP/V1RmePJsWRwrDMYSQo3z7AbJKN/8z7j3Duc1di79GDohf/i2vYUJT0dOSkpLYSH5KEnJiIvXdv7D17Ej9hPOk/+ylycjLYbLhGjqT366919fCFGDFXXAn/rN9EZ5r2gIlTmXmpeSHFAZOmMe9n11s4IuuJenGXGDFixIjx/SEm7tIxYu/HGDFixPjhECvnAARWbyK4cCUE2hFZiHNh//GPkNNThWx4926Ct/8ato10zWM44sVUjPa+fjbB5tDCF4mDziF38m+EbKz49DKaG7aFbiAnMOdscVWnpz+YgtauqD9IOLnypAXIstgtePHCKQRD2AC4rM9NnFQgtht32/rXWaSTq7Bs1u1CNtzBAJcs/5CDnpaQbd6Y8iPyDISEhuO1/cU8vOPY+o0AZ+b34MYh4iEqb++r5cFtFSGP24H5Jw4WtvPX5W7WhTAzJkfiN5M6Vny4PTZv9LJ2Teg8p8JCmD5LrJSLrzXA9ifaF1GwJ0Hvc5w4U60NzlAr/PjnN6M1BFFGxGGbEm/J6rymaXhf3Qi7DuWJ2CRs5w/H1jtNuO8YXcMlTy3jy921ps5VJFh351yS4qJz14uFf4WF95g715YAV38GOUOtHVMEqfXU8vslv+fL0i8N5fQdpm9KX148+UUSHCHCGKKM2pdepvrRRwg2NrXVagy2zTkcAweQctrp1L/8MsGmJpy9e5N9043Ejw8fJdTd2bashPnPiQkb/eLx4ywaTdfw+t13ULxxXYfPy+hVyMX3PIC9G5f0iPpQz2BZJcHPl7Xv9AG4Pfife0dI3Q/QdfoAtMevFTJR9tlNYZ0+gOZtb6AGzSv81VVtCu/0AagtbF/3sGkbAM9+PCek0weg4eXNxZcI2bhxxQVhnT6A5/b8nVa/yXo0QIW7QdfpA7hk5VOmbQDcuOaLsE4fwHlL3xOysbqmNqTTB/B2aRlvHygRsqFqWlinD8AP3LRyn5Cdt7b5Qzp9AGsqNN7dIaaE2dwUDOv0AezfD3v3iNXs2v5k6HH6m2D3K17x59d30AIa3ufqULd60coCBD5uIrjKvOrxd/F/uvtbpw8goBF4aQOaQdGfGN2Lfy/ZY9rpgzatn6n3fWHhiCKIp8m80wdtip5PzgZ/9xdKC8XNi25mceniDjl90KboeeWn5ks1dSdali6l4q67CNbUtql3Br+dc/i276Dq/vvxl5SgNjTgXreO4qt/ir+isgtHLI6o0wfw3z98ZcFIuoaV775pyukDqDmwnzfuucPaAVlM1Dt+6rqt+o18fuPqn+2gqWJy7UZpLTMmf1uz5mnTNjatNJa7V7LzFdM2APzB8GUDAOpbjClmhqLMbUzV86PSl0zbeHLfIkPtdrVWmbYBsMlAyRAV8Ancix+VHdRt83FZuen+AT4xKAW9qlbM0VhUrO9sLdgv5pBt3WLsu96+TbDUgs6cKugGb411jpNa6oemIx3a4FZrJqfq9nZ+BxqopdZIhMeILM8vFS+/0eiJ0mLmX4uV6AEg6IXS6AzDdQfcrCw3L8m/rVZngTlKaPzk0w611zweWpYu7aTRdD6tTdZISDeUR6+y6dqP3hU6v3xX91azjXrHTzKo1iklmldElOTIqJIprlRD7RL7mN9Cz8k3dq4rMd+0jTb0w8YUSVB8A2OKW8NTJ5m2MT3DWOFhm6Cia7Ld2HfhELgXBySHFo85TO9EsdCcsRnGfmdJNrHvq0eS/qOrIFns8ZadY2yMaWmdLGAggT3JOhtyunLMk1/KtCjqP7X98FrJ4H0Ro3sxpIf+M0OPqJ1k9J1lTT/pfazpJ8K4FBfZ8eZVeJPt0anqeDTO/h1X7Hb2LrJ+IBHClWBOyfT7RHZvMfE5V5L4c7Mzidpn8mGUkQORcjLCtpFnjEdyCN7MSVn6bYYaKMcQhp6nPqffSHYSlxFeyTIcA0b90lC7SSe8YNoGwInjHtRtc8rEx4Rs3Df2ed02GfYcBqQOM21jVvYgQy7di+N+atoGwF9GTNdt8+MCsfy7M3r1pDCMRGWSTeH6geZLhQBkxzvIdek7ES/OEHuwXjfOQTjf0S7DT0aJ5RUVFtmJ1/GDJQnGTRCzkzkx/B2WN8uG4rTO8ZOSFOwnJXF43UTKt2OfaU0ujuP0wRxdyUUemoUcH6U5Xj9w/nrOSOFJwl/PGWHJWCJO3ghwCeamzrgFkkMrdXdnJEniT1P+hEOv1kwI7ptxn8Uj6hpSzz0X18gQ97AkYevT54h/p19xBXGjRkVkbJ2BLEtIFvh+V/5tqngnXcRJv7gRWTG5yC5JnHL9zdYOyGK+N6qeak09ankVSBKSy4kaCCC1eFCG9hN3+g7hbW6EJ6/nmPLT9ngc1/3LMuni2s2vUbvhv6CpEPRBwAcOF9mz7ya5hzVid/t3vsmudcfmLeYVncOQ8dbdtJ+tup3qxp0EVS9Jzh40uvfTJ28uU4b/2rLv6+8bbmN17WLUQ/l+CjYyHbn8Zvj99EqyZrV1UcUO/m/rW6ioqPBNZuHkxEIeGHexJTaCmsp7B3bxWvF26nxuclzxBDSNPFcCfxw5nXibNffx/pYW3thfTK3XS4YzjiSbwpTsTIamplrSP8DeBje/W7OfMm9bdogD8AInZMdxx5giy+ysPehjV73GuNy26enXB4P0z1AYlWPdqmVdbYAtWwKgarg9EDiU5jFqjEx+T2sSuAOBAAc+9iMpoHnBmQZxOTaS+9hQHJ2zo6h5VLRWFTndeo0v/+4aKG9GHpGLktSx7yim6tkxIqHq+cnGMu5+bxMVTX4cCrQEIF6BeJdEvVtDUyHAt2pxNhlOHZXHfWePQjFY27PbUrIGXr4QVA3S+4KnFlJ7QnMNtFZD9hCo3gmSDD3HQ/laGHo2TP4ZuFK6evTC+II+tlRvYXPNZg42H8Qb9HJSn5MIqkEONB4gqAUZnTOaipYK1lSsoV9qP07ofQJKhCKlIoV3/36CtXUoycm0btqEJEmknvYjAHzFxaheH7aMdGzp4rUvuwONNc288LuOh/omZspcdvcs6wfUBexY+RX7N6wjOSObkm2bGDRtFi11tTTXVuPzepFkmcyeheQPGMSBrRtJTE1n4JQZyEYKAAsQU/U8hLqvlOCazW0RhnYH+ANtb5+AH2XsMCQrLsSnT3KM0wfgb8X36p9xXiCm7AjQsP8ralc+cOwBn4qsWpMrEQi42bXub+0eO7jvDdJyJ5LXS2z3Etqcvn2V87/5t9vXpsax5cBrZKUPYkBPsbp0AMWNu1lVe6R4QJAAFb4Sbl39Y56fsRiboHKoL+Dn9q1vtHflWda8n401xQzPKBCyAbC0qoz/7NtM9SExgEZ3EwD7Pc28VbyDH/exRh3uo9IyPig7iF8DpySRYreztr6BCwp7MSPHmgLbu5o9VHi1b76zw9H+n1a6GbS3knN6i9sJqhqbqjUW7lf53w6VeBvYbLCiLECCTaJ/hvjjzesNsGplgNYWDWccuFvAe+jD7N2rkZunoQgUiT+Mu0RCAtwlEGiG5r2ALYDNFaDXyQ4S862fREkuGcnVOS8oe98MghoEF+xF65eObWiscHu0snBbOT9/ce03v2XfoddQSxBaWo5cOD78hgqo8Maag4wvSuf8CUWRGmrn0FQBLVVAEEoPKUrVfCd/renAt/9dvwuQYcVjkFYAoy6I5Egtp7Klkue3PE9Zcxk763bS4GtA0RT+t/t/2CQbGXEZJNuTeXbzs4zNGYuiKLy8/WW21m3lpyN+SqJDTIW6q/Hs2kX9m2+ixCdg75kPskKgsgLPjh04C4toXrQY1edF8/pInDGDhvfexbNlK2kXnE/c8OFdPXwhXvqjufzO5mqVuoom0nK6d7hjOMp372LBfx5Hktrq8u3fvIGDO7dTvGk9qbn5eFqa8LU0Iyk29sXFsd4VhxoMkt6jJzl9+pHeo2dXf4SwfC92/HzPv4N2MIy4RmoyjqvPFXL+vA9dDQGdZFXZifMG8+qOtZtfoXblP8K2SR1xBZljf2baRjDoZ+Fb03Tb9R91EwX9zZdBePaT4/EHmsK26Zd3ErPH/MG0jW116/nDev0Qy1dmrTBtQ9M0piz6s267Pw86i1m55kMx79u6knfLdodtMzAxjX9PPNG0DYBzFn9FhTf0fXxSXi63DxsiZOOu9aV8fjC8mNK0zHjuHRe+0Hs4VE3jmo89NIfJQ79qhMKc3uZDDP1+lVdfCv+bl2U4/yKXkPNXusBH7frwQjI50xSyx0dPuKT/o50EV5d98295UCaOc4wtXMR2/DpGZ+74PTx/B3//TEyo4JThuTx68ViLRhRhPr4Vlj9u/vwhZ8F5FojEdAEbqjZw6UeXEtTMCYrF2eJ474z3yEnIsXhkkaH+zbc4+LvfGT/BphyhLp99221kXH5ZJ4ys83n0GvFyXpf9eQqJaeIllSLNxgWf8ukTDwn1cfpv7qDfePPaEnqIviOjPAYDNLcnvNMHUN+Iti98mYRwqJ4WfacPQBVTMdJz+gDqNxjIAwzDttX3Gmq3c93fTdvQNFXX6QPYdfAj0zYA7l5/naF2r+950rSN329621C727e9ZdoGwPtl+gqn25vr8Auoeh50u8M6fQAfHywXLh2g5/QBLKk2X2IDYENlMKzTB/DfzWJqvEsW66ubqSrs3ytmp3aj/vkVyyKjLGwVwbVHKsiq26pRg+FLY8Tofvzjc3F1ug82iikFdynLnxA7f4vYe6EreWjNQ6adPmhTBX11+6sWjiiyVD6or1NwBEeVFKt+9FELRxM53C2CKtWH+O+d0alsuvi//xbu44vnzSvvR4Kod/wwOJnQ/AJhkgJ186xHbFLu93a+rLoaofIXKsauaZ1Xv1RCKGr8+mUpQPSqYLhOUlDAKfOEqnV5xDjEP0skMKIQHxT8ID6DqtY+v6AhI4+waPOZ2rtPoyC6JMaRxMov/nC/AJH6t9/0ERDvo6tQPWIlbjR/d5o3Gkf1WzN/i9Z1vmBQ/PMHjE4euoiod/ykxHhI0JEKd9iR+/QybUNOSDV9bkeIK5yr2ya+l776YzgGjzdWxy8r33xIoaLYOUbarx0yksVUKi/vZ0yE5oqBvzFt4+FRxoRbLi8QU7AakaqvGptqc+JSzOet9U5KxKUT7jwsJRlZUHRnoAExj4I4sfy7MbkKetGVcwrFHm9TpxsTiOndR+yzJBoYZ+qQ6HpUy4WpR/xbyklAtn2/xB5+CJw0XDxMb2BOFOd59Z4tdn5O9OZ5XTlcrAC7jMzZ/c+2aDSRJ/2SHwudn3LG6RaNJLIkhCjJ01FOuy461XxHzj1JuI/xp55pwUg6j+9Fjp8WCOJ/+zO0/WVtq8qHJ4SyjNQrD/vJM5ESQsvYGyHo9xJ4+Bq+1XM8FueN+uUF9Cj+4Bf4Kle3eyy+z8n0mHmnsI2qgyvZsCR0WQdXykCmniD2WVQ1yLMfH09Qa3/FLyd1DKdN/ZeQDYAnttzLF5X/C3n8jyOeYmC62ANoScUObt76Rsjj01L6cP9o8ST+P29ZwfsH2w/57JeQwjMT5mETVEprDQS4evkqit3fFlCXgQRFYXZuDjcNHijs+Gmaxq1f72d5TftF2ovi7Tw/o+O1kY6m3qNy9xIvZS3f/k2iTdPppD4KFwwVz4krLfXz1ZcB/L62zrXvrGLGxcG8k50kJoo5ZZqmUb7ET/32IO1FSKeNlug5K/pyJfyf70bdU4ecn4RyUn/DSmexHL+O0dmqnte9+DXvb6wwde6wHom8f/1Mi0cUYV6+FLaHfseEZMCJcFH0hjoCLCldwpPrn6S0uZQ6Tx0BLXBEdIpdtqOgENACZMdn41Ac1HpqKUgq4K6pd9E/Taw8UFeiaRoN//sf9W+8iaQo2Hr2RHY68O0vJlBWhi07m7ixY9ECfiQNEo6bTd1zz+MrLiblR6eSccUVXf0RTOPz+Hnqhi9Nnz94eg7HXWyNGF1XsOytV1j9/juARlZBb6rLSvA01LcdlOVDoRDaN/+WpbZ3mysxiWkXXsrw2fqbOCKIviO/F45fjBgxYsT4fhBz/DpG7P0YI0aMGD8cYuUcAP+eA6ivf9z+wd49cZ4nvnXrfeVeKNsWvtGMi3GOm2fahhr0s+f5mYRL6Mk7/gESek0xbQNg/usTddvMOde8EiZARe0m3l12Vdg25818nZRE82UQVE3lokWTw7bJdfTiH1NC79YZ4fSvHqIyTK6fBCyecavQblyT38uJi8MLATwz/gQGJWeYtgGwpraWX61e1+6xQUlJ/HPcaOJtYo+Fp3dU8Pye2pDHk2V4b+4goTqOqqbx8488NIVIo+ifJnHDBCdpLrHdy7fecNPaEvr40GEKo8eK7SyqAY3dL3vxVLe/CJc5QSFvanQoempuP/4PdqDuqkXKjMd+8gDkHtEr6/1DR9M0ev/2Q6E+XvnpBCb10Q9l75Y8dybsFVA4LJgOV75v3XgizGvbX+NPy/9k6twRmSP4z4n/waFEx7OrPYKtrew7+xx8e/d++0ebjaxfXU/aeedx8M7/o2n+fAgcmXQuJydT9OorOHv3jvCIreHFu76ivkxMrPAXjx9n0Wgiz/rPPmT+v59AM6FXMWTmHE669tedMCrriK7EkRCob3wS+uDeEoLb94Y+boBgwK/v9AEsflHITulH16Kn4nBwwS1CNvZsNqYK+uX7ZwjZ0XP6AN5YLFb4/LJFs3TblPsOsLdph2kb+5qrwjp90Lbhf9mqZ0zbALh0ub7C6VWrPhWyAXBjCKcPYFtTE4/u2CXUv1/Vwjp9AI0qPLerUsjOk2t8IZ0+gJ11Gs9uEEuw3rzRF9bpA9i8KUhjo1gWe8mnvpBOH0D1yiC+5ujIlA98vgd1WzUEVLTyZnxvbhZWiY3RdRz/94XCfVzwpLl6YF2Ou1HM6QMo/hKqxJVRu4Ky5jLTTh/AhuoN3LvCmIp4d6XsxpuOdPoAAgGq/v4AB//wR5o++eQYpw9AbWyk+Er9OVB3RNM0YacP4N+3mQ8V7Uoaqyr5/OnHTDl9AFsWzWfHiq8sHpW1RL3jp/kDumpxwR1ijh/7N4udbxBvjQHnUg0Q9OqXSgjF/u3GHD+f+6B+I0FUTWxi7sfYw2nhwfdM23hm3xJD7fa5a0zbAKjytZ8PZyWNfn+YDNU21tbWCdkobTV2TeeXG1NLDcXaCn1HaHuNmLO0c6exB/+BYjEVsNYy/XE27YkOx089cJRqcIMXGsUnETG6hj2CZVeimjVipZO+YbW4PHxXsKFqg3AfX1dEdwiye9OmkMdadcKrAwcPonVzdcf2KN9rjfK7uz46VU3LdhqYh+tQsjX0fdMdiHrHT7LbQCdkTOlfJGakMDJJqs70AfqNJBuK03zoVMEAY7tsdmfnF12VJWOqiaGwYSyEZGbuKaZtXF6gX+weoCAu3bQNgAx754t3JNvtulqro9JThWzkxxu7JrMFlf5GZus/uvqniz3e+vUzFrrbq5eY4E58nv44k3pHx6Na7pl85B+SnWBA5TVG96QwQ0wULaoZY1Hx7TGXW9NPhBmeJa5IOjp7tAUj6TpcQ4aEPBY3dkzYc5XcXCRH9IW55hQl6zcygCs5OjPJ8voNFO4jf2Do+6Y7EB2zCR3kM48PfbAwD2VQH6H+FZsdsg30MfVcITv5Jz2G3iXJPe7PQjb6DjMWfjD9RyZUzL7DqZMf121z5jSxFdXnZy7UbZNhy6GPQNmIvslZpNt0yoUAz43/iWkbAM9O1M9DfWJsmPvcIPeNHhnyWL/EBH4xQEyFzS5LXFSYFrZNogyX988WsnPNWAfxYdYNeqfAFSPEXrrDRjiI05n3Dhwsk5wi9hjteYIDZ3roxauMMQqOpOh4VNuO74vcPx0kkLITcJw9BEkWy7OM0XV88RvBcgbAc5eNtWAkXUBcMhSI5dOTPwGyxSeSXUF+Yj63TbjN9PlD0odwx6Q7LBxR5Mn/+9+wFxylQ6AoZF5/PT3+8AcS58xpd+NBSkig4OmnIjRKa5FlmaRMcYf1qr/OsGA0kSclO4fZl/8UyaAK9dEMnDqTAZOMbRh0FTFVzxgxYsSI0W2IqXp2jNj7MUaMGDF+OMRUPYFgRTWBtz6DxkN5Q5IEiXEQ1JBSk1DOmouiV+RdB19rI9rj14VuYIvDef0TQjYAaje+RO3XD7V/UHJQeP672ONShWzUVK1l3cJrQh7P6nUKIyaJ1wv8dNVt7K/8ot1jia58LpwTXsXSCC/vfIz/lYbeObx31HP0SRUrFL+joZzL1obO0zi/xzhuGHCCkA2Al/dt4ZHd69s9luOI563p4gVhv6qs5I71mzg2HR1OzM3h1qGDsZlc6TpMg8/HjxbsDnn8kqI0rh6UK2QD4NGv3XxVeuzf421wYh+FcwaLr1rWVAf45CM/ajspdrIMc+bayMkVC1kGcNcE2P2qH+1wOpwCtgRIG6KQNdaO4oieXTPNEyC47iBaqx9leA5yVkJXDymGABc/uZSv9pjL/S1Mc7Ho1jkWjyiC1O2Dp0+EFjM57zJctxIyo7eWHcCiA4u4c+mdNPma6J/Sn1E5o1h+cDl1njpsso2eiT3ZUbsDd9BNnD2OSwdfyrWjr+3qYQvjKylh/1U/aavZl5VFj7/8Ge/2HfiK94Niw3/gANjtqI2N+EtKUDIyyLzyCpLmdm4Nt0gQCAR54rpFps/PLErk/NsmWDiiyFJTcoClb77MjuVLaPflH4ZB02Zxyi9/00kjs4ao3/FTWz34H34hfAeKjOPXVyAp5ie03gcu1W8k6PzVbnqJ2lUhnL7v0O+K5aZt+H3NLP6f/ou478jfUDTAfOjqZ1/fxr6K9p2+wzhsqVw2L4wiqw5LKz7joa36oSQvTF+CXTE3OfcE/cz+8n7ddnf0P4VT8kOHUerxSvFWHt65Lmwbl6wwf/Z5pm3sbWrm0uXhFfaGpiTz+ASxzZYZH2/VbXNJnwyuHmA+3PP+5W7W6tSUnpAnc8ME8/llfn+QV1/ST84/9wInTqf5Z4u/RWPbk56Qx+NyJPpe6BQqfxEptKCK7+nVaFWHREEUCcflo5HzjOclx3b8OkZn7vj9+pW1vL2uTKiPzAQ7X/9efGEs4vha4d488X7+YI1YRlewqGQR180Ps+AdgtP6nsY90+7phBFFBtXrZfvIUabOzb75ZjKuutLaAUWYR68RVLMFRs/LZ8qZ0RfmXLV/L/+9/deo7ai1GqVg+CjOveNuC0d1JKLvyOhIHAlDcKGBenNBVUjZ03/AoMpPQEyZsXatsZjw5gNLTdvYsPx2Q+12r/+baRuArtMH4AvUC9l4dOsfDLV7eudfTNu4f3uI+pBHce/OD0zbAHh690bdNh6T8sKHuWuTvjrt5oZGmvzm1bg21hpTAXxlj5gKqp7TB/D1QTElzJUrjD34v1wsptxW/XV4O+4KDXdF91+gA1D31X/r9AEENYJrOl8hOEbnIOr0AVS3RKe6H0sfsaafBdFb0uCfq/9p6rwP94rVfuxqap973vy5z5s/tzvgbrFGiXTtJ+2E40QBGxd8KuT0ARRvXGfNYDqJqHf8cBpc0XcIhGM5IqNsJsnGxqg4zIdO2e1G1RRFb43O351QDKqCJirmVVCT7cauvSL4fdmkzv8pxinG1CcVgZ2lOJuxcw02E0JUU8SoIJtTMNLTyG0sR0lQvmRr5z62R/9rJsYPEKeY8vA3xGdY008X4LSZi5hQdPWjuzdyovk5lmR0TtpNsQlExn0fsFmhxNrNo3Oi/gorM8bq+xguB0qfXqZt2HMKjTVMFiuBkDPlVgOtZOJyzIcUDp3wR0PtRk3XDzkNe34ffSns9ASx3Ic7Rxtbkb2k/w2mbVzfz1h+yqMjfmzaBsCtg/Xj4bMEFyDuHjFCt83snCzibea9jH7Jxsb4yyFiOX4n9tF/dM3tLeYtjR1n7AUwZbrYiz5rbPhxJveVcWVGx6NaKkhBLkr99g/xdpRx+V02nhhi3DzPQIkhHYZ3IMy3WzHxGpAtmARO+pl4H13E7yb8ztR5Vw6P7lDHtPPPB7u5Fb2sX/7S4tFEFrvLmlXGE6/p3iUNQjHqhFNwJogt+ow4/kSLRtM5RH2OH4Dq8xN4bz7agYq2Yu52G/TMhYZm5B5Z2OZMNi3N+l28/7wSgiG2gAdNxXmy+APeXbWN0vevBo4Nj7Gl9qfwjOeFc338vhYW/++4kMdHzXyCjOxRQjYAdpZ+ysJ1v2/32OBe5zBtxM3CNvY37OTWte07XS4pgSemfoDTJuYwuYN+Tv7yATwhyp8/OfJShqf1FLIBsLWhmuvXLKRVPfban5pbxG+HTha2UevxcPXKr6n0HhnOkago/GpgP07Mt2aSfu78rVSEiPB6bEIBw9LFBT++OuDjqXVBfIciOhXaNpdyE+G8wXZG5Yq/wAKBIB++76PxUJrO4Z+epkFSCpx0sh2HQ9xO0Key5x0vnlJABlsyxKXJpA1XSO6jREV+32E0VUPdVYPWGkAZkIEUru5GO8Ry/DpGZ6t6vrvmANe/Zq6Y99VTC/ndj4ZZPKII4vfAm1fBtvc7fm5yL/jVOlCiZLs+BKVNpdy+5HaKm4qZWziXsdlj+Xjfx9R6apGQmJg7kQUHFlDaXEpOQg43j7uZKfmCZTC6AarXS+lvf4t75UriRowg949/xLttO77SEuS4OPzFxUgOB6rHi2fLFmx5uWT8+Mc4+/Xr6qFbwqPXLaBdFTgDHH/1AAaOFZ8TdRWe5mY2Lfycrz98h5baGpAkJFlG+24IqCwjKzbUYKBtQiBJOJwu5lz1c4ZMFy+DEw7Rd+T3wvE7jNbSSrC8mmBjEzQ0g9eHPGkk9hRrClL6G6tRn7+jLen7uyRn47jqfssmZ6Xzf4u/uZyEgpl4a7fjba5EAXocdy+OJGsKq5cXf8nmFccqD6XmHMfYGWK1Ag+jqkE27HmZ+uYSSqtXYJMceP0N5GaOZe7Yuy37vv6z9e8srHgXL20CGfEkYpPs3DziQfqnDbbERovfy49XPEFdoBnvd/5+QsYg/jj8LEtsBNQgf9uykmVVZYBGpjMep2xjWHomV/YZjssmrh4JUOv18nVNDc3+AI2BADVeDwXxiZxd2AvZomtS1eLlznXFbGsKEATigHgFxmcncPvIAr3TDaFpGu/v8LC7HhIcbWqeNhlUTebU/gpJTmsmXHV1XtatUUlIALcbnHEQ9MOIkQ6Skq0JaVJVlcYdKvZkjaBfwt+iEmhVScq3EZcbZY6fpqHVe5CSnO2HfuoQc/w6RiTKObyyfB//+HwHgaCfoCaBptHihXgXeH1twndJcTI+v0p8nI0Up0J6UhwvXj0Z2YJF1y6leg98dAu01oFib4u7rt0FCbmQPw62vAlKHMSlQHw2BFqgsQJOugeGntbVoxdmW/U2lh1cxujs0VR7qom3xeML+thZtxMVlWEZw8iKz6KksYQgQTwBD9nx2UzsMbGrhy6M6nbj3b0be34+trQ0fCWl2DIz0AJBgnW1BBsbUT0efPuLURITsOflIaek4MjPRzKYWtFdqTvYzEv3rmxvDyIsg2dkc9xFUbzYc4j6inJWv/82mQVFOOLi2LdxHbl9+uFpbqLnoGE4XHEsfPFZ4pISGDBpOtXFe+k3fjK5fTrf8Y85fhxSkvvf57Bzf/sNMtNwXnWO0Bi8j14H3sbwjUbOxTnnEtM2mkq+puKz8ApaSkI+vc9707QNgPmv6z+QJ574OolJ5ifoOw58wKINd4VtM3XobQwpOtO0jdKWfdy06vywbRTsvDhriWkbANesfp71TSVh27w/6ZdkuMyHNL1Xsou/bF8Vts3FhYO4tt9o0zYA/rBhI/MrqkIe//vokUzIFMtJuXTxLva1hn9b3D2yBzPyUkzbWFvu534d8ZWJefCrCWK7vW+86sYTWnCThEQ482wxGzXr/ZQtCP1ZJBv0u9iBK737TyTUmlb8r25Cq3VDnA37aYNQ+nfsfoo5fh2jMx2/Fo+foX/4VKiPC8f35M9nm09P6FIeHA4NxWJ9RKmqZyAYYM7rc6j11po63y7b+eisj8hJsGaxOtLUv/02B39/Jxza5ZGTk1EbG5Gczradn2BosTUlO4tejz5K3PDhkRqupTz+ywUEBTWZrn1sNpJoon0X8exN11JTYu5374xP4JonXrAmVzAEP3hVTwB1y67QTh9AdR3BmnrT/Qc8LfpOH8D6z0zbAHSdPoBgSym+pnLTNg7sfMdQuxUfmy/lALBog76U7VebzattAtz2tX6JjSB+1teYL38B6Dp9AGcuF1OA03P6AF7cb1BdNgR7m5vDOn0At69tv46gUardfl2nD+CO9WJqgQ+u1I9BWXEQfEHzC1t1dcGwTh9ASzOUHBBTWy1bGP6zaAEo+Tg6lBEDn+1uc/oA3AH8H+xAU7v/4mKM9jn/SfMK0od5eZX+87NbUrVD3OkDWGFMrbu78dDah0w7fQB+1c+vvviVhSOKHMGmJg7e+X/fOH0AamPbHFDzesM6fQDByirK/xh+4bu74m7xCTt9AC/+UfzZ0RXsW7/GtNMH4G1t4YvnnrRwRNbzvXD8NANOnXZAQFK8Yp/5czsBb41+nbRQVJSIrd4aR0xK3wh+zavfCFhb81UnjwT8dP/J7eYG/ZVnY99oaLY36XhKFhEw+HU3eM1fl4pyY/dwRYWY42fkp+Jr6P73F3BkKQeAZh+4o8NpjXEsuyuNlWf5XlJsoFSUEdY8Z00/EWZjtX6JIT1Km6NT0t9fdhAEyhoBeHfvtmg0kaVqn4FNDgM0VIrOJrqGsp1iC+wAB3fvtGAkncf3wvGT++ordipDzStI2gqHmj63QyguQ80Se001bWLQmFsMtbM7zRfXBnDY9FWRJMRysPJcxkJRTy24WMiOEQpd6ULnOwzkcCmCJTJmZ2fr9tDDKRaeMDHTmBqWUzACJM2gkGZWvPlHXN9+xkIr+w8Qu49lAz/7xKLoeFTLA44M65Tyk5ASOi/kJUbncv5482rYUc8w82kIR3DBf63pJ8KcPzB8GoURZvScYcFIIo+zX1+UbLE5UNLsWZaMJdIUDM20pJ9Rc6NTzXnwtFnCfYyae5L4QDqR6JhN6CD3ykM5dVboglpzJiHZBYUeZhlwHn7yoJCJvpfoFz1PH38jkmJ+IpWYUkR8sr7M7ozT3jNtA+C8WW+i6MxoL50ntvv44KTXdesFTck4kUyXWOmAR4ZfoNvmlUnXCNl4e1r4SYYE/Gf8PCEbCXY7d48YhjOE2EKiovDvyWIJ+TZZ4ubB+jkdH84dKGTn/jlOnGEuvQT8drLYb95ulxk2IryHOnKURHKy2GO0348dKPGhjycUSvScGx3Ok+243iiTeiJlxSMPzcZxdoQWzWJ0Cn84fRi5yWLlSr66ZaZFo4kwzkSYc6dYH7ljIK3IkuFEmhN7n8g5A8xrI4zOGs090+6xcESRQ1IUCp99FteI4UguF7a8PBJPnIdzwADiJ00ibvQopIQEaOddKiUkkHLuOeT+0VjprO7I8Lk9xDqQYepZYu/4riIttwczLr7C9PmDp89ixJxYOQdhIqFaFiNGjBgxup6YuEvHiL0fY8SIEeOHg+g7MroLzBwi2NBE4KnXINhOsozLgf3ys5FTxAoyenesgvcfDtvG8evnhGXX9719MYH6ELHhsouCM/+LI1msPsrXC39FQ1VowRNZSWb2WWJCNS2eKl6af2rI4ylxvTl39ktIkthuyU3LL6DUszfk8dPyL+Wi/r8QsvHS3qU8vH9hyOMSsHTW7UI2AO5Yv5gvqtvPiXDJMvNni4fe/GnjZj4tr2j3WE+Xi0cmjCXDKbbCv6KiiZvXhhd0WHyieJmNj/f4eXFTgPb0W1Ic8PA8JzZBKfmN672sX9d+Ep4kwbyTbGRmiZfZ8DWq7HjRi3Z0iqQCfc6xk9Ajeh7Vmqbhe3ED2oGGtvoaCXbwBpF7pmA/ZUCH6/rF6FoG3P7BN7UyO0qiQ2bTXd077Cksm96FN8wrdXP5J1A0ybrxRBh3wM2jax/l7V1v0+RrQjOYy55sT+Y343/Dmf0tCpftAoLNzVT+7e80ffEFBIPILhfYbMSPHk3mz6/BUVCA6vNR/cgj1L3+BmpLS1tdE8A1ZAiFzz/Xdk4UUlXcyGv3ii0m/eLx0LWiuztrPnqXL57tuECL4nAw6azzmXSm+FytM/lehHoGnni1facPwOPD/9SrCO9s6jh9AL4HLxMyUfrJ9aGdPgDVQ/FbYjeU11Mf1ukDUIONbF4lVssvnNMH0ODey3vLfi5k4+8bbgnr9AG8W/o8LX7zycqqpoV1+gA04Edf/tO0DYB3DuwM6fQBeFSVkxe+IWTj2d37Qjp9ACUeDxcvFVNA9auqrtMHMOdj8wJFAKvKAjy/sX2nD6DBB7/5XCy5vKkpGNLpg7aarR9/GEC1QLVyx3PtOH0AQdjzqp+gv/PFkqzC98J6tH31ENTAG4RaD7T4UbdX431+bVcPL0YHmHzvZ6adPoBmn8rEe8QWEbsUEacP4Nl5EIhecaP/++r/eG7LczT6Gg07fQCN/kbuXHonKw+u7MTRdS4lN9xA/SuvEKyoIFhdjb+kBP++fTS8/Tb7f3wJqtdLxZ/upubJp1Dr6sDna1MBDQTwbNjAnjOi1+kVdfoAnrppoXAfXUFLfZ0ppw8g6PPx1SsvsGH+xxaPylqi3vFTm1raZmDhCKpoVQKyxDsiE0bjLtOX9EcL4qsP7+yEY+V8Y7HL5fveMW3DHzCmBFdRt860DYBVtV8aave3jbeatvGfPYsNtasOtpi2AfDUng26bRoENZZfL9aXKG4JBClrdZu2Mb/MmJMtOhX6aI++kmal+Y8BwMrlxkZZflDMKfPUBNF0qlM0bBNUDo0gWkmYe6DajVoneGFiRIyDjT7hPiqaxPvoEpboL/YaYsPL1vQTYQJqgE/2fSLUx3NbolPRNNjUROuS0GrggcpKWleupP690FoI/n370HTKPnRHGqutUfL1tUTPYuV3mW/S6fsu6z75wIKRdB5R7/jhMhaWJiUIFFnOFgutNIxB0RYlznyB7dTMMYbaSZJ5MQlFNnaujFhIoUsydv6QtLGmbYxMM1/EviNkuxI63UaawYKiyXbzoXiFiZERIcmK7/zCsBkZxmwkJonZsSfoP4Yd6VH0qLaFGassxUI9Y0QHBROs6SdrkDX9RBibbCNDYK4B0DMxQnMni5FdLuTE8OlBtpwc7OGUP202JMWYMnR3wpUUHUJinUWP/uKiNEkZ1iijdhZRNJtoH9lug8LwCkRSn15ICWFk83Swp+aCESn9nvpqmeHInX2fbhtn7hgUZ7JpG8Mn/t5Qu0nzXjVtQ5ZtpCX20W03c9Qdpm0A3DrCmIrqub1/YtrGuPTehtrd2f9Hpm0A3D9SX/nuJ0ViCokPjhmp22ZeXg6JAgq4g1PjDZVqOLtnimkbAJcMteHQeXpdNETspTtytP4LMCEBkpPF7CguieQBoT+MPRkS86NnAmE7OXTpHGVmIZIzevIVf+j8+QyxdxrA70+JTseHgolgE8zRis+CXhY5kF3A7RNvR5HMPXtSHClcP/p6i0cUGSS7nZw7fteuaidA2o9/jGvAAHLv+B3Y2n+eZV7/y84cYqfhcNqM7kGE5ZTrhol30gWMPfl0IYddsds5/idiuhKdzfdG1dNfWoH6/kKwKZCfDTV1gIQyZzK23CxLxuFd/Bp8/X77By+/D2d6nrANNeij5ONf4qvcwrcBcRJychF5039HXLY1P6Yv3j0D1dtOUXs5gePOmi8sUgNwoHIln6++jYB6OAxSBiQykwZx8qR/4nQIbpUA/oCf3359OSWeXcccm5w+l1+NuFvYBsAt617ly3byLxXgi+m3YFfEJ7OqpnHrmi9YVl/xTTaFBKTbnbww4WRSLEgU1zSNB7dtZ3VNLa2BIDLQJymRNKeTCwsL6J0kJoJ0mNf2VvHI9upj/i4Dr8/sTVacNZ/li/1+FuwLUtYI/kNfWo9E+O0UB6lx1jhLX69ys2MbqBo47JCaCj4/jByl0KvAutXR1qogpZ/78DVCfC74WyB7gkJqv+hbgQ16/Khf7kfqkYyUEY9W2ojcPx05Wf+6x1Q9O0Znq3o2tfqYcM/nuEMl1IYgK8HG5zfNIiVeLLKjy/nqEfjiT206AppKW1Z3EFBAVkANACpIdrDHg6+prSbv6Q/DCPPlELoLDd4GFh9YzL7Gfeyr30dWYhZJtiRsso0lZUto8jYRZ4ujd0pv9jbupW9qX6blT+PE3t1b0t4IgZoampcuRUlIQHI60QIBnEVFOAoLv2kTbGqiadFiAuUHkZNT8O3aRcaVV2DPFSsj1dVsXVrKgue3mzo3moVdDrP0zVdY8+H/Dv1LIyElHTXox5GQRFxCEvmDBlOxZxeV+/YgKRK5fQbQa8hwRhx/IrKgqJwe3V7VU5IkBfgaKNU07VRJknoDrwAZwGrgEk3TxJMA3B5wu0EF/D5IT0MZ1t/aC1C5P/Sx6v1ggeOnBQMozlQ4IpFaQ23cS8Oujy1z/CQ1ROy52kIg0IrdLh566PZUE1C/m8/TFvNd3bSZ8totFOaK1YwDaA00hhR4OdCyR7j/w6TK7YcKB4E6v5tsRdyJ3dZQzer6yiOuvALYJJn97iZGWOD4SZJEmsNJjceLT9NwShLbG5vIjfPjCXVPmCDFbiNehtajwvwdAJo1v0lVg6AqIUngUAC1bYE2PQ5DG/RG0DSN1FQbLleA1ta2/P2q6rb1pYb6ID17aZYskvibNWrWBVAckDpIwpkq0VoGiiN6dvq+i+Kyo8ztB4DmC6I2eyEQnTkfnUnE3o8CaEDQxAJxVUuA/TWtjIh2x09xgDMN/E1tQi2ql7YHjATqdy6N5gdfw6H/1qBuXxcM1loCwQCPrn2Ugy0H8at+nIqTdQfXUempJDchl4rWCtCgorWCOm8dRUlFLCldgk2ycVzBcTis2DrqQgLVNfh27Ub1+3EWFWHPy6V56TLUjz/B0b8f7rXraF2/jmBdPY7CAlJOOYXEqVOQEzo/daOz2b2x0vS5alBFVqI3oLC1uZHNCz/H19pKYnoG7pZmGirLsbucBP0BGioOUrF3J/EpKTji4/G0tFCydTOSLNF/4hQSUlK7+iOEpdN3/CRJuhEYByQferG9BryladorkiQ9DqzXNO1f4frQW9H0vvAOlFWFPC6PHIT9xOmmxv+NjQcu1W+Uno/zcvNqmO6qLZS+f6VOKxv9rlhi2oaq+vjiTf3vYtT0R8nINb/o/trC82lo2Re2TXbaOE6f8qhpG0vKPuGRHfoFdl+ZtcK0DYDJC+/VbXNbvxM5vaex/Mn2uHvTMj6q2Be2zfHZBfxx+FTTNgDmLVhEa5iE89N69ODmoWKhWRcv2skBd3i1kluH5HBKQbppG41ejRs+8+AJ46teP87OpHzza1vBoMbbb3jwtKe2eQhZhvMucGGzm3f+6rYEKPkktJBMYqFM77Oic/KsVjTj++96OHQ/2GYWYZteGPacH9KOXyTejyJ8sa2CK54V6/v0kXn880Lzz8Yu5a99ofXYyAXDOJPhtwesG08EKW8p54Q3TuiQmud3kZD4+OyP6ZEoWAy8i6i4/2/UPvOMqXPlxER6PfUk8aNHWzyqyPDoNQuE+7j4rgmkZlsTQRRJdq/5mnfu+4NQH6fd9Dv6T5hszYDaQfQd2akuuSRJPYFTgKcP/VsCjgMO69I/B5whYkPTtLBOH4C6fhuqgKqn6jGo2FgbWo7fCJWL/2CgVYDG3eblsVcvvNZQu3Vfmo9R1jRV1+kDqKwTm1AYcfoAPi0xXwah1ttsqN1fdonJ9+o5fQCfVxYLlSVZVV0T1ukDeLeszHT/AK0BVdfpA7h/S+iyEkZ4fas/rNMH8PQ6Me3QHdsCYZ0+aCvbtGuX/ucNR9mC8ONs3q8SOHrrNEoILN73jdMHEPhyP1pr9MrbW0kk3o+iXCXo9AH8b307KQXRwI5PxJw+AG8jVGyxZjwR5tbFt5p2+gA0NO5bpa9b0B3RNI3aZ581fb7a3EzVPx+ybkARRA1VGq2DvPzH6Czl8d6DYqXMABb8+3ELRtJ5dPZe7D+AWzgc49cWvlKvad+Il5cA+e2dKEnSTyVJ+lqSpK+rqsI4dkZraLUISIgbdfwECXqNSeF7a83FXQN4Wjr/JayqYhNhq9nRsNn0uZUe8zUAOwMzIVeHKW6xRqY5HC0BY+Gioq+WOo/+9+AVjFxtbjH2XbcabNcemqqhGvCDAq3dPxe7PbSWoz6cqqF5Yo7fIf5BZ78fBYnO5QaLqDVfNukIWjrv+nQmNe4a4T4qmsUW+LqMYLDtfyJd1AguGnQRwYA17xoLM0ciStAv/n7yuiPjM5il0xw/SZJOBSo1TVtt5nxN057UNG2cpmnjsrJCi7NIigyyTphVShJSL/P5d3JqGMleC0kZfK6hdhljzRc+Hz7F2ApcWqb5/DtFcWAsyUrs9iuKNya7+7NBt5u2MSjFWJjKwASxRO5kA7kQKXYHNoGc1dN6tTuHPIJsp1hIYZbLmFT/qDSB8irAyf30c9/G54rl3g0ZYixMtG9/8+GkkiyR3C/8NZUd4MqM0ly/ETlH/FvqmYycbl5h+ftCpN6PopwwWPzdFycQBt2ljBEs3n6YwinW9BNhrhl5jXAfV4+42oKRRB7JZsPZP7Q6sRFSzjjDmsFEGLvTmnfNqLnRWcpj4ORpFvQxw4KRdB6dueM3FThNkqR9tCWrHwf8E0iVJOnwTKknIBYfCdiuvxTak6BPSkAeNwzHRae2OYgiXG6g1MKNzwuZyBh9FSlDLgjbJue4vyPL5n+YqRnDyC7QKT0gJzFmtliYwqVzP0ci/DivOtl8riLAXyY8T7KSGrbNFX1uxq6I1Q17fsxVYY8n4+TZ8Xq5meF5b/oZJIS5rlkOF29OOU3Ihl2WeXTcmJBXpU98PC9PnSRkA+Cd2f0I9433dCk8NLFIyMaQTBvXj7OTFMLQxDyJX44Xc2ITEmXmnOAgVPlDSYLjT7CTkiL2bOl1soPUoTLfXBi5TSBQsoEzU2LA5dGZ3wdgG9MD+5mDkYdkoUwtwHF+dEp8dwIRez+K8ORl48lPNS/QIQNb7jrJugFFEkcCXPU52MwuVMjw8+Ug+P7pKk7teyq/Gv0rXIoLqYNqWTIyt467lTmFczppdJ1P4Wuvknj8HOSkJCSXCzk3F+fQodiys1GysrD16AFHLZQqWVkkHncceffcQ8ZV4ecN3ZlL/yImvJeQaWPq2QMsGk1kOfVXt9BjkPnSWcOPP4kTfta9S3lEpJyDJEmzgN8cSl5/HXjzO8nrGzRNeyzc+Z0tVx0jRowYMboHPyRxF4i9H2PEiBEjhnG6fTmHdrgVeEWSpLuBtYA52aTvoNU14nv3cyhvPyZdmjUBx0T94tXh8H71Dqx4K2wb+ZJ7sGf1ErKz760LCTSEzi3InnUPyb3FVtG+eOdEVH9d2DZzzhVTwmz1VPPi/FPCtjl96gtkp4qtCl2wMPzKVK+4ftw/8UUhG3MX3U+zFj7ue8mM21AEwjC31ddw1epPQx5XgLennUGGUyxE8uFtO3ntQPsqc3bgrpHDmZYtFjr2yJZyXisOf38tmjdIqAyCpmncvtDD/jApmHdMtTMkU+wR5/ervP+ul5YQGj9jxioMGSYmWa5pGuVLfFR/3X5GlWSHIdc4kW3WBGgEd3jxf9EMHhXbhHhsk62THtc0jcCifaibKyHBAQ4FraYVOT8Z+7x+SAnRLe8eASx/P4oQVDWG3fkxboFSHGvvOJ60xCjdtd72AbxykfnzL/8AisRDx7qKT/Z+wl3L76LR1/Fc90Hpg3jt1NcsKXfTVZTfcw/1r76GdjjvS9NAkrDl5WHPz8e7eTOapiE5HKgNDd+cJ6ekUPT6azgLCrpo5GJ8/OR6dq8Ry/GM5lp+z9zwU+oPmhO6S83J46qHnrJ4RNYSkUIbmqYt1DTt1EP/vUfTtAmapvXTNO1cTdO8ov373vwkpNMHoC1cieYzn7Cpaaqu0wegvvA70zYAmkqWhXX6ACoXitmoKluq6/QBzH9drGzAywvO0G3zv6/EciguWzhbt80B9y72Ne00bWNh+VZdpw/guMX3m7YBhHX6oK1e4I+XfyhkY1N9fUinD8AP3L5+IxV6UpZhCKiartMHcO4XO0zbAHh8rS+s0wdw91d+VMGIhgWfh3b6ANasDtLUJJbFXrclGNLpg7byYDteEH5MAqA2BPG9VIdW4kerDuL/sIngFvPX+2iCK0sJLilGq/OglTSi7amDBi/qlir875oXpfo+09nvRxGuf+lrIacPYOKfP7doNBEm4IdXLhbr49lTINClZRhN4w64ueXLW0w5fQDbarfxm8W/sXhUkaP+7bepe+G/aD5fm8N3+F2iaQTKynCvWoXa2ormdh/h9AGoDQ3sO/e8Lhi1NYg6fQBv/8NU+nKXs/KdN0w7fQD1FQf59KlHLByR9URvhcVDaM2tUFOv207dFab4up6NevOFLDtC9bIHDbULehr0G4Vg14Z/GmwppsypGnCWRPFiTKXy2Z3mnbL7dn1iqJ2PzpewahScQPyvRP9hpgFravUdt1AsqzI2Saj0iU0mN1QYO7+8WczxqzYgyLd3j9hnad6nf76/XsjEN6h7fRx9qwZ3WedbqHtC3zvqHvMldWJ0DZ9uEVek9EWpuh97vwCBcgbfULFRvI8uYNGBRaia2LNtedlyi0YTeRo/+kjofLWhAVVgEbWraKiyRpGybJv5eWpXsvqjd4T72LFMTL+is4l6x494F8Tph5FIPXJ024Q8N8l8oemOkNjvBEPtZGeSaRs5BSebPjdamZV3uulz52WZT/K1GlGtrYkZxu7jfknmi66OSDUmhCAa8JdvcIiZ8WJhRokGfmq5eWKPUVeW/hhliyLl5JxjQ1/lXOvEJ6Sc0GGjUhQW8/2h0ydLXIE1agP9eoy1pp/0vtb0E2FGZY8S7qMwqVB8IF1E3KhRQudLDgeyy2XNYCJIcoY1qstxSdGpRN1z8HDhPrKL+lgwks4j6h0/SZax/+g4sIe5yQp6IKead5YkmwOSDchaTxBTXcwa/ZM2Kb8wJPQ5CUkyf9n6DLnMULspp3xg2gbA8aP1VVCH9RYLo/nXRP3QRxmZWXnhcw3DccPAuYbaPTv6CtM2AC4pGKTb5oFR+qGt4Tg+L5eBOk7dRYUF9E8y/1tJcdrJd+nn1b06S2wydP0EJw6d98o5A2Uciti0c+YsJ+FSVHrkS2Rni73gMkfbcOlUA+lznjW5cXKeHdvxiWCXQAJlhAtljFje6HexTSlA7pPW9g+HAgltTqWUFof91OhUefsh89rPxEL+AZ68dLQFI+kCEjJg8nVifcy8DeJSLRlOpMlNyOWSwZd0WNHzMHG2OP41918WjypyZFx1Fa7hIZwAWUZOSfn23+28JPL+Gp3F6yVZwkB1KV0u/8t08U66gFN/dQuSYv6dLikKp998h4Ujsp6IqHqKYkS1TFNV1KYW1FYPsqqiJcWj7i9DGdAbxWnNpCkY8BF4+mZo/W44kwJ9xuI8Q/AF8R08tTupXPcSvqqNoMRhi0slsddEMoZdiCRQyuG7NFTv4OsvrqMtsytw6H8SmQWnMXLibZbYANi09w12ly3EZUskPbkvB8qXk5CQwwnj77Es6ful7Y+y6OD7yNjw4sZFPImuVH49/G7yEqxJrl5fW8wdG96inlacSKSRiGxXODlnOJf1s+4B968dawgGNRJsNmySjFdT6ZuUyqycAsu+rxqvl7U1NWxvaERDItvpZFBqMgNSUnAJPPC+S7PPz+9W76WsKUiOC5pVCGpwTlEmp/e2ru5YSWOA4oYAFc0aQQ1SHZASJzM6z4FNr75nB6it8dPQEEDVZCRUbHaF3FwbDod1a2cBt0pTcQB7ooYtzoanJoCsSCT3sV4QRfNpENSQ4jpn7U9z+9sW4xQJWv0Qbzd8//7QVD1FiYSq55c7DvKPT7eRaLfjcspUt/hxSTIHm9w0tPrJTotH8/vRJJmqJi/xDomfTB/A5TP6deq4IoLfDTvnw9dPQ0ADZzykFNAWM61CfC5UbAJ7AjSWgazAgHkw4QqwRb+YkdvvpqK1gqAWpLqlmgPNBwj4A7SqraQ4UyhKKWJb1TZkRaY10Erv5N4UpBbQL/V7cO2BQHU1QbcbJT6eYEsLssuFkpSEHBdHoKYGTdOwpabiO3gQ3969KMnJxI0YgSQg9tYd8Ln9PPu7L/G30qb8ZjB7Z/oFfRkxK3p3eg9TuX8PO1csp+eQIcQlJtFQVYWvtYWK/fvweVqJT0kjMSWNopGj8bvdlOzYSq9Bg8gu6vz7XvQd+b1w/DSfH987n8HeQyWPJKkt/DMxAXlgEbbJo4UnzZqm4XswzG5ZWj7OK/4sZAOgoWQlVZ9df+wByUZy/1PImnKb8Gdpbalk2Yeha/kNmfBn8grFFZneXnwl1U2b2z3Wr8dpzB4tJlQDsLjsAx7bcVe7x5xSPI9NeZcEu/kdLICK1kbOWBk6WfeO/qdySv4IIRsA75Xu5pHtq2nWjk2KmZvdiz8MF1eHK2t18/v1G9nd3HxEqpcMjEtP4y+jRmAXdP58wSDzPtsRMutxUpqDv04UD3/SNI1P9/p5aVMQ/6HHmF2CJCecNUDhuN7iky63O8jHH/hoOSrtwWaD1FSYNtNBYqK4s1z+lY/qtUG0AN+kFdlTIXuijbRBNiQLndjORguoBNeWoe6rR+6ThjIqr0N1VGOOX8fobMfvleX7uO2d9p/jehw3IIN/XyleG7TLaKqEfwyHoIlcreSe8IuV4LRONTfSfLrvU/698d+UNJXgDroJqkEUWUGWZBKUBHyqj6ZAExISNmz48SMh0SOhB0+d8BS9ksVUzruSYHMzVQ89jK+0FCUpEbWhkbjx4/Bs3ARoOPv2wzmgP57Nm/GXlpF84jyUzEzcq1cTN3Ik8eOi+xH26DULTJ8765L+DJ0avde+rryM/952Az73IR0JWUaRZYKBY7UvJJsNNA1NVUnN6cHZv/0jqbk6ITyC/OAdPy0QwPfgc6CGTkKWcjJwXH6W0Bi8D1yq38iZiPMXYUsuhaX14FrKPv552Da2xDyKzn3btI1AwM2it2fpths68V5yC8yXjXj2ozn41TByiEB26khOn/qkaRsfHniF53frC+K8Mst8aQpVVZm6+C+67W7oO5fze403befeLSv44OCesG16uhJ5dWpoh12P0tZWLvgqfLJ9nCzz6ZxZpm0AzPh4q26b/ok2npnWX8jO31d4WF0e+vk1NV/iF+PM51h4vRqvv6I/4Tv3AgdOp3nnb/erblrD6O4kFkn0PjM6ckU0TcP3zBq08m9/+1J+Ms4rjIf7xRy/jtGZjt9zX+3l/97bItRH74w4vrg5CqXd1SDcZUF+/x+iU+Tir6v+ygtbXhDq463T3qJ/mthzvitQfT52TpuO2mhO0RQg+zc3kfGTn1g4qsgh4vQd5oSfDKX/OPPaGl1FbekB/nNj+Hm4Hlc88C/S8zvP8RV9R0b3XjSg7ioO6/QBaBU1aI3hnZCwNpoMqtF5zdsAKPv8Jt02geaDBNzm1fE2LjO2y7Zl1f+ZtqFpmq7TB1BZv960DYAXdhtTKH1zr/maKjdtfNVQu3/u/sy0DYCPDoYv4wFQ4mnGGzQvkffP7fplLdyqyqb6etM2PjhgTBF0Z7OYamyjVwvr9AEsLRVb1Fq7xpiK6oplYp8lnNMH0LxPw10lpq4XKbTihiOcPgCttBG1zPwEKkbXIer0AeytcVswki7g7Wus6WetWB3ZruK17a8J93H/KrEyR11Fwzv/E3L6AKqffIpo2Fg5muYGa5RIP33aXJRAVzP/308I97H4pWfFB9KJRL3jh8EflqbjHFphQxijdgTGY/R7iIYHlmZQajsgUFoiYPT7Mm2hoz2YtxQ0eE1Fynb5gpFxUCJxdxpVMhd5tBim+/8cgTCPpujwW2PE+JagRfX3orSOn9H3aziCapTW8rBi3AKLtF2JYAWPqEe14Nqr3fzaR73jJ/cr1NeLzkhFTk02byM5w1hDRUxzPXf2vfomXBnY4g2Opx2GT7nHULtBo281bUOSJGyyvlJgaqJYCMi5hVcbandeb/Pb9g+OuMBQu58WzjBtA2B2tr4ITbYjDqeir5gZiusH6H/fdmBUeqppG2cWGbs3e7rEHj0pTolhmeHbjM0Vy4sbNdpYmYMJk8xfEwCXjtZNfE+JuOzoeFTLhSlImUfJgWcnIOWL5dnG6BpunieuxJqbbFEtkkhzpvlIkSMYa0xJu7vxoz7m0woOc9N4/Sim7kjKGWcgJ4jlZqZfdpllgmyRJCnNmrSCmRdHX4gvwHGXG5tXhmPaBQZSw7qQqM/xA9A8Xnwvvw+V3wmBdNghzoU0oBD7zIkdEhdoDzUYxP/PMJL9jkSc15nP7ztM3fb3qVl6dztHJOILppM3+14kWWyi2Vi3i1Wfhy6l0GfYdfQefImQDYAXPzuNVl9Fu8eyU8Zx+rRHhW28vfc5Xt3f/vcuo/DIpHdIdxkoxRGGnY3lXLrm3yGPX9VrKj/pO1PIBsALezfzzJ4N7YpnjUrO5JFxxwu/SHY2NPL7jZsoc3uOWM+VgAGJiTw8YSxxguIu9V4/p32xK+TxojiZ52cOFLIBoGoar2/x8u6ub9emJSDeDif1VThroLi4S2NDkE8+8uE9qsa5LENSEkyf5SA1VVzc5cBnXuq3qEfsjMlxkD1RIWO4HdkWPRMIzRcksOIA2v4GpKJUbBN7IoUrt3MUsRy/jtHZ4i5/eX8zjy/ZZ+rcwTnxfPRrsTI0XUrVdnhsMrQjuKWLMxmuX9dWFiJKeW37azy/+XkqWivwB/0ECSIf+j+n4iSgBfCqbQ9HGRn10AMs1ZHK43MfZ2hm96mD21ECtbVU/PV+/GVlyHFxaK2tOIcPw7djJ6hBHP364ezXD8/WrfjLDpJ84jxsWVm416zBNWIESbNmdfVHMI2qqvzr2oWmzx85ryfTzoze8j3le3fzyh03HSnmIkmhQ1oOHYtPSePs2//Y6XX8fvDiLofRNA0tECDY6kVWJGSXC01TkWw2y1ZdNE3Dt+BFaKhtCwWISwZ/AAoH4RwtPvE/jLtqJ63N5ciaiqr68DbX4UpIIqXPXBSBHZ8jbLgb2LX+CbyqhBYMICORkJBOrwGnk5BoXULuntJl7D+4FFlWyM4YhKqpKJKDQYXHW2ajrHE/G6qW0+Rvpab1IHGOePqmDmFC7iwcFslpe/1+/rn1EzbV7iNHScaHjFOCUwrGMrNgsCU2AEqbG1leWUKaM4E8Vxy7m2rIT0pldEaeZTZa/X7qfT5UTcPjD6Ci4dY0BiUn47RZc3+pqsryg3U0BVTqPX4SbBo22cGYnGSy463bAahs8rK7TqUgGQJBUCVQZImCVOvEULzeAOUH/Sg2cDrBbpcIBiE11YEiuKD0XfzuIMGAhmIHf2sQza8Sn+WKKkXP76IFVDQZJJU2j1yWDD2LY45fx4hEOYed5Q28u66EeDtoQZWEOAcuh50ku4KqBlh7oJ78dBeKbCPZZWPJ7lrOG9+LiX07V90uYpRvbqtHU7m9zZFzJULdPlC1Q3OBtDblT8UBibnQXAH9jwN79JdzaPI2UdlaSc+knrQGWpElGbtsp8nbhKqpNHgbkCWZOHsceYl57KvfR7oznfQEC4RxugG+6mokmw3bofq2mt/fpuIIBGpqcPbsier1IjkcBGpq2so9JIavlxstLHx1PcXba9AAmwtsmkQwqOHztkWyqgooCng9kJlqIxiAqWcPotdAscX27oDP00pLQwPellY0NUhSRhaKTUHVVPxuN7Ki4G5sIKhBWnYOTfUNpGRk4IyP1+9ckJjjB6h7S/C/8zn42tkriXNhP3UWch8xhR3vgz8BTSdWf97PcA41X/DWXbOD0nfDbxHLCfn0Oe9N0zYA5r8+UbfNcecsEyoUv7tkPgvW3x62zcCeZzBj5G9N22j01vLTZSeFbZNiS+eJaR+ZtgEwZeG9utkO/xl9OYNSepi2Uelu4cyl74Ztc05+P349yLxyqKppXLhkGWWe0MnbfRLieW6KmPz6L5btYWODN2yb948bQLJeBfYwFDcEuG1h+NzNn46UmVUk5mS+9II7bA5fegacfKpYAfTm4iB73/KFzONLHyORPzM6VD0BNE8A/7vbUHfUtDl8hz+XS8E2py+20eEXMWKOX8foTMevye1n+B8/FerjnWunMKogzaIRRZj5d8OXAgIlST3gJn2V4+5IcUMx531wHi3+Fv3G7WCTbCy9cClxdrHnY1fR9MUXlPziuiOTuG02aEfS/2jk9HT6vPUm9k6W9e8sXrlnBTUHzF33w/zi8ShU8qUtuu/pX11NU1WlqfMdCQlc9Y8niU9OsXhk3/KDV/XUAkH8785v3+kDcHvwv7sAzW9eec/vbtV3+gA+EVMDKn1XPxdAbSnFXWVeaW3rmn8YavfV+2eYtgHoOn0A20veEbJx/fJzdNs0BGpZU73EtI3PD242lOJ+xdpnTdsAuHT5h7pt3igNHT5phCd27g7r9AHsaWllVXW1aRt1Xr+u0wdw5Ve7TdsA+L/F+oI9T65XUQUWttau9ugKt9TWwL69Yqqe+94L7fQB1K7R8NZFT8Z94Mv9bU4fHPm5PEECH+5ArYtSlccfIBPu/Vy4jzMeW2rBSLoIEacPoKkMDqyxZiwR5lcLf2Xa6QMIaAGu+vQqC0cUObRgkJJfXn+scpcBpw9Ara2l5KbfdMLIOp9gUBV2+gAe/bl4SYiu4IvnnjLt9AH4Wlp4/x/3WTgi64l+x6+hCTw6TpnXh1ZvXppX3fKl6XM7hrFJasN283X8yveF31U6jNdTZdpGpPBoxh5Onx18y7SN50oiM2lpUo29UPwCalGrao2VAfmg9KBpG8uqjJU0qfKKqV55DfpBTfo+aEiK9xv7PZaVmv8smqYZWlNyV0aP46cebAp9UOOYcg8xui9uf/Tcd5YTFFvQ+YZV/7KmnwhT3FQs3MeuOrHFyq4iUF1t2MkLhXf7dotGE1kaKlqt6aj7BxO2S/EmsTJjAJX7wtdk7mqi3vGT0pIhUSemNiEOSUCp0DbSfCHzDiEZC31LG365aRN9hv3MULuE5M5NTrWCFJuxHIJzDKp/tsct/U82fW5HyLYbC+WzCwivHJ9rLHfz4qIi0zZm5xlTz+2dYEwxMxQJBlMRU1zm8+MGDjb2XRf1Nn9NJElCMRAJldBDXEAmUsiFqaEPKhJyr84LgYlhLemCv9OoxqJ8embfaU0/EWZQ2iDhPsblRGfEti07G1xi4fUJ46Lzs6fliamZHsbmjM7c9IGTxRTaAXoNHWHBSDqP6Hf8ZBn72SdASjvJtJIEGanYz54npOqp2GyQZkBc4xJjpRJCUXT+B7ptHLnjcabkm7ZROOB8QH8SOWmeWNHZs6e9rNtmypDbhGw8NuU93TZ9EobQN9m8+Mrw1HySZP0E/Y+n/Nq0DYAXppyi2+bWgebz+wAuKipkZGpq2DbTMzPon2Jeej9OUTilR/jzZeDJKWILC3+bo39N7pgiNnEbNNiBS8cpKyiCHvlidnqf42iroxGCHsfbsCdFz0vUNrUAZWwPcCpgl8Emt/3/zHjs5wxFSox+wYsfCmt+f4JwH8tui85cHwDOfFLs/PwJkCamL9BVPDznYXokmM9bT7In8cjxj1g4osghSRJFL/63Tc3rMIqCnJLSJul8NC5X23zzEPb+/elx318iMFLrkSSJAZN1agwZ4Gf/jE4138nnXEBef/OLHqm5PTjpF2Lzwc7meyHuEiNGjBgxvh/ExF06Ruz9GCNGjBg/HETfkRbFMnQtaosb/3/egpZ2YpNtCspZc7H1Flt189UdRPtP+KLmzhufF7IBULn8QRq3vhryeOFFn2N3ikkFb/n6fg7ufSNMCxtzzv1KyIaqBnhlwVm0eNuv4yfj4vIT5wuXp7hh2dmUe0tCHj+9x+VcOMB8AXeAl/cu56H9oROVhyTk8Mx48ST2369fwoLqA+0eS1Ps/G/mWSgCSqsA75aU8sDW7bSXlWaXJJ6YMJb+ycbCNUNR0eLh3C/3hjw+PtXO3yf1E7IBsPpggJe3+ClrJ2WsIAn+MMOJyyb2fe3a6Wf50vZzPRxOOOVHDhISxMMwPbUqu172tpvvlzVJIXdydO6SaapGYOFe1O3VkBaH/eT+yMnRo1AaA056cCFbK8yJPcjAnr/oRzN0W0rXwlOzMZWwpDjh6i8gN3pr2f15+Z95Zfsr39TnM4KERGZcJjePv5mTeodX3Y4GvHv3cuDn1xIoK0PJzibxuONoXrCAQEXb3EY+LN+vadjy8si46kpSTzutC0csTl15Ey/9YZXp8zMK4rjg9skWjiiybF2yiA8f+Vvoun1hmHftjQyb2b2jHKI+1FNTVfyPvti+0wcQCBJ87eM2ERgROzpOH4D3gfClGPRoKl4S1ukD2P+SWP27pvpdOk4fQIDFH5wlZOeFT08K6fQBqHh49pNZQjb+uPrnYZ0+gP+VPUu1O/Q49GgN+MI6fQBbWiq4e+v7pm0A3LkhtNMHUBf0c+6S/wnZ+LKikvtDOH0Afk3jyhVf0+TXV8wMRzinD2BVvZ/X9phXDgXYVBXk7yvbd/oAipvguk8ElF2AmupgSKcPwOeFd940oMyig+rX2Plc+04fQNXyIKULxO10Bf63thBcegCtxo22qxbfE1+jBX7AgiFRxnn/+sq00wegAn1u009h6JZ4GuGpWZhWqQh64fEpbXX+opA7v7qTl7a/1CGnD0BDo8pdxS2Lb+HTfWKlQLoa1e1mzymn4t+3D83nI1BSQv3zzxMoKQG/H/x+1IaGtv81NuLbvp2Dt9xK3Wuvd/XQhRBx+gBqit0seXOHRaOJLOV7d/Phw/ebcvoAPnnsAWpKxIWROpPod/xKKwxdIP9i8zdyYP8m0+d2hIpF/2eoneo3L4e++gtj4i7+1lLTNoKqH19QX0VV1cQcjK1NxmSyf7/mStM2fr7mBUPtPqjYYNoGwBdVoZ2+w1T4PELlCZ7YZUxp6s0D4Z3pcGyuN6YI9sgOMdXY/+3QV1xrDUCD1/z3tWK5/v2paVBRLjaxq92gf37d1uibPGqa1rbT9128QdQ9xtRlY3Q9K/fXC/cRtW7+4r9b08/Sh63pJ8K8v0dsMRPgmU3PWDCSrqPho4+PLelggNrnnuuE0USGqgNimySHWf+Z+XlEV7LwP2Jl2QA+eeIhC0bSeUS944fLYIHmJIHwyIRU8+d2ANlucIyyeaU1uyPV9LlGkQ2qk0aKdLv5ROXCOGPKoaI/JKMhnLJkXuQjyW4srDbDYT6sMM1hzIZojHmSwSE6BC5MnMGIRKegepnNwM9ejsKgfEmS2oRdjv67Kwo/TIwfHskGBN2MkFpgTT8RxikbnFuFIdkhljbQ1dgyjL3/j0YRTJfoSuKTLHo+R48e2RHEp6YJ95GQau6+iRRR7/jJWentK3oehX3KaNM2bJk9jTV0mldDBOh5ioGVBsmGLJAXN9GgWmfBgJ+YtiFJMj3SJ+i2S44vNG0D4Io+xgqk3jPhWdM27hp+prF2g421C8UN/cfotjklR+z7+v1QfXVTG3BSD/MTnh7xDgOasfDMlN6mbQBcPNTenk9xBP3SJOLs5t8+U6bre5dOF6SmiT1GUwYoup5w3ozolNW3zSg64t9SbgJyQWqXjCVGx7lt3gDhPvpkGqhX0h2ZdI3hEkshUZwwTCxtoqu4daJ+eks4ZGR+O/63Fo2ma0icMQMlM7NjJykK2bfc3DkDigAJqdb8Xs+6eZQl/USauVf/QriPE6+9QXwgncj3RtXTt3I92tJ1bfH0AbVNWtemQL9eOE6eLVTO4TDe5+6AmhCxuyNPwDnnx8I2gr4W9r5yGgSPzatw5k+h1wkPCNtQ1QBfvDmdUEE4w6Y8Rk7+WGE7O0s+ZuH6P7ZrZ/yA6xnV/2JhG7vrt/G7dZe1e0zBzn9nftm28yDI5IX3hjz2+oSf0TM+Q9jG3qZ6fr12AVX+Y3PT7hs2jWk54rLgLf4Ad27YyLq6epyyTKrDTpXbQxCYlZPNHcOHCu0qHubmFXtZUedp99h7M/uSEicuVuIJqLy/M8CGyiB76/kmdzHNCecNtjGzUNxZCgRU5n/qpeqoyFS7HQYOUhg1xhrRFU3TKFvsoXY9bR/k0OMqLg96neDEmRq9a3RqZTPBdRXI+UnIQ7J0f48xVc+O0dmqnuv313Lmv5aZCtm8dV4/fj57oOVjihiaBi//GHZ0NOxRglEXwxmPdsqwIsX+xv3csugWSptKCWgB3AE3EhIaGioqDslBUAsSJIgdO5nxmSTYE5jWcxo/Hf5TkgQXw7sDmqZR/fTTNM+fT+KMmSSfcjJ1b7yBZ8NGUFWcw4ai1taBJOHo1ZO0iy7Clia+a9TVPHHTAgIm03t/fO9kUtKjdMEHCPj9vHH37yjbuR0teGhmcei95UxIJOj3EwwGkBUFWVJQNQ3V7yU9v5BL/vwAir1zF2pjqp6HSU8Fhw1UuS0OTAOSEpAH9bXE6QNg4ARY2o7jJ9mRport+BxGtsfhyhmK5+AG2tQebIAfHFmkDxcTj/nGhmwjt/fZlO89OgHZTmr2BEucPoAEVy7tJcYrxNOvh3h9KIC+qYO4fuA9PLP9Plr4Nq9QRuba/r+3xOkDuCBnDK9UHJtTmIydHi5rHvK5cQnkuZJo9HsJAg4k7JKNoakZjE43VnxdjwS7jYuKCnEpMsVNbU/1JJuN5mCQTIfdEqcP4NSeqXxdV36MkIwEOGzW2HDZZOyyiiRBkh1a/ZDshNQ4GJ9nzW/eZpMZPMSOc48frxdkCdyetvWl/J4WLpqpkNLfjrfRj+oGRxr46yBnhi0qnT6t1Y/W6EXKTkDOTkQ+QUyJOEbXMbxXKj1S7JQ0dCwnu39mHJdP7dtJo4oQkgTH/RaKl4LfA454iMsEdw0E3G1pF4qtbWewtQE0N6BAeh84/o9dPXph8hLycNlc9ErqhUN2UN5ajj/gJz8pH3ewTWsg1ZlKsjMZp+ykuKmYoBrEoTi+F06fd98+WlevQUnPIOOaa1Dr69F8PhInTiRxyhQkmw00jbjRo2n+4gvsPXt+L5w+gMmn9ebLl8MLtbWHI1GKaqcPwGa3M/HMC1jzybvYnS4cTheqGkQNBEnNyaWhpoqW2loaqirJzO9JwfBR2B1OEtLSO93ps4Ko3/HTNA3fg/8BfxjxA6cDx/WXILVXeNMghhQ7h07HOe9q0zaaS1dS/un1YdvYEntQdO5bpm1omsaCNybptpty8rvEJZh3Np7/eC5eHYGXHpmTOGXiP03baPE3cc3Sk/GHkkMEZGy8NEusNEW43b7D3D/kHKZlmw+Ler14O//YGV6s5qYBYzirl/nVc5+qcu6iJdQGwgujfDlXTIp47idb0dNUmZXh4q7x5sM9K5qC/FpH6fKsATLnDDafpxIMqrz2spdgmEdLYiKccbbYS85dpbLndS9qCBFSZxYM+HH0vEgDq8sIfLoLghpSqgv7RSOQOzARiO34dYzO3PH7YlsFVzwr1vftJw7kp7PEy7d0CY9OhKpt5s8f9xM41SKRmAjzxrY3+OMK886rhMSyC5eR4EiwcFSRo+RXN9D0yScdPi9u9GiKXn6pE0YUOR69JrySuREuu2ciiRnRee0f/9mltNSbEyFzxMVzxYOPk5jWeXl+ou/I6FtKPgp1257wTh+A10dg7VbTNgKNNcYabv7StA2A8k9v1B9Lcxm+Bn0FyFDs2mhMsWjlZxeZtqGqQV2nD6CserlpGwBv7Hs6rNMHoBJgZ4N5VdbXS4xNem7eolciIzx6Th/AgzuMqZiG4plde3SdPoCb16wzbaPS7dN1+gAW1rQfBmqU+1fqlzd4a4eYnuDqrwNhnT6A5mbweMTslC/2h3T6ALxV4GuKDlVPzRMg8NluCLbdBFq9h8CifV07qBimEXX6AO79eLsFI+kC3PViTh/A109bMpSu4K4Vdwmdr6HxywW/tGg0kcVbXGzK6QNwr11L06JFFo8ocvi9+nMEIzx3xwpL+ok0BzZtMO30AfjcrXz25CMWjsh6ot7x0yqNOWXawUrTNtTSSNUjMfaD89aaH09N+TJjI/Gbr93k9VsjB6xHcctOg+12mbbxZVX3mbSIyqLvazF2TXc2hSiOZ4AdjWK184wSIn3QUurrjH3jzU1iURO+Bv3zvbXdPzIDQGv2teVYf/dv9ebLz8SI0WU0mC9p9H1AM1u/8DvsbthtwUgij3eb2HvfsykyJcA6g8Zai16u0fHKOobireLXrqHSfO3oSBD1jp88Sl+pEECZOMq0DcfgyabP7Qi2VGPhMAkFM03bGDbpD4baZebPMW0jzplq+tyOcGL+eYbaTc42X/T+rqFnGGqXIhvU/g9BsqIfF57hEJPXPquXMXXamwb1N21jWk5k8jqm9dR/dDkFBfmGDDWWAp2ZJWYopb/++Ym9uleJlFBIGXFIWUeG9yiDzJdTidG1FKSJhxjH26N0mpEzRLwPgdJLXU2qBaWfrht1nfhAuoDEOcchmc3VkiRSL7jA2gFFkIw8a/KxMwuiM697/KlnCPcxdKZYukxnE6VP5G+RU5KQ5k4J32bmBJQswYTb8WfoNrH9SqxYadGZ/wWdWn45s/8iVM4hMbk3qZkTw7ax2dMZOeUe0zYAThyvv9V90ewPhGyMz5rFmYXhi7Nf3vdG4o0USgtBqiOBmWn6DvnHM/TDdMPxzvQzcIT5OSYoNl6b8iMhGxMzM/jlgH5hy+uMSU1heo6YkMxtQ7J12yycN0jIxhUjnQwJI6SqAI/NE3OUe/ayMWxYeIfruDniDlnOFBtZk5SQT+Ois+1IcnQURZIkCccFw1BG5iL1SsF2fB+USQbL4cTodiy+9TihclyKBOvutEbIK+JIElz1uUAHMvwmUtFC1rPw/IW4BBY0J+VN4tyB51o4osghKwoFzz2HvVdPkOW2e0GSwGZDSkxESkiAuDikhASUzAwcgwYhJSVhy8sj/+GHsGeIq3x3JVPOFiu3BHD+7folvbojjrh4jr/a3IKFzeFk7KlnMv60sy0elbVEvbhLjBgxYsT4/hATd+kYsfdjjBgxYvxwiJVzAPyVNaj/CaN0ObgPztPMhy4CeDcuhs/CJ2or1z6OzRUvZKd0/m24ixeGPJ5/0pPE5Y4QsrHsk8tobQyXtC4z51xjuYChKK/ewHsrwiucXnzcR8THiSkfXbJwBn5C55Vd0fdm5vU6R8jGbetfZ1Fd+HzCZbNuF7LR5PNy4peh72EJeGXyqfSMFwul/N3a9Syubj8vNtVm46Vpk0kSlCP+pKSWezaFjnFPVODDucZCtEPhC6pc+7GX1hBpsQ4F/jrbQXaC2I7cl4vc7N/X/rGevSRmHScW4gsQ9GjsfsODt6r9485MGHCJNaqeWmMQ//xmtOoA8kAntmkJnbabGNxcSWB1Gbj9IEtIWQnYZhR1SOEzRtfT97cfHNbqMcX2P52I0x4docrHsPdLeO5U8+df8i70NZ+a0dVc//n1fFH6RYfPk5C4Y+IdnDfIWDpGd0RTVfacdRa+o/P9XC6QZWRZxpaXh71HD4LV1WiApCgkTJlM5s9/juwUizjpSkq2VvO/f24Q6uMXj3fvcMdwVBXv5ZU7b8Xnbu3wuZmFvbnsrw93wqisI+pDPYHwTh/A1j0EBVQ9AV2nDyD42DVCJpqKvwzr9AGUfvRTNNW86lJry0Edpw9AZe3im0zbAHSdPoAXF5wkZOP/Vl8d1ukD+M/u+/EFzQuO1PtadZ0+gLkL7zdtA+BHYZw+aMuTvnBZR4sIH8n/iktDOn0A9YEAP12+SsgGENbpA2gOwqNbyoRs3LYgtNMH4AvCb+brK3+Go6TYH9LpAyg5oLFhvZgNgH3vhXb6ALzVsP99axLuvS/UEVzjRi32E/ismcAi8yJO4QjursX/9la04ga0qla0ihbUTZX4X9yApnb/KJMYbcy+f4GQ0wcw6PcfWzOYSBPwijl9AC+cZs1YuoDH1j1myumDNmGYP634E1tqtlg8qshR/JOfHOv0AXg80NqK2tyMb+dOWhYtwrN5M97Nm/Fs2EDN409Qed9fIz9gCxF1+gA+enK9BSOJPJqq8t/bbjDl9AFU79/L+//o3tc/6h0/tcGYgmRgpfkbOVhXbvrcjlCz0lhNO0+VeSd23ZfGctFqK5aYtuHx6ZdysILtTcau6aJy8w7Tn7a8a6hdMx0rbnw0Rs5WaavDaJYX9+/XbVPi8eBXzeuHLq809nt8rbjBtA2AcgPP5IAGNW7zn2XdWv0SCjt3iJVZUAMarSX67Rr3iDtLam0ArfxIbzm4pXPkUdXt1e3+XWvwoB2MjOpvDHH21ogrskatm79nsTX9VESn8/PWTvP1gg/z+vbXLRhJ19C60vwiaONnn1o4kshSV2HNYuCeNQbLoHUzqg/sR9Wr46TDrq/FIuY6m6h3/EgwFlopZaaaNiEndl4hxu/izBpmqJ09Kc+0jaweMwy1k2SHaRsOW2SKdtowNsaByeZDY4/LEhMhsRpJMh+WV5So/1tRALts/rHQL9lY6GOaXSy8UDF4epLDvJ30TP3vIVFQxFRSQDIQEaRYEB0pJchw1PchpXdOCJ4USg1SlpBSxMNjY0SG6J8gCJBlXt34CFKiU9yoR0IP4T4Gpg+0YCRdg5KcbPpcR0GhhSOJLAmp1oSo2gTevV1JYkamcB9xySkWjKTziPrnumxToLf+g1X5kfl4Y8nuANnABGnwVNM2AHKn6eeJKan9sMWbvzH7j/i5oXaTT3rTtA1ZVkiK078mRTlieZf3jn1Wt42LeAqSzL/AT8kfZajdQ8MvNG0D4LICfenwOVkFQjb+MGyYrkLf/w0bKmQj02Un2cBP5eWZYpOqX47TN3J8oYLDqIfYDpMm6+c6zpot9pKUJIle8/Tt9D5LXBZecsrYT0mCQ063lKZgn9s55TeUsT2QC496+SkStjl9kBLNLyrFiCzvXCteyujG442VKep2pBVBltjzkNTe4DLvQHQl/5xtLAIpFNlx2Zw9oHurG4aj56MGi3Arh95FhxZlbVlZ5Nx2WyeNqvNxOG0oFqzNXfZnsflwVxGXmMSQmWJz0/N+f69Fo+kcvjeqnv76BtS3Pwe3F/oXgj8ADU3IQ/pjH2nNqpN3z3p45+/HHnC4kK/6B/Y4MWGXw9RufpXadf8G3+Et9wDYUuj5o6dwpYpN/g+zccW9VBb/75i/O+MLmHaKNeEZNQ17eG/ZzwgEfUiASltYmUISF815E5fLmlWR21dcyR735iP+pmDnlqF/Y2TWJEts/GfXIp4s+eqYvydh59NZN1tio9Xv45pVn7LP3YQMJMt2FFkiLy6JP42YRoagcNBh3i4u5t0DpZS3urHbFJyyzPiMDK4fPBCXYs0O0LqaJm77uoTWox4v41IcPDC5ryU2/EGVJ9Z42VgNA9JgaJZMSaNKUIULhjpIcVnzWXZs87Brp0ZCIjQ2gDMOiookBgy0budK9WtUr/VQvxMSiyDQBP4WiM+TyJ3sFNrpPRrNo6LVB5GybZ1eJkKtaQW7DJ4gUqIDKV7fgY2penaMSKh6nvD3L9hR1bGcl0Q7rLnzRBzRKuxymKpd8NK5bTl/ktL2v5Yq0DSQZAh6wZkGThe01kPQB0nZcOGLkDu8q0cvzKtbX+XNHW/S7G/GE/SQn5BPkiMJSZZo9DRS3lrOuOxx7GnaQ7wST7w9np+N/BkjssVE6LoDmqpS/eRTaIEACZMm4tm2nYQpU1Ab6iEYxJadjS0zE19xMfbcXPzl5Tj79EFyRP/iVsX+Ot7489oOn5eca+eSP0zvhBFFlsaaalZ/8DZxSSmk5/fE7oxj3/o1yIpM3cFSVFUlISWVpupq/B4PwWCAolFjmHbejzt9bDFVTyAYCKAuWgU1dRDUYM2WttorioyaloI2vD+SQPjaNywJ4RD5PKhLXoW5VwibaDm4jtqVDwFHxRgHGqhZ8xT5x/1J2IamqVQWt5+75m0txuutx2lBEfaVWx7FH2zL9/vu/D9IE19uvI+548VXRVZWLDzG6Wuz4eeRzX/gqVniwgKaprXr9AE04efL8m1MzxUPCd1QX8lud1v+UxCoUf2gQlVTDevrKjkur0jYRqPfz4b6Bna1HsrdCQSBIO8fLCfN4eDqAdaszt+9vuwYpw/g6wYfnxTXMK9AvM6RLwhNfolAUGNdBaypUHEpMCFfRtWsCWbQNI26eqivh9pa2uRVG6C6UkOWffTrb80Lvn6Xn4qlgAbeykN/lCDQrJExTMVhZBvVIJJLRsrt3GAPLaCi7q4Fm4zcOw0pOTrDfmLAq8v3ddjpA2j2wxMLdvJLwZqdXc4nt0LdnmP/LtlBUwEVPBXw3XTZhmLY8kHUO35fH/ya+1bdh19ry0KPV+LZWrsVr9YmmGbDRrIzmc8PfE5QC+LX/MjINPoaefqEp3Hao1fZ8jCOgl40zV9A4GAZ9uwc6t96E7WhEdXrwV9aCkDmL36Bo6gIX3ExgZoaEiZPtmbO2YWYcfoAGsv9NNe7SUyNXvXmxuoqPnr0AWpKD6DY7fjcboI+LwlpGfQfNxm/10vpts2ogcAhsbK2yU5LfR0j55xIkgXhop1J1O/4BX0+Ag8+F74Dm4Lj15cL/RC9D1yq38iVhPPaR03bqF7zOPXrnw3fSHbS77JFpm1omsaCN/R3wSbMfYmkVPM7M09/MB2N8IqHihzHlSctNG3jqa33Mb9CPwH9lVkrTNsAmLxQ30G9MH8C1/c/3rSNB7et4o3SXWHbzM3uxR+GTzNtY19zC5csC/9dZDnsvDVTbLVuxsf64kNTM+P58zjzeRAHm1RuWhBerfW3kx0MzxZzmF550U0gjHpodrbECSeJ7fztectNi47uTuGZdpKLomOdTnP78f1nLVpt2+KC1DMZxyUjkRRjz9/Yjl/H6Mwdv588u4LPt7Uv1GOUwVnxfHTTbItGFGH+kAGYV9EmuSfceOzCZDTw2JrH+NfGfwn1seriVbhs0ZnTqwUC7D3nXLzb9FTQDxEXB+62Z178pEkU/PuZqHX+Hr1mgXAfF945nvQenZNK0Jns37iON+6+Q6iPc39/NwXDRlkzoHYQfUdG5135HYKftr8TcwSBIIEt+pL8IU9vNKhO5BFTq6tfr+PAAqhePDXmP8uqBT8z1G71Fz81bUPTNF2nDyCoiinGGXH6AF7f/ZRpG79dbyzX8eXSlaZtALpOH8BnlQeEbPxz+w7dNlU+P00+8yUKFh6sN9Tuq2pzUsmHeWa9fomOV7aIlVrYuycQ1ukDqKzU8PvFFs/0nD6Akk/FVGMjSXBd+TdOH4BW0oi6IzoV3n7oiDp9AFtN7BZ2Cw6sQsjpA2gsgap2SgJEAaJOH8Cti2+1YCRdQ/OXXxp3+uAbpw+gdflyWr5a2gmj6nzK9tRb0s9rfxEvDdUVfPrEQ8J9fPTogxaMpPOIesePVoNy5K3ma7nhbjZ/bocwNoFUveal8L2tlfqNgKBA7TtNE5PCtZpqn/lyHCXu78+EtUXPizncLmi+BEJZa2QclBYDZkSH4nYb+z0KKj8bQosevw/Ne+x91t7fYsTo1jRZVMbJE5nyRt2Rmih+f6rNYvM+tTk6y9Y01lizUBMUL3HbJfi9Ar7C4T484n10JlHv+ClzjIl32EaYF3ix5URGmteZPcpQu7i8saZtTJr3gqF2g8aaV6WS5ciEpGXb8w21u3LAb0zb+Pf4Kw216+VINW0DoHe8vvJbnqC4yyW9i3TbyEBunPnQnIv6Zhlql24Xe/ScN1hfJGReHzElzAED9cNE7Q5wucTy14xUP8kcHx1hngDK8Jw2QZfDJNhRBnbvnIcY7ZMWJ37fievRdhFDfiTeh2SHfPPv665kTOYY4T7umXaPBSPpGhJnz0ZOMheqaMvNJXGGsdJZ3Y1B48XLeADMuMiicigRZtypZwr3MfGs8ywYSecR/Y5fRhq2s+dBqPwRhwPblWcjuQRl13/yD902zhufF7LR65THcWSPDNNCofC894QU/uyOJAoH/SRsm4z8eeT3PtW0DYArT9IPwb3qJLFQiIemvkWSnBq2ze3DHsIpUATNrti4vjB8fkocCq9Nuda0DYD/Tj6FfEdoxy7flcAbU08XsjE9O4u7hg8LORFLkCXenyWuxvXY+F5hj6co8M4cMaXd0bk2fj5aaVedKl6Bn4+2cWJfsUmrzSZz2ulO7CG+sKRkOOc88fyVwT+NQwnj92eOl8mZED3TZzkjHseVY1Am5KNM6YXzijFIcdEz/hjfsvb/5uEUSJOVgJ1/OcWy8USc69dheprkSIHfbG8TmotCnjvlOYalGastfDSKpHDf9PsoTIneenZKYiJ93nuXxOOPR0lPR8nIwF5YiL2gACUrCzklBex2JJeLxBPnUfT6a6RdcgkZ1/yMoldfQU6ITD3jzuDs34o5/YUj0xk+I/w8oLsy4fRzmHbBpSghXvxxySlhf9OTzr6A8T86q7OGZwlRL+4SI0aMGDG+P8TEXTpG7P0YI0aMGD8cYuUcAN+Xq9GWrgl5XJ4yGvt0sXmEd8F/Yd2n4Rud8zucBeZ3MjRNukB5wAABAABJREFUY/cLx0EwtOhJ2thfkjHiYtM2ABa+M4+gvz5smznniilh1jcV8/ric8O2+dHkJ8lND7fDGR5N07hw0WTC5UYmy2k8OUOspMMpSx6kNhBeiGbx9FuwK+Z/ThXuFs5a2n6JjcP8aehUjssVq+N4yoKFNIbI4VOAm4cM4pR8sVCPixdu54AnfJ7gJ3MGECdY3+vORW521bd/bESWxC2TnciC9e8WLfRwYH/o+6t3H4mp08V2/VS/xr53vbQUt29HSYT+FzqxJ0bPzoHmDxL4ZBfBzZUQUNt+oilOHJeOQk6JTpW/HyLNbj/D/qjz3tNh7e/nkpYQpXXNXjwPdn5i/vzBZ8D5BkTbuil/WfEXXtz2oqlzXYqLZRcuwybwXuxKvLt2sf/yKwhWd1zgSHI6KXjpReKHDu2EkXU+L9+7jNpiMfG9Xzx+nEWjiTyLX3yWVe++YepcSbFxzb+eIz7FmjrVnUH0zCRCoNbUhXX6ANSla1FbxW5iXacP4A2xePbSj64N6/QB1K1+WMhGU8M+XacPYMmH5wjZeX3x+bpt3ltmTGE0FHetuxY9QZxGtY69jR1Q5jqKDXUHdJ0+gBO+fMC0DYDzl76n2+b3mw0o2IbhmZ27Qzp90FY78L4t2yh3m/+tNHj9uk4fwI++0FcYDcfmqkBIpw9gQ5XGR7vFBEXKywJhnT6AvXs0PG7zYjgAB7/0hXT6AILNsO+d6MqUDyzeT3BdOfjVb3+iDV58L23s0nHF6BgT7v1cuI/jH1goPpCuoP6AmNMHsPUdaK6yZDiRZlfdLtNOH4An6OGKj8VrG3cVxVf9xJTTB6B5vRRfYqAEWDdEVVVhpw/g+TvE5itdRV15mWmnD0ALBnjhtustHJH1RL/jt2OfoXba7mLzNjwtps/tCJ5qY/V+gp460zb2bDBWZ9DbIlY6AIxMhsXCjLc1rDPU7j87/2baxiO75xtq5xGU/fYb/C4a/eYdgPdKy3TbaMCGevOqsa/sNabi5hPzlXh7u77M5epyMbnNHTuMnb9rl9i1bz6g/2V4a7t/SP53UYvr2z9QJz6hiBE5Wv2CP1SgxogEb3dk9bPW9LNUbLG2q3h/z/vCfWyp3WLBSLqGQKUxBfRQaK3RWcZk19din/swTdXdW9kyFNuXLhbuo7mu1oKRdB5R7/hJvXsaa1doTAGy3XOdYmqKRnGk9jbUTnaa30LuNchYmKhiTzNtI1IUxBsrMH9WYXgxm3BcUjDVUDsFsZBCoz/EJJt5kYyZ2cYUNwclmy+6elpBuqF2YkGeMLe3fvjQkAwxK0W9jZ1fVCRmJyFP/+rbk8Xur0gj54W4h5KiNOTvB4qg+C4ASY4onWaMsEiZb9zl1vQTYY4vPF64j6KkIvGBdBFKmtgcSHKKCQp2FUWjrFFgdsaLvuW7hj5jJwj3EWdSDTZSROkT+VuU3Cyk4QPCNxraHzk50bQNSZKgcIR+w+MuN20DoOfJT6J3SRL7n4Ukmb9s6VmjAP3J18zTPzJtA+DkCfrFX+eMulfIxj3jntVtY8PBqExjJT/aY3p2f+wGnLqPpv7atA2Ap8adoNvmF31HCim6/nrIIN2k3p/260OBgBpZXryDRAPP+1emG1vkCMXEfDvZYdZjCpIlThsglltSUGgjU+cdmJ0NiUliL7jc6Q6cmWGuqx2KTo8uh8k2swi5f8aRf3TZcJxnTiUwRtew+BbxPJ2PbohOWXuyBkKWYI5Wj/GQ3sea8USYYZnDOL7AvPMnI/P8KWJK511Jz0ceRoo3uegvy+Q/Ep07vQ6HDVeyeF7mVX+Pzt99dmEfBk8Pr+Sux4V3mY8yiwTfG1VPTdMINLeitriRkuLRAkEI+HGkpwlNlo/Gu301lO2ChFQI+qG5AfoMx9nXgGNoEL+nCW9TOa31xahoEPQTl5RNioX1gFRVZc+2t/F7GwhqEgkJ6QSCPnr2nkVcnLGdISPUNuynpn43ca5UWltrCGpB8rJGkJpkTa0YgBZvI+urV1PjqSTX1QOnLZ4GXz1T82cjWySlHQgEeHPfSpo8LdQ0NJCUmIikwOmF4+mRlKHfgUHKmppo8XvxBVW8+OkRl0IQyE80v3BxNJ5gkJ319SgaJDoceAN+8hOTcNltwmIoh9E0jfn7a3FJQXxoNPp8SJrEuLwM8pPMl9c4mkAgQI07SKpLwR1oe5YlOBTsocq7mEBVVVpbA0hAc3MQpxM0TSI1zWnps0UNaqhBjUCrH2+LijNRwhbnwBatOyaAFlSRFBnVF0B2GJtMxFQ9O0YkVD3L6ppZseMgrSpIqkpWahw+fxC3149dkimu95ISL1GYmkC9O0iiy86IgnSyUqJX0v4bNA32fAWORFD90FoDaUUgK6AGoaUOnAlta7ZBP6T0Al8TZPQBC58PXUVQDdLibyGgBqhpqaHF20JGUgZenxeH7MAv+VFRSVaSURSFWnctuYm5JLv0a9NGA2pLC5qmgSQh2WxtzzQJVI8HKTkZrb4eVZLA50NOSEBSVZRuLOzRETYtKaasuAbJFURyS2hqW2lKZ3wctjiJmtJGtIBKcnI8VeX1ZPZIY+ysviRlRv/vXlVVPM1NOFxxBAN+JFnG09SIJivIigJaWxi8zeGgoboKu91OXFIy8Umdf+1F35HfC8dP0zQCX61BXbEeAkfl5eRlYT/nROR4QeW9QAD/Q1cRMi/NmYTzF8by58JRufJRGje3X2Q9adC55Ey+SdxGyRI2LgvdT36/ixg0+lfCdt5YdAl1ze2LeGQmjeTMGU8K23hs010srv4g5PF7Rj1L39TBQjbK3fWcueKxkMfPzRvLjQPnCdkAuGPDYr6oKm332Iz0Hvx59ExhG5+WlvGnLe2L3QxITOTxCWOxK2I7WDWtPs5cvDvk8RHJNh6ZIl7ctapF5d8bvGyqguBRP8s0J/xjrlPYAWxoCPDR+34C7aTx5eRIHD9P3PnTNI2ST33Ub1fbFHa+iwy9fqSQ2ic6dvw0VUPdWoVa2YLSLx25V8dfgjHHr2N0tuN37fMr+XCLOYGS/jlxfPbr6FX3o3YvPD4TfCbynouOg4tfArt1C12R5tfzf83nJR0X+FFQ+MuMv3Bi7xM7YVSRpfmrryi/+24CVdVogQCoKihK24JAMNhWy0+RIahiy8oiYfp0ko+fQ8Ik85FG3YFHr1lg+tzhx+Ux4zyxeVdXUrZzOx88dD+NleXf/E1SbGhqsO26t4NidzBg4hSGzjqewuGjOnV8MccP8L3xSXjxFkXG8evLkQQmtN4HDCg0yQ6cNzxt2kbl14/TuPHZsG3iC2fT47g/m7bhcdfy1fsn6bbrPew6+gy+xLSdFz496f/ZO+/wuIqrD79zt6p32XLvveMKxgXTe2+hBBIIoQdCSSBfgCTUQBICCTWB0HvvNtjGxjbgAu69W+7q0tY73x93hWVb2r2+c7XS2vd9Hj22tHPnzO7eMmfmnN8hEI6f4Jqb2Y1zxr9i2cYrqx/jvY2NO8kNeXn8LDSF8NgxUxOHpN7Q7WjO72Q9NvyXcz5laXV80Z4+GXk8O9r6g3RJWTm/+j6+Am66y8VnR6k5mOM+XZqwzZAcL4+OMZej2RgVAZ1rPw/u5/A1RAAvnWZ90hUM6rzxavwEdZ8fzjlPbWK34vlAQvGWDid4yOvT+mXRwx8sJ/rDnoel57Q+uAa2OaA+HMfvwGhOx++6l+fywY9bEzeMQ0m2l1m/P8amESWRcB38pa1aHxlt4Zbl9ownyVz40YUs3KmmwvvI+Ec4pksKfvcxKj//nM3XW1sEb/N/fyD/wgttHlFyUHH66hn/s14MONKcBkdronTlcl6+U22DZeLPr2TYCafaNKL9UX1Gpm4MUQwZCidW7IzqRBetsmxDLzP54NPVJNcrFyau91O7/iuktK609v0Uc/LKaxep7V4mcvoAyqvXKNkw4/QB/GW+dWndx1aYW+38xxo12fNETh/Ashrraq4Atyz4MWGb2miULQqlT15eY25nYEGF2rXy4apIXKcPjL357TXWr5X53ydWIwwGIJpoIHHQw9KUYue2b1q/MqKsCxPdx0mIzNnUQqNxsANVpw+gtDK1SpH8xCe3q/dRsxU2z1XvpwVQdfoA/jJHrcRVS7Pj7/+wfOzu51K3fqMdTHtJrWRTSzH9pf8q9zH3o/dsGEnzkfKOn+kYepWQL5vyxBJjNmTMemiZcJkNGUv93IR6fC7r6lo+zdznlQqfltvkteJSCF3M0JLzSbhN2nEpDEczucGmFOlp9thUuFMLsf+HofIFODi0JG6bVBnN3kgOQlQibVoDwm39u1M51qHl0NzqaqSajRoDzUHrHp0JhMeN6N8jfiOPG1c/62FlWk6xuYZ+NQnX/BGJQwqye52ulFM06ujnTLXrO+L/LNsAyPIn3uIvzlMTxLmkq7kQjFsHP2zZxhU9zClT/V8ftW394bmJw+FG5po8D5vg74cNTdgmz+2mTZr1fNjTupiTgj6qSK1Eyik93XgT3J9dQEG69Vvc0GGJS2dkZICm4OxqbkFa28THtxvX+nP8hN+Na3gD0SYB7sM7tdyAHJS5dExH5T76tElRoYfj1FSnAcjrDiWD1ftpAY4oMVfKKB73HWk9LaU1UHzrrZaPLfzVlTaOJPU47leKirgtxIRLrlDuY9QZ59kwkubjoMjxAwj/uAx96ndQFzD+IARoAnp0wXPSODSP9fpnYAgwhP51NQSbKObepge+n6k5SwDlqz9l5/S7Gn2tYNSt5PU7U9lGdcVG5nx+dpOv9xlxD+27qIuVTPn+TtZs+6LR13p3PJtxg25RtvH5hjf5z5qHmnz96TGfk6VQ9xCgJhLi6BlNy/P+sdcpHN9uoJINgKdX/cDz65c0Kh90aae+XNlziLKN5eXl/Oq7eftpiABMKCzkniEDlcVKQpEIJ0xeSVPBied0yOS6AeoTyuqgzqtLQszeIqndR3ylazb8eYJf+b0EAlE++ShETfX+r3XvoTHmCHt2BbbNDrJzvo5en1IYOwk0H3Q7x0daUeqs0UXXlCF31KB1y0MrOvBJv5Pjd2A0t7jLE18u5/7PraVKnNy/iMcuVq+L1WLUlsGTE6Bi3YEfO/xXcMK94ErdnZ/H5j7Gk4uePODjMl2ZPHXsUwwsVn8utjR1y5ez9Z4/Edm0iWjUUIvXPF5kNIoMhRAZGWhuNzIQwNO1K5lHjiVr3Dj8fVNX3ATg8Wu+3F9szCTH/KIvvUaU2DugJFK+bSufPP4IW5Yv+elvvvQMIuEw0XDjoetp2TkMOOoYeo8+kjZdrW80maHVirsIIfzAdMAHuIE3pZR/FEJ0BV4FCoC5wMVSyrhJAKbKOUSihJeuQe7YDTt2QttCKC7A3aEEV5Y9K47hYC36i3dBoM5wLPUweNKh93B8Ey6wxQbAjgUvUrnxG9Ky2xCNRAjuWgkIOhz7EP5ce5Jly7YvZN7XN4NegbE3Yvx06XMJ3QdebosNgGk/PEBF5XrC0Vqk1KkLVdAmbxDHjLjHNin8D9e9zOvrniJEAGPG7KJHWl+u6f9HSjLt2XFYU7md6+e/RIWso6GPcXRub/405CxbbAB8WbqOz7auoTIQItfnw6e5OLy4E8eUdLbt89oeCPDooqXsDgbJcLvol5/PovJyftWzO71yc22xUVYX4qbZq9kUc2Q0oMADw4syuWmQutNXTySqM2NjBIgSjGqMbu8mx29v4diqqjDLl0bIyIJwCMJBYy7Xo5eHzEx7JnVSSsqWh4kEotTtNG4t6W0hu4OXtKLmK4Qra3TwCoSneUMyZU0IfG6EO7EDe6g4fnY9I5NRzuGmV77lnR92kOOFoiwfWyuDoBtquvUihy4gIiHdC2HgktHduPn41J78AlBXAR/dCtXboPNYaD8EtiyAsrVQudUo5dB2IFTvhMqN4MuFzAI44gbItKcYdkuycPtCvtz4JeFomGHFw1i5eyVloTJW715NYWYhRGF91Xqi0SgZ3gzS3emc2+9cxnVMzTpu+xKtqaH2+7m4S9oiPF6Cq1fhzs4Gn4+6FSvQEGRNnEDd4sUItxtf+w54OnZQEhNsDVTvquP5P86CRhStG+LJhHCDhdFRZ3Ri+HEJovBSgGBdLbs3bcSXmcnaBd+zdc0qXG4vBR06oWmCSDBAm+49CdXV4fens3nVckp69qLLwMSRVaq0ZsdPABlSymohhAeYAdwA3AS8LaV8VQjxBPCDlDJute9ED7bwrPno0+M8+NoU4vv5GRbexR6C/77OeADEQZx4Nd4+1iV8A+Xr2fROgi1izUePS6dZtgEw5Y1RCdscfvKHSvX8vln0MIvXvx63zajev2FQj/Mt2ygL7ODXs0+O28aDjxcmTLdsA8yper4z8hraplvfWZy9q5SbF0yN2+bvQyYwosD6KpouJWdM/ZrdjdUmiOECph6jJr9+2uRllEXi31ceHtaeEcVqdZ4+Wx3k+UX7i7d0y4E/T1CXUJdS8ubrAYKBptv40+Dsc9VslS0Ls+mTpr8T4YHel/vwKISt7osM6IReLUdfHQKfwHN8Fu7hauG3jdqpCxN+cwn6+nLwuXAf2wP34PhKiYeQ42fLM7I5Hb/563dxxr9nK/Xx6i9HM7qHfbVOk8pTR8EWBXGW4n5w9Sz7xpNEvtnyDb/+4tfoWBfI+uD0D+iS08W+QSWZLbf/jop33z3wA/1+Oj31JBkjU3O32w5Vz6sen4Crlee6NcXnTz3KwimfWztYCC57+F/kt7dvgXt/E61U1VMa1K8DeGI/EjgKeDP29+eB05XsBILxnT6AbTuJLl5p2YYeDiV0+gDkx03XejPDpvcuMjGYIDVbE6szNsXSuQ+YavfNR2qOciKnD2DO8r8p2bhhTtPhqvWECTK99GPLNiZvS1yaAOCMb9VUUH//Q2Ln9BYTbeLx8eYtcZ0+MCI7Xl691rKNrbXBhE4fwM3zGq9XaBZdykadPoA1FbB4R4JlShOsWR2J6/SBsfm/ZpWarU2fxj9ehmHjR/YqI0am1xhOH0BQEv6gElllMa4nnp0ZGwynDyAYJfLxCmP3zyFpz0gVVJ0+gPOfUe+jRajapub0AWxfAmUb7RlPkrlt+m1KTh/Azz/9uT2DaQHCpaXWnD6AQIAtN/+WVEil2pdArT335+dun2FLP8lmy4ql1p0+ACl56171tK/mpFndcSGESwixANgOfAGsBsqllPUznU1A+yaOvVII8b0Q4vsdO5qWiJfllabGom8oPYCR72OjbIvlYw8I3Zxke9UK61KxO0tnmmsoW798fEgmmJXH+Han9dWrD0rnWz72QAiaKNERVijjATBvt7lyEFO2WyvWDPDdzlrLxx4ItQlOz0U71B+4paXmPu9NGxWdTBNDDeyydwKhb9tnzDroNjjL+yK375MTHZXI3dbLhRxsWH1Gmn0+Oiiw9mt7+lnZeJ57a6cyaG5uFY/yYLn6QFqI2rnxa94mIrJjB3pNcp6HdrJpuVrZqHoCVfY/T5LBzg3rlfuoLrPnM2wumtXxk1JGpZRDgA7ASKDPARz7lJRyuJRyeFFR0yGHoqjAlJ66Nqi3WdP74SruYq6honSxSDOXD1Awwnpduh79rzHVzutXU5BMBiV+c/l7Z3W2rtJ0a+/Exe4B/KjleuV7EouE5LrVlB1P6djoGst+XN3TemLyse3NhbuqZj9kekXcPiZ2Vr+19e5t7jvtN0Dtu9dM6E5l9bD3Vu3qtc+5lCbQOtivHKr1yN/7DxkeRIma+vHBhNVnpNnnoypeG047fzPnjzYbA9SF1AAYmppFvDtlq+fH98rtZcNIWoasSUcp1erx9++HKzP1FG17DE2sMG6GzgPybOkn2XQaoK7C27ZH6z7vkxKAK6UsB74CxgC5Qoj6mVIHQCnmS7g0XBedGvcC1UYPwdVe8WQeflLCJq6rHlMy0e3cd0lU2MvbdgSeNOu5ZCVdj8PjS5wnduQpH1i2AXDa4c8lbHPexHeUbPxt9BsJ2wzKGU3XbOtOf/u0PHr6EzvkX02wLvsM8OKoE/HG+e49QuOl0YnPwXgMzcvjhJL4+VW9MzI4rNB6Po7PpXFqu8S5e58crX5jvHeit9Eb2Fm9NYoz1BPri4pddOkSv03nroLCIjXHr8cl3rh34rR2gg5H2euUuUak4z4qE1HoQuvmxXdJHsJr/wTdNaI9riM7I/LT0Lrm4j1/oCmBl0ON5nxGqrDoHnMLX/FY8H/H2jCSFkDT4DjFcgTjbgeP9fI4Lcl/jvsPJRnWc8oz3Zm8cvIrNo4ouWhpaZQ8+CBYUIT3Dx5Mh8fV0j9ako4D1ZTQAU6+tvlFTpqD3LYlnHj9rXj81nL303NyOfvOP9s8KntpTnGXIiAspSwXQqQBnwMPAJcCbzVIXP9RShk3OS4ZqmUODg4ODi3PISTuYssz0nk+Ojg4OBw6qD4jm7PATAnwvBDChbGe/bqU8kMhxBLgVSHEn4H5wLOqhmQkQvjdycjVjSRRC3D//AxcxWqyyuGaSvQnr226gduL7/pnlGwAlM54gJqVTe+ElRz3JBnt1Laif5h1Fzs3fdLk625vIeNP+0jJRiBYwQuT46/0Xn7817hcajsZ1848lZ3hbU2+/vuBjzKoILGKaTw+3LSAv6xqWiAmEw9fTFCrSRjVdU6d/jbl0caT19Jdbj4ZdyZuTW0n67dz5zMnTq7fr7p34aJu3ZRszN9RyQ1zm96k0ICpijLvuq5z0QfBRl8TwOBiwTXDfWQohplt2hhm6peN5yoIAeMmuOnYSa1GaLhaZ+27QYJNpGqltRP0OM+eXQO9PEpkZg3U6LiGpuHqaU8dwp/631VLdM4mZDCKSHMjq0Lg1iCqI3L9uEd3RGS2/mL0SSJpz0gVjn5oCqt2mcunbox196tFKrQo0Qi8cBqsm4mpZNx9Oed56H+63aNKClJKjn3zWLbWbrV0/EV9L+K2kbfZPKrkUfbqa2y97z4IGs8Z4fejFRYS3bTJaCCEUcekXjBNCBAC4feTd8EFFP/2ZttKMCWbuuoQ//mtdXGWbsMKOOFK9ZDJluL7D99h+kv/ReoHrqvQd8IkTvz1b5phVPZxUBRwD772MayLHw3jvfkyhNu6nxt85JLEjTLz8V35d8s2ds5/lvIFTyds1+My6yppgdrtzPzolITtCkomMWRs4jIGTfH0R2acLcEVJ1l/L39feAezd01O2O65sVPxu61t2weiYSZ+3XSB+HpOazuE2/ucaMkGwMnT3qIsEl9NK01zMXniuZZt/HPZSl7fmFhh7n9jRtI1M9OynXGfJlZC9Qn44jjrzt/P3qtLOA3rlA33T7ReaiEclrz2cuIJ71nn+klLs/6AX/SvOmTjPuxPZHYRdD1DzfmTYUnwHzuQFbGHmQDvJXm4etjj/MlAhODjc6AuTmmKogy8Vx4Wd0J0qOz42UVz7vj94rlvmbJMTTxGAGtT1fl79njYqFiO4f92g+KCXUtw0tsnsaFqg1Ifvx/1ey7oY1+N42QRWLGCtaeeptRH/uWX0eZWtRSQlsKOcg6n3jCEjn3zEzdsZayYPZMP/qYW4j32/EsYdYb1uVoiWm05h2Qho3pCpw8gutK6Uo+MmlQnqt5t2QZA5dLEJRAAKtd+ZdnG3Ok3mGq3q3SKZRvmFxPUFh3MOH0An24297k2xnPrzamgvrd1gWUbQEKnD6BOV5Pbf6d+pTIBDyw2V8KiMWZuS1z2BCCouN5k5vANlbCrzroS6qIfzSnbLjbZrjECZdGETh9A9Xr1BTp9bWiP0wcgIbrAPoVNfdWuuE4fgNxRg9xaHbeNQ+vhS0WnD1Tv8i3MRhtKUXxlfQG1JVF1+gCe/bFFN6sts+3BB5X7qHjnXfWBtAC6bs8V+/mzi2zpJ9l8+15i7YhEfPfB2zaMpPlIeccPTYCJIpEiW0FJTkvOx+TymUuo9eZ2tWwjJ9essKr195ys8AaXSW3I9uldLNvomWFO3TQVAjrSXOY+r64Z1pXIOmbYGzqoggDS3Na/mdw8c8dm51q34fabO1bYsGEgMve/pkWWjTsRGSZCOAWIdLXQWIfk4Um9jSp7UUxFAKDdMPU+WgBhw1MtPy31dnwAfJ27KPfhys1V7qMl0DR7ZjPZBdajbVqSrHy1tDCA9KzEAnctSco7fkIIXMeOjd8oKx1Xe+vlCYTQwGtiMjz2PMs2ANqMvyfxWFw+/HldLNvoP+pOU+2GH/WcZRsAWWkdErbJzbDuwALcMTixapYLNyOKxlu2MalNP1Pt3hjxa8s2AM5s3yNhm4lFHZVsPDpsiKl2t/a3HoLZKdNv6qZyfNt0yzYAupq4r57Vx0W6Qo5f124eEvnKbjf06Gk9hNydppHTK/En1vF49XRsrZ0H12F7HsYi34V7jNr3sFf/XXLR+sR/aLrGdETkpKbK4aHIv392mHIfR3RLTVl3AI6/X+14oUHf1AxzvWaIudJP8fjr+L/aMJLkU3zrLZbUPH9CCNrefZdt40k2LhvW5k6/OTUXPI66/Cpjzq/AqTffYdNomoeDIscPQK+qIfz5DNi8HYIh0HVwu+DYI/ANtC7n35Dg95/D9Bf3f0G40K74G57MXGUberiODZ/fSmT7d/u9ljPw5xQNv0rZBsCXbx+PjDYm8uFiwpnTcbnUJ5orNn7MtB/vbvS1SUPvp1u7ico2AuEAV848jhD752Kd0u4iftbrOmUbAFfO+Q8L6xpPcp857nY0G3aF11aUcd38L6mMhhBAfVBepsvNw0Mm0i9XfSUqGI1y/ffzWFtdjQtBpzQ/K2tqCQOjcnP46wj1iR7Awws3897mxgsAPzemE91y1Osbzd9UxyNzjVAyDcj2QE46dMzSOKOPmzY2lHQA+GFBgEU/SupvlUKA3w+9ersYONgeoZLa0ijbvg0R2A2RMBAA3JBeIOh8mge3376tF31rGFmro3X2Ilz271XrpVUQikJBOnJbNaIgHbm7FpHjRytI7Gg6OX4HRnOrelbWhTjivi+oShyNvh9vXjGK4d3V71stSmUpvHctVGwClw+2LwEZZo82XgTwQlYxBMohXA1oMPh8OOPfLTZsO9hUuYmLP7mYnYGdAOS4c6iJ1BBh/5DuDC2DWr0Wl3Axvv14Hpr4EB4zRUpbKVJKtv/tb9TOX4BwucgYNYqsoyex7a9/JbxtOxlDh+Lu2oWqDz5Ey84mbeAAwqWleNq3p+Cyy3BnpXa90tkfr2Lu+wce7puR5+Hn9x3ZDCNKHtFIhOkv/5fl33xNJBxG16O4vT6iwQC6hIJ2HampLCM9J4fs/EKqdu2ktqKCws6dOeU3v8fjbV4Bs0M+x6+e8MfTjFy/uoDh9AlAStihlne3F03NkSQIm/xnKaNEKtbu/4LLT2YXdUepHo+n8Ym35s60LVQzzdtUPTgXmWnW6wM1xO1ykelp/Aa7vmqlLTYAavXGc5dcCMIWlJ8ao0NWNkPyi3FhTCX02I+UEIiq5ffV43O5OKWkBHRJta6zJOb0AZzZSW1HcW+aviAi9nxcDGnv59RebvoWwMBi6FUAeX5I94LPRofG5xP4fIbD5/EYu3yaBsKuix4QbogGwJNuCMUhwJMG3jzQFMJVG0Nr68HVzdcsTh+AVpKF1jkX4XOBSyA0gcjyQW34APJ/HVoLmpTUWnD6ANLTUnfi/xNrpsH2pRCogGAFpOWBv9CIAtLcGNOoMFTvALcfvNmx2OzUj5PN8+cRCu/58isiFXs5fQ3TLWr0GiQSXersDu7GLdQXj1sSIQQ5J51E29/eTOf//gdvt67s+t//CK5eQxSo/fEHKt97H1duLtHaWspee53q6dMRbg8uhXSJ1kKw1tqDurbKes57a8HldpNZUIQ3LZ2swiLSMrNwud0MPPoEMnLz2bVlA5FQEH9mNuU7d6BHdTLy8qnZXUZdhTmdg5Yk5Xf8InVBoo/+L34HQuC79ZdKYwj+4wqIJlBhOOJsfKNOtWyjau2XbJv6+7ht0juOp93RD1i2oetRvnrr8ITtRhzzCtm51mX935j6M8prVsVt0zZvBKccbr3o/fqq1dw298KE7V6dMMeyDYAxUxMn5/++x4mc0mGIZRtrqyu4aE7TJSMABmQX8OQI68WQpZSc9NV0quI4kW3dLt6YaD00Fsypeg7I8fGvMdbPr0BEcsXHAaJxbl9XDvEwobPa5OOVF+uI53NrGpx7gR+3gnO24dMgFUvjP2S7ne8hoyR1JlJ6aRWhl3/cT+xFFGfgvXgwIo5D4Oz4HRjNueP31nfrufktNZGGo/sW8cylI20aUZJ5sAfUqgjcCLir3K7RJJXP1nzGb7/+rVIf086dlpJ5flLX2XzDDVR9EROQc7v3lG0wg6bRc9pU3EVFzTPAZsYOVc8L/ziKvJLUc4Aj4TCPXXYe0bDF1S5g1BnnMvZ8E5UALHLI7/hFX3g3cSMpCS9YYtmGjEYSO30AM9+0bANg27T/S9imduM09LB1Jb5vv7jcVLvvJls/aaXUEzp9AFvL9g9nPRD+OM+cM//xhlct27h3yfvm2sWp82eG3/04PWGbRZW7lGzM3LEzrtMHsDUSZWNNrWUby8rMHbuowsT1FIf//BCK6/QBvLBIbeVx7ZpIXKcPjOCCJYvV7CRy+gA2fJRaq6iRqWsbVfiU22uIfr+lBUbkYAVVpw9g8lJ1ZdAWYdlHik4fgITFH9gynGSj6vQBXPzJxTaMJPnUfP31HqcPDszpA9B1Sv/0Z3sHlSRqKqzX7GzIy/eoLbi3FLPefEXJ6QOY8451JflkkPKOHzXmnCBZutO6jbDaJNU00tzNRQ9bl0OvqzUn6W/kMFgjElW7aMwSkOa++4UKDuaPlcmZpJaHzJ1jKjv0G2tqTLXbGbR+vq+osuehkYjS6sSfQ0gxOrZst7lQl/Iy69+J2e/TzLpTa0LGSQiT1cm5Pzg4KLFjuT39bPrWnn5SkJ11CvOuFiS8fbtyH5GtpTaMJPlU7bLpYdP6gwkbZfdm9TImrZ2Ud/zE+BGm2rknWA81EX6T29XpuZZtAHiLhyRuJDy4062HDwwcYy5MtLD9JMs2PG6zqn1qOUZHtz3DVLvfDPiLZRuPDvmZqXbFTeRMmuXsjr1MtVPJvzy5Q3tT7Qbmmisr0qiNjslR8LuwX+Kwx975aufXgEHmQisHDbYegimEQDORB57XL7Vu1a4BTasou/qnZvjToUiHXPXyLKl15jZghFp6yE9MShzJ0xrpnasuinfzYTfbMJLkkzVxIlpmplIf+ZdeatNokkvbbtaf/w3pOTI17/OHn6e+S52Z35S+ResgZe/J9XiH9YeeneO2EccdgZamJiGuXfZQghYuvL/6h5KNTic9gUhr03QD4abL+WphI4Vth5NVEF+50eMtYvDhakVnL5z0YcI2l5/wtZKNX/a5jRJf/O/+tI6X4HVZ/+6L/VkcWxC/vIEbeO+IGyzbAPhl90FMKm5aXMUFvD/2NCUbWR4PjwwZHLfNy0eMxq2gUKoJwV8GJRbumX689ZIRAH2L3Jzb19XoDUwDhrQR/O5wNWUtr1dj3MT4Tt2oMS5y89REHHr/woc7jthldi+N9hNbT31EM7jGdMR9Qk+0nvloQ9qiDSxG61uI54KBaJ1yW3p4DiaZcfvReBRnCavuPdGewSQbfzZc/K5aEc2T/wHu1BS4efO0N8lyWVemPKLkCM7tc66NI0oe7sJCOr/0IjlnnEH2iSdQeP11uNrGmZvtQ+FvbybnpNQs4wFw6m8GKR3vTdc49vKBNo0muRR17MxxV92AsDgPyswr4Jf/fMbmUdlLyou7ODg4ODgcPDjiLgeG83x0cHBwOHRQfUamjkxcHIJT58CcH5t83X3xabjaWS/gDhBcMhM+fTJ+o0vux1fYTsnOqufHg950jHX+8OvIH2gu/LApvvn4fOpqGikZEcPtzWf8aZ8o2SirWseb0+MXtL/o6M9I8+Uq2blg6mhknGDyvv5h/HG0Wi2lF9Z9w7/WTY3bZtaE+GqsiSgPBjh5xjtNvpNcj4/3jzwdl2Jh0T//uJjPtm1r8vWzO7bnhj5qIT63fruW2bvj5/p9dUwvXImqo8chqutc9mGQSBMf2IndXVw0QL2Wzqxvgqxe2XSuX5dugrFHqkUTRAJRlj4Z2lO4cR9y+2t0PDY1dvxkMELky7Xo68rBqyErg1AbBk2g9S7Ec0Zf28rFODQ/NXVh+t/9uVIfs247ipK8NJtGlGS2LYGnj4KIRUG1U/8Fw9Se1y3F8p3LOfujs5X6WHjpQptGk3x2v/oa2+6+G6xsjni99PhyCp7C1KxhuWj6Jqa9vEKpj2ueOMqm0SSfqS88w9wP37V0bFpWNhc/8E+yClpvuGfKh3pG12+J6/QBRF54D6laay2R0wfwv9uVTGx8/+dxnT6A3d//Ez1iPfl2y7qP4zp9AJHQbhbMuMWyDYA3p5+fsM3LU05WsnHD7LPiOn0ASwPz2BVovPC6GarDwYROH8CEqdZLbACcOfO9uO+kPBzkuu+nKNmYs3NXXKcP4M2Nm1ldZV08SNf1hE4fwFlT1Wos3jSlaacP4OPVUeaWqqm7lJdF4zp9AOvWSLZuVbOz/NmmnT6A8sU6FStTQ9Uz/NkqonO3IHfVIkuroSZsJPlHJfqSHUSmrGnpITocAKpOH8CYB9Sl4VuMpydad/oA3r8aQuZEtVobqk4fwOEvJy4d1RqpW7yYbXfdZc3pAwiFWH2S2vymJVF1+gBevmuWDSNJPmWlmy07fQB1VZW8+Du11J/mJuUdP32RuRNUbrdeyF0/UClfiwR3mVMRq1r9qWUbq340Vzdv19ZvLNsIR2oxI+mkKyiHAmwLmFMofX6V9dzLKdvNlQEJojb5D8rECxMLK9UU0t7dtNlUu5fWrbNs44XV5sa4O6wWYr7DRNWIqRvUrtuFP5g7P5ctUTuPdRMil7t+tKnqfTOjr4p/n9WXpabKn8MhSLgOIjaoFK+bod5HilIVrmrpIVii5ms1/QEAmQKFvBujLo4i84FQtlVhwaQFmW1DKYbainL1gTQjKe/4iRJzIZwi13qSsuZOUkSsx5yKVFqJdYXS/DajTLXzplkPjXW7khPW4xHmwt+OLD7eso0huZ0sH3sgmAl+y/WohRQONqnWOarAenjKpBJzNlRvPF4THXTPU7PSoaO5UNSSEsV3Y+LLz2iXGrdqURhHpcbE6w4OrQa3H1XlaQCK+6v3kaIIOz6/FsDbvbt6JwqpDC1JWpZ6igSAlqKJZN0Psz6/rsflad2CTqkxm4iDa0gfyEngMA0fgPAr5sgUd0ncpo9aWEOn055P2Mad2wNvdmLVxKYYMOqPptqNOibxWJpCCMGgromljI8ceKdlGwD3H2ZujCOKx1u20TmjgHa+xM7Mf4deZtkGwB/6JnbInxh+tJKNszt1JDPBw6jI5+W4dm0t2+iQ6TN1U3lqdHw11kT88cj4N9bidDi1p9qTp2t3D74Etw2vF3r1UbvJdzg+/nfiSoeiEanxFPUc3wORF1ug2PdEyPDgPtlc2RKH1sFdp/ZR7uOKsV3UB9ISCKFeiqHDaMjtYM94ksykDtZLOtXz8okv2zCS5JM1aRL+w+Krnyei5P77bBpN8sltq754/8u/WZ93tSS9Rh1BdpF5BdfGOO7qG+0ZTDNx0Kh6RssqiCxaATvKoaYa3G7o0Bbv6KEIjz2TplBtFfK9v0HpevD6IRSGjDRIz8Hzs7vQFGTwG7JrwfOUrYiVbZASoiF8hf1oc8RNeDPUTsh6tm2awaJZtwNGmJrb3wGvJ4NOvc6nfTd75Ld1PcKX8+5h3bZpSCJkeDsSFTV0LBzN+MG/t03k4X/L/87Hpa/RMFHKi4//G/IveuQOsMXG9kAlN85/hfXBXXulYw3NaM+/RthTr0dKyZMrFvBj+XZK62oo8Prpl1dIn+xCTmzfzRYbAGsrq3hs2Qq2BgJUh0J4XYLRRcWc3aUTnRVrF9WzbHcVN327iYbZgj7gxHYZ/GaQfbuo7y2vY0slaAKiEvoUCvoWeSjJtG+1tbwszMIfI9TUQCAIOTngdsHAgW5y8+1Z2ZNSsmNuiEhAR7jBk6mh10FWNxdpBanh9NUjpYSKIGR5oTaMHggjdNDamDu3HFXPAyMZqp6THviC1WWJQ8DSgPoAryHt0nn72vG2PRdbjHAAFr4BFVugfANktYd10yCvKww4AwKVRpH22gojR9+XDUKHSXdDZmqKe9Sj6zqXfXoZZbVlbK7ZjBs32e5sCjMKKQ+WUxutJdOdyfCS4awqX8WWyi0Eo0GO6XoMdx95d0sPX5nwrl1UvPseUanjKS5GExq+vn0ILl+OrKnB368/gdWr0CMRQhs2IiNhvIWF5F96acqf97VVIV6/bzY15REQxg6eL02gCQjUSfQwyAYZLu40Ix22x8hCjrtcrRxEa2DXlk2s/2E+4boAFTtLadutN50HD6VixzZ2rFtDNBLF6/cRrK0jK78AX2YGkWCIniPHoDXzbq+j6olxc4pM/gbWNMj5EgK27SJUUYVn0uHKdfwA5DM374n5D8XyemoCUFNG+KuX8E1SL/xYvXkuZfP3V6EMbp7Grnl5lBypJiADUFO5hUWz9i6sGglsIhKAZXPvRiLo0O0EZTtL17/P2m2f7bEbMkRlVm5+n4rq9Zw29illG5+se4WPS1/Z7+8hgty54Bc8M2YKmT41ZyYQDXP27H8RbkSBY37NZt7dOJ/TOw5VsgHw4NI5vF+6R3hne12QpXUVsGU1Syp38tu+6iEINeEwv/9hIZsCDXJXIpIvtm1nWGGBLY5fVNe54dtN7BvhHwTe2VKDz13K1f2s71rXo0uJ1+Vi/o4o1bHLccYWSZYnxAX93UzorO6URSI6s2dF2Lljz9+qKyE9HXbugpw8acsCRs0mnap1OnVbQYYxJo4Sts/WaXukpHBI6w4daYgQAnKN+63udRH9fBWyMohrXGfc3Vuv0plD4zwxdaUppw/Y65pfsKWWc56YyVtXH9k8A0sG0Qi8fSWsmgLRIOhhfgr/3DQHlrwLUt9flC2jDfQ/G3pMTPaIbeXRuY8yb8e8n34PEaI2UsvWij2CabvDu9mwZsNex7295m165Pbg4oHqc6KWRPP5CW3eROWnnyHLyoyF+HqHTteN/6en40pPRw+HkbW1uLKz8XXvQda4FD7vgVnvrqBm9548eT0KdcGmN4rqNZBWfbuTIUeX0yaF67VuXLqYj/7xAHXVVehhY3KxcMrnePx+MguK6DXycAZMPIbvP3yXhZM/RpeQkZtLu569adezN1mFrbt4/UGx4xf867MQjSN+oAm8116EUHD+go9ckrhR2+74LjQXStkYVRu/Zdvk6+O20bK70e0s6+ETkUgd096ZkLBd1wHX0a3vRZbtTPvhXlZsei9uG5eWxuUnTLVs443VT/PWxsSFMl8cNxO3QsD5mKmJi9lf1Xkcl3Yda9nGxbM+Zk1t/GTwLunZvDTGelHYmkiE47+aHrfN+Z06cE1vtXC8cZ8uTdhmSK6PR0er7WL+YWodq+N8ZEPbCG4Zbf2aj0Ylr7wYX9yhTVuNY45TCyPf/l2YbTPiC9Fk99LofFJqlHSoRwYiBB/5BvQ9zxjXhC54xsYP83V2/A6M5tzxu+HVeby3oFSpjyyfxsK71RcSW4S/lEDYhJJUUxx3P4z5tX3jSSLXfnEt07ZMU+rjoj4Xcduo22waUXKJlJWx6uhjkDXWVFmLbr6Zwit+afOoksPLd8+mrFThvAcu+MNI8tvbE0GUTJZ98zUf/cO6SrsQgovu/wfFXeyL0mrEhtIzMrX3ooHo2s3xnT4AXRKZtcCyjfCGxBNZALautmwDYNuUmxO20SvXEA2UWbbxzUfnmmq3dtE/LdsAEjp9AFFdTfXJjNMH8OgS6874E6unmmu3Pr5DlYhETh/AutpKJRv/WZVYSv+1DZuIKJQ+mVZqTslsQbn1kiQAa8v1uE4fwPxtkso4K5SJWLUysVLrtq06FRVqips7v0usPlq5IjVUPRsSmbl+L6cPIDpzQxOtHVojqk4fQFUw9c5dAFZOVnP6AKakbrijqtMH8OKyF20YSctQ8d57lp0+gB3/VJtDtRTRqK7s9AG8+VDzhp83F188pfa9SSn55vXWfd6nvONH2KSUutl2jR5rg6SzGUxI+hvNrMvU69Ieqd5Uoi5iXVK6WvXBbzMqO/R1iRZIMIpwqEzTakzYsIOwbu5zMNmsUSLxCgU2IKpWycNyqajWjgw3ci4crG/W4eDDjnu/VLw5OLQYMqRYO1W1dnRLYdOw9Whq3uulrn7NhkOte56d8o6fq1cXc+3GWM/B8nQ3eWymWv5K/qjfJm7kzcWdbj1+eOTRz5lq16bzaZZtALQvMFM2Qu30O6LQnMrlzQMetGzjN73MlYI4qXigZRsAeZ7EEsp5Hp9SPtkVPROHHkwsLsKrkJR+Yoc8U+06pqulF/fM0yhKIDzWPRdy/dY/r169E48xJ1eQn692Huf1T5wInt4u9WTRPUfsL+KjDbauGOuQfIZ3zlXuIzVF7YE+J4NQlEEYeZU9Y2kBeub0VO5jXMk4G0bSMuSceopSSYbc886zcTTJw+XR8Gep55SfdI3anKilGHOu9RSnn/o483wbRtJ8pLzjB+C+/mLIaqI+VJsCPL88Gy1bLdZY+9Xj8RvktcN35d+UbOT3O4Ps/k0rRLqyOtH9gg+VbKRnltBjyO/jtilodxQDRsZvk4gTRz9K5+KmE9s9rkyuOGmWko3rBvyF7mnxVTvvHvQMfrf1PC+XpvHyYfHj9MfkduPOfqdYtgHw4biz6OBrusZZj/QcPhx3ppKNPK+X50eNwNeI8yiA8zt15K5B6iqob02IXwOpZ5aXl8apTSqEEDxwlJ+xHfafWGoCjuki+OORaoJOHo/gjLN9jZZ00DTo01fjBBvy7tpN8FJylBt3E6VGs3sLup+nLk6VbESWD89VIxBtMiDLh/uornhPcMo5pBJv/voIxnTLtXx8ukew+n7recktiqbBLSuhoBcHPFXSvHD0PXDcn5plaMng7dPfpm9+X8vHjyoexePHJpg3tWI8bdvSY/IX+IcfZqjEN4UQ4PHscRK9XgquvYaSP6iVq2pJLn9gLNlF1p9to0/vQsc+qaloO+LkMxh/0S9weRtfjPemZ9BjxGjO/eP9FHfbM4/R3G4KO3Xh/HsepEM/e9Tkm4uDQtylnmBdHSJ28WmahpQSj82FFIOVlcYFHo0aD4ZoFFdGBm4bi7zruk44HCYajSKEQNM0IpEIGRkZttkA2L17N36/n5pYHLvb7SYnJ8dWGeLq6mqCwSBpaWlEIhGi0Sg+n4/0dPsKOUejUXbt2oXb7SYYDCKEQAhBmzb2lL6op6KignA4jNfr/ek7ys/Px2WjdG8oFMLtdhOOhSa73W5CoRBpaep1dRpSU1Pz0zVS/57stlFZaeQkCiGQUuJyufB4PHibuKFaQUpJJBL56ZyVUqJpmu1S2rW1dbhcRp/RqI7b7bL1fYBx3Rv9R9E07afd3VSUBZdSIuXeiqdmd6sdcZcDIxnlHKLRKOXl5bhcLurq6tB1nbS0NKSUuN3un77vmpoa/H4/uq6TlZVl+z2lxQiHjQm+lMazPxIBv9/4W726Y33Mt5SGI5CC121jBINBKioqcLvd+P1+amtrcblcP92jIpHIT+eFy+XC5XKRnZ1t65yoJamrq8Pj8eB2u4k2iOsXQhCNRnG5XD893yKRCEIIW+cELUkgEPjp/eu6js/n++k5JYQgHA7/9Hz3eDwEg0FychLXPU4VGn7f9XOLhs+2+mug/m+QnOe1U84BCP7jeQgYMbX1bmz91xUExNhheI9QK8YZfOVPULqy0deisR/Xef+Hu30PyzYideWse/UE9ryL/fEUDaPzyf+ybANgyhuHs+cTapyJZ81EU1DCnLrgL6zc/H7cNof1vIphvawXPg9FA1zydZwioUsBBK9OmG3ZBsAx0/5KdYLcyClH3Ey6x/oK2YztG7lt4Yy4bS7p1Jdf9Rxi2QbAxC++JF6G6Gnt2/HbfmpFm++Yu56vd8TPj3nu8C50y7Y+KawISm74PECoiXwEATwyyUsbxXp+L79Q1yBVo6GxKFBHm7aCY45T240LlkdZ+WLIKOPQCJoXel7kw5vT+ieSsiZE8MUfoLHvP82N5/S+uLrnJ39gDpbYXhlg5L1TlPp44PT+nDe6iz0DSjZf3QvTLCr8aV64Zg4UNJ+6X3Py4aoP+d3M3yn1MfuC2WR47V2wThbrrruOui8mWz6+3cMPk3OSPTWRk813n6zm2/fWW+9AwDX/Psq+ASWZN//yB9b/ON/SsfntO3LJg//E1YoXPlr/TCIBoWnf/uT0NYWcMU8pUVdKvUmnryHR19TCOjZ9fCXxnD6A8I55ROp2W7ex+l0SOX0AMz483bINIKHTBzB35RNKNm745iwTrSQLdlgPKZ1ftj6h0wdw3MyHLdsAEjp9AP/bsFRJ3OWhxUvjOn0A723eoqTqWRuJJnT6AH7+zTrLNgD+Pqdppw+Mq+jO6WoJ1nNmBRLm52/bKtmyxbrYEsDat8JNOn0AegjWvtO6k8XrCX2+qnGnD6AuQvitJciQI3iRKox94EvlPm57d7ENI2kBKjZZd/rAuHBfON224SQbVacP4IhXjrBhJMknUlWt5PQBbLnlFmSKCrwoOX0AEqa9ssyewSSZVXPnWHb6AHZv3sjnTz5q44jsJ+UdP7nYXAkFuduczHxjRHdsNDsayzYAIlWbTbWrXj/Vso31y/5nql04uCNxoyaI6opqWCYpi+401e6VtdbzDJ5Z+7WpdmpTf/NUhq07AF9tN/edbqi1rma3tjo5Dsqa8sRtahRPw/XrzV3P69aoOTLhysR2whWtPyQfQK4vj98gFEXual1KuQ5NE0pRZT5b2DwvcZtEVGxS7yOFiZpYZG6N1H07R70TXSeyw9wc5WBk5ffbW3oIllgyTX2xq3TlchtG0nykvOMnhvQ2164g17INV9H+6nSNo/ZxenLiFzauJ7PLJMs2uva7wlQ7b1o7yzZcmr15lU1R6DanEHh5z1st27i6W9MCNQ3xK2rXmdVszPFaDyc9vm2xqXZdFHJJu2Ump8h4LxPioVmKKXjde5j7Vrr3UPvuvbmJ7XjzUkPVU3RN8MX4XIhC+/J7HZoXnzs1zrtmocMI9T5yu6j3kcJ4RHLmAnaTMWaMeieahrvYugJ7qtPv8NRUcB509HHKfbR2cZeUd/y8hw+DzPi5QtqkMQiP9XhbIQR0HpKwnesitVDPDic+CQlulL4O43H7rSfPtut6AojEk/OxJ71t2QZA/y4/S9hmTL9blGz8/fC3ErbR8NA7b5BlG/1z21PgSjxR/XTczZZtADw2NLGDeXVXNXnk6/v2wafFn8hd1LkTmkLJiDS3xkntEivovj5WLe/lhlF+4lWE0IB7J6jl3h023E8ibagOHQVt2qrF8nc5y4sW55J0pUGXM+0VkmkuvMf2gKa+/ywv3nMHIDwHh/DBocDs31lfZKznqYusl1JqUbJL4GiFZ7o7E37+gX3jSTL/nKhegHz2hWr59S2Flp5O9llmUkmapsPjjyuVX2pJxp2vqLrtgsPPSk0F5y6DhtFjxAE4/vt8x2269eSYX15j86js5aBS9XRwcHBwSG0cVc8Dw3k+Ojg4OBw6OKqeQGT1eqLvToFI4/Hk4pIz8Jao1RSJRkJEnrgeQk3kpxR0wHfpvUo2ANa8eS561YYmX29/6sukKaqErVv+Jqt/fKjJ1zv2vZxeA36lZEPXozz7yeFxWmj88sRvlFfELpk6nhCBJl//TZ/7GNVWTV2qLFTD6d/8kxCNJ2qfVjyI2/udrGQD4D+rF/K/dYsJN5IrOiy3mL8NnYBbU9steX/TJh5auqLJ1+8dNIAj25gLCW2KUFTn6C+ajnH3ApOPt14fqp4PV4Z4ZUm00czaU3sIzu+vXvtu27YwX02OEGkkiTMjA8ZN8FJQqL6DtWlKgLJFkn1PMeGB9pPc5PW1J2RKL48S/b4WGZUIj0DWSly9fbh62hOiq9eECL+/DLmlCrwuRNtMhN+DyPDgGlKCln+QyPsfQoy59zNKK61lMad5BEv/lJrKhgAEKuGpCbC7oZaAxn4XamNkdoDrvwNv6oY2D3p+ENKidsENg2/gl0Pi18BtzUSrq9l0zbXUzptnlPNoDK8X4XYjQ0FD4kHT8HbtSvu/PYK/e/x6tq2d9/4+j03Lyi0dO2BiO8afp6YO3pLUVVUy+Zl/sXret+iRKELT0CN7zgHhciOj+98TPf40jrvqBnqPGZvM4R4wKb/jF6msIvrvVxP24b3xUoTPerhU8G8/B5ngZp9bgu9y6ypga944G706cTJ4j8ush09UV61nzqfnJmw36tjXyTSZc9gYT380ylS7K06ynkR9+bSjqZVVCdv994gvSfNYy1uL6FHGTX8g4aPv9p7Hc1r7YZZsAPx58Sw+2boubpv2aRm8fviplm1sqqnlgm8Snzsfjh9LjkKNunGfLk3YJg34TMH5+3xNiOcWxhcOuLi/xgk9rDs01dU6774VTNju9DN9ZGZZj5pf/0GQylXx7y2dz/CQ3UVtnU5WRwn8cyfU7n82e87MwT1UzSmTUhJ8eCYEmvhe/G58Vw5HZMf/TpwdvwOjOXf8TvzHNJaUViv14XMJlv8lBZ0/KeG+jhBK/IxpEpcf/rDNvjElkSHPD1EWZ3noyIc4vtvxNo0ouawYPYZoebm1g4Wgx7SpeIrVFlFbitfv/5Yd69Su+xOu6U+3gfbWUk4G0UiEp6+5jJryMst9nHDtzfQ70pw+hBVUn5Epn+OnfzjVVLvw7AXWbQRqEzt9AOWllm0Appw+gN1L3rRsY8H035hq9/2Xv7BsQ9eTo3FpxukDuO9Hc++5Mb4vW2dqvfOvKz+3bANg8ramd3nr2VxXQ0i3/iC+df4CU+3u/GGhZRvlIXPffZ1lCwZvLU/8Oby+TE1Ke95ccwqlixaqne+VaxKPc+s09WsquijQqNMHEPlWXWlTX1/etNMHEIgQXZyaSm+HKqpOH0AwVZVBt8xXc/oAogEoW2fLcJKNHYqcf5nzFxtGknwCq1dbd/oApKT81cQbEq0VVacP4LMnU7OMy8YlC5WcPoBv33vDptE0Dynv+OEzuaKfoRBu4WpdYgSeDOurSG5Plql2LpPtGkOI1nVa5Xmth/mmu8ztfHk0tffsNnm8Zlr/c3+yXOZ2jPI91nf7PAnEY+zCY+LjMtMmHmYDBLw+tfdsJtpZs0Pbxdu0IRHnNdP4TJxf3tZ1L3VwaBK7Co+7D93w5jRXar53LV09PFfLzrZhJKmLO0Xv9R6feoqIx9e6z/vWNUO3gPs0c/lbnqH9LNvQPD7wJ1YqpNdIyzYAMjqZ2xrO6jzOso3DJv7bVLvRx5qr99cYQmgIEl88bk3t4uiZOdhUuxsHWF91HJTbEb+WeEL72KALLdsAuKxL/4RtDi8oMe0gNsY/RpgLRf3DoMRjaYoMtwszSzE90tVuPdccljjn7caRanlxww5L7G1pGgwYqBaCWTQi8QOy/THqOX6uAX5Em0bG6gb3BPVJrqskC4qanjCJwnRcA1Iz9OlQ5dLRHZT76JSnPpFqEYp6Q6FiLnJuZ8hKvXA3gAJfgXIfj05q3YWsm8JbUoKvr/XvXmRkkHfOOTaOKLn0PUK9FMN5d9hQDqUFaN+7LyU9zZWJa4oJl1iPmEsGKZ/jBxAJhYi+8Sls3m7E5TckJwvvleciFHdkAIKfPQuLpzX+4nFX4uuvntC5e+l77J59X6OvaRnt6HauWpkFgHComunvnQA0Hso29tQv8fnUJ4KfzLqJTbtnNvpah4IjOWH0X5VtvLHyWd7a/FSjrwk0/nfkdDwutUmzLiV/WPQ2X+5qXLDkjRG/pkOGicJyCVhasYt/LP+exVW70dlT2y/D5eI3vYZzfDs1UR+A2lCI06bPJNDIdZ/t0nhn3Fi8bnXNp1u+XcOc3Y3nx53fIYOrB5itjdk026oj3DcrzM5YlKJHg7Bu1O/7w1g37bLUnaVwWGfGtCDbtrGXwIvLDV27aQwf4cHtVr+3VG+KsnlKiEgt6GFAB+GGtDbQ6WQfnjR71uhkRKKviAkRpAtkWRRXDx8i257VWSklke+3EF2+Ey3Hh2iXjfC6EG4NrWcBwsRn5eT4HRjNrer57tz13PjGIkvH/nxUB+46w9wCXatl+t/gqz+BjILLB/ndjfDNaDi2XS8AHfQI1CcGCBcccRMcfWfLjdsG7ph+B++vff+AjxMIJp89mWKF6KTWwK4XXqD8tdeJVFVBKIReWWnMMfNy0dwePO1KcPn8hDdvRqSnQyRCxsQJFF9/PZpCnnxrYNX8bXzx7GKsZO5cct8YsvJa965XPKSus3TmNOZ98j6BmhrSMrMo27qFYHUVvsws8tt1YPu6NUg9ij8zy/BBIhE69RvIMb+6jqx89UWTeDiqnoDb60WOG4k+/TuoqoKqWiOkyOeHw4fY4vQBiKHHIJfNMu7tAoiGjOTtfmPx9LGh4CeQ3/c0qtd/QWj3WtCjEAkb+YUuQZvxf7bFhsebSa+ht7Bi/sNAAOPNSCCNTr3Pt8XpAxjd/ybe+Xou0X1UNzX8HDXsbltsnNPzF7y7+Xmi7O9knNfx18pOH4AmBKPzuzB712oCRPbSczunzTBbnD6AXtl5jC/uSCiqo0kYmF/EzB2bmVjckYlt1B0lgHSvl9Pbt+ONTZvRMb51N5Dp0rixb29bnD6Am/qVcOXsdVTs89DI0eDX/TvaYqNNppvfjhTM3x4lHJW4hSSsS8oDgjTVOM8YHo9Gj15uojJCXR0ICbl5xk5fx04uW5w+AF8+5PR2IbUoQrrI66cRLhN4soVtTh+AcAu0Hl70XVHQwNXJi3DZF54rhEDrmQ91YbTBbREZHvSVu5EZXkhSGLCDvZx+WGfu/XAx2+sObJHYA9x8nLp6b4tz2CWwcTZU74D2w6CuHPI6Q6gGCvvA9iWQ2QZ0HcK1kN/ZcA57Hd3SI1fm/8b8Hx+s/eCAlT3zPfkp7/QBFFx8Md4ePQmuXIHweqmeMRNXmh9X27YEV67E37MX+T+7kOCKFZS9+x6RnTtxFRYiWll6kBW6DS5i0FEd2LWpGj2qEw5LairqEAgy8nxomkagNozf7yGr2M+mJWVkFvgYfUqPlHb6AISm0e/IifQeM5bdmzcDOi6PD196OtFIhJ2bNhANBsnv2JnSFUvx+v24vD5KevQkPTu3pYefkINixy/42ItQE0cuQgi8t/xCqXRA8LFfQSi+JIV29GV4BllX8qna+A3bJt8Uv5E7gx4XT7FsA2DKG4kVN0cf9xoZ2V0s23hp8mnUBrfGbVOcM5jTxja+W2eGGVu+4LEViVdUX51gXTkUYMzUxGU63h99HUV+63mRC8u3c9Xc+N/rH/uN5tiSrpZt1IbDHDf167htXMBXR09UulYumrqCDfFEPoC7B7VhYrt8yzaklNwxLcC6iqbbjCyBG0dafwBJKXnlxQB6HO0VtxvO/5naQ27L1BC75jf9eWV01Oh6lteWYsDRRQFCb5dDvTJ1hsB3ST5aO3vKRQRfXYhctbvxF70uvBcPRiuJf504O34HRnPu+L35/Xp++6a13b56uhX5+fJm9ULwLcKbv4RFCkINnQ6Hyz+xbzxJ5DdTfsPkTZOV+rhzxJ2c1+88m0aUXEKlpaw58SRknTUpso7PPkPmEUfYPKrksG7hDj563LrIm9snuOJvE9BSeLFv09JFvPvQnwnWHJjQzdDjT+Goy9TKoSXikFf1DK9YF9/pA5CS0AzrD8ZobWVCpw9An/KcZRsA2ybfnLhRpIZg+XrLNlYvfMZUu++/sn7i6no0odMHsL3iB8s2AFNOH8Cba8y958Z4ds10U+1+Ofe/lm0A3P5DfIcM4N6l3yrZuGLOdwnbRIFnVq2xbCMY1RM6fQB//FFN4nzB9mhcpw/g21KoDVlX9pwzOxTX6QMj/HPBfHPqn42hR/W4Th9AzUadytXqCnsyIgm9X7HH6QOokYQ/rlTuG0CvCjbt9AGEooQ+XWmLLYfkoOr0AazZ0XSd1VbNrtVqTh/Ahm9ge+LyNq0RVacP4M/f2ROl1BKU/u73lp0+gE03WlcTb2k+fsK60wcQCUq+eXuVTaNpGaY8++8DdvoA5n/6AeVb1RT+m5uUd/zkRpMf8JqN1m1sN+loKe+emjs+sN36RblzW+M5d/sSUZCxDkUUJbBtZtYO6w+w6bvMTVR3htXk8CsjiZ2HsJmSInEoDSSuSQfw7e5dlm1srbXuBB0I6yrMfRZbmyhfYIadO8zZ2FZq/XuJmjxtAjvVvnsA6nRoJFxP36nuVALIHTWJG+1SLeTh4JAkdq+1p58NahEnDi1DeJO58lpNIavVSyK0FNKGR8K2dfYsKLYUZaWbLR9bvnWLjSOxn5R3/NwjB5pq5zrWuvCKu4s5Gyjmxglvrql22d2PtWyjz7DbTLXLK7ZejNxv8n0ki5v6Ny6WY4a7+55mqt3RRX0s2wAYmFOUsE1bn5rE9Jkd2plqd2OvXpZtdM4yp+CnmgExpp25XMRuudYtDR5qLvxx6GHWbXiyNISJw3N6qudeiiwXov3+78nV13qR+4ZoXRLnump9rJdWcUg+KT9BUKHTaHv6GZyaoY52oKXwGZR17DFKx/v6qM0JWpKsAnUl3mHHdbZhJC1H9+HWrn+Xx0P7PtaV0ZNB6l6VMbSsTMTYw+I36tYRd4liovExCeRZ3V48V/5dyUS3Cz8h0VeSN/w3CJO15RojJ78PuUXxT2i3t5Bh4x+zbAPg2GGPJGxz7vh3lGyYyd3rmt6H9pnW8+K6ZBYyOkGuY46Wxt39T7dsA+AfwybSLs7CQZbLw39GHq9k49o+vSnyxHdmJhYV0j8vV8nOw4e1T9hm8nFqD8W2mRpXDnHjbiKFQAPuPlItb61jRzddusXPUejRS6O4jZqd7hd696/TJwAN3BnQ8UQP/gKbRGQuzEUb4Id0AZkC1+HpeE60p96U0ATunw2EerEYDcj3Ge/FJdAGFuM5roctthySw5r7T1Lu48ubrJcfalF8mXDlNCxPk9xpcPZ/wZOaQhdfn5c4/SARP1yqls7RkrS59VayTznFXKHVfXC3b0eXV19phlElh5/dPRpfuvUFzYET2tN1YGov8h37q+sZfMwJpGXn4E1LJz0nl4KOnUnLzjHy7YUwVN5iCCHIbVPCeXc9gMffukvYHBTiLg4ODg4OBweOuMuB4TwfHRwcHA4dnHIOQPCl92FTHLGInEx8V12gZEPXo4SfvAHqmohbzsjHe+XflJX3Nnz4K0I7mlgl0zx0OPk5/AXdlWwsm/cIm1e/1uTrmTl9GHXs80o2yqrW8+b0c+O2ufTYKXg9mUp2zp86mni5kQMyR3DncLXdyy+2Leb/lr7X5OtZmp/PxyVQY03A9roazvzm/SbfSfe0bP47+gRciqVJbp+/gJk7mxbgOL1dCTf3V5Ngn7mtgt/Njx/jPv14dZn315eEeX/l3uU16umRC7cf7ifdo3Y91tZKJn8eoLIJIZnxE9107KS24xfYpbPytSB7VSRxgb9A4MkUFAxxk9U5deTBo8t2EJ2/FfxuREkm0VkbIRCBLB+e0/vg6pDT0kN0OAC63P6R0vEr/3w8HnfqnL97sfwLeOXsJl6sL4MUh6PugnGpKfJRF6pj5CsjlfpYeKmaSEhLsuPZ/7DzoYcO/MC0NNrffx/Zxx1n/6CSyFcvLWPJ1weeq+byCI6/cgBdBiZOX2mtLJnxFVOe+TehOiMJ35OeQXGnLuh6lEB1NTXlu4mEQuhRIxlSi5XvyCluyyk33EpRF/Way81Jyod6hhYuj+/0AVRUE5ymlmAd/s+tTTt9ADW7Cb15v5KNHd893rTTB6CH2fT+RUo2qqs2xHX6AKorlrF26YtKdhI5fQDPf64m8X3bnEtI9OBdVP0dNWHrSdbBaDiu0wdQpQe4ccGrlm0AnBHH6QNYXVfJNXPVVNZeWrs2rtMH8O6WUtbXmBDpaAJdyoROH8DET9WU7uZsjvBuE04fwKpyuOdrdTXBzz9t2ukDmPZVhJoaNeGVlS/t4/QBRCGwXVK1RmfdOyHqttkg7pIEoqt3E35zCfrq3eiLtxOdvAZqwhCVUB4g/L8fkLXhxB05tAp636Hm9AH0/cOnNoykBYiE4jh9YEqM7cu7jLp/KYiq0wdw8psn2zCS5FO3cKE1pw+gro7NN9xIzbdqKtwtyYLJGyw5fQDRsOSjxxcSqrNQ+b0VsG7BXD7558M/OX0A4doaNi9bTOmKZZRt2USothY9EjEEHaVEj0TQIxHKtmzipTt/S7BWTeyvuUl5x09+OdtcwzmKK0+VOxK32ag2ma1c/raJVpJgmXW5/RXz/mqq3bolT1u2EYkmR757fd1yU+3u/9H6iutHW82dN3PKrX8nZllcaV1tE+DldeaUbR9abP08nrzFnJKXqmjY+ysTP1Q2VEEgYj2UvaJCp9qEQO3GDdbfTe3WaOIPQ0LFKnuUN5sbfWmC+6Qu0eOVfHBoVQRtOO0ULsGWZYHa4udPfPFHe/pJQdbXWC891ZLsfMp6feF6qj5N0QUPYOFUNUVTgKWzWndJg6ZYPnuG0vHRcIgNCxfYM5hmIuUdP3JNChNkKCrXCRMfldu66AqAK63AVDt3uvWk2ZwCcwqlvvQ2lm249lOqaFlGFUy0fGzvTHOfgzcJl1KaSy2ksI3f3DUwOC+xOmNT9Mq2RyEyESWZiUM4PRp4FSLM/H5zYaJZWda/e0+OORve7NQohCtyEie1i9zknCMODkqUDLWnny7WFcUdWgafgrJ1PZ72iUXOWit2qHoWtldL42kpsgsVhSCB7CL1PpqTlHf8PBeaCyVwXaEmqSyOviyxjTNMFGCPQ7vj/5mwjb/NUFw+6yp83QdcYardiKOtFyQXQiM/M/GNs3u7Ey3bAPjL0OdMtTu5y4WWbfTPaY/PRPGBp4b93LINgH5Z+Qnb3NFvlJKNRw4zN5G5oqf1HNIuWX7MTOsv65Jr2QbAZYM8eBPcvS4Z6EFTyLn1+QSHjYifBu33Q7v2Co5fmkZWz/hjzOykkds3NXKkXCPaI9pl7fmDb+9xi265aJ1ykzsoB8v87oSeyn1cOqaTDSNpAdoPhSxzJXCaRHhg0Dn2jCfJ9MpRd35eOSE1lS0Lr74afNYXqNwdO5J7XuqW8TjmcrVyBHlt02nf2/oCcksy9PhTyFJw/nofPo423Vq3evVBo+oZfP9LWLp6/xfaFuK79AxbxhEN1hF5/1HYthZCAUAaO4ElPfGeextCs2dyVjrtHmo3zwZ/LrJyM/hz8OV0omjk9fgL1G/GACsWPM7GlS8BHiAWmqn5KWgziiFjH7TFxo6KZbw749JGXtG44KgPyEyzR+7351MnEmD/mOq+6cP448h/22Lj0y0/cveKD/f7e7e0Al4a9StbbKys3M0tC6YR0aPkeHxsD9QgNBcTCjtwU98R+N32aDH9fclSPt26jbqo/lOOnBs4r2N7rurT2xYbn23YyV+W7B/2pwGfHd0Tn03vZfr6MPO2RigLQI7XuBw7ZWkc28NDViLP0CR1dZIfFgTZWiqJRsHtNlSchw7T6NDRnt2rwK4oW2eHkCHw5WtkdXHhzdaQUfAXpt76nL61GvxutFw/0Y0V6Jsq0brl4WqTeBXYUfU8MJpb1TMcidL/D58SOsCpQroLZv7+aPJUo21ampVfwkc3GWUZhBtyO0CvYyEahV0rwJMBqydDNALlG8BfBOEyGHcLHH5tS49eiTW71nDah+Zq2TZEQ0vpUg717H7jTcpffx2Rl0e0tBRfv76E1q1Hr60lbehQ9MpK9JpqAqvXQF0daWNGU3jRRWQMs14HubUgpWTB5PUsm70VXQdPukbt7hAZuV5kROLN8BAORek8sICNi3YhhCAjz0f/se3p0DvxQnZrZ9PSRSyfPYOM3DzadOtJmy7dKd9WSkZeHltXrcDl8bBzwzq8aenkd+jEjrVr6D58FPntmn+n11H1BCLhMKxc1/iLO3YRjURw2THRrCmD7HzYsR786eD2Q6QOMnOR0agtjl80WEVN6XcQ3G38ANRtJ1i3i+o1k21z/PLbDKd0/ftEI7UILQc9UgF6gGgkgK5H0DT1z+vr+U3lE+rMXvg4R49Uz33YUVvaqNMHIGzc0J5f0Xh+3Lq6Xayp2km3LHUntmd2Pv88bBIPLJ3Dxtpq+ucVUxMJ8X3FNhZWbGdEgeLqM1AVDDJj5y5qonuLhUSApVVV6LqOpqgcCvDplsYVUSRQHtJpY8PlGIhIMrwaug5ry433ALBkp063vChDS+z5/tesCrBmlfF/vx8yM2H04V4yMuzbhROaIK+Xl/R2grptOuXLI4QqJO50jXbjPXgyU8f5iyzcitxZi2tEe6SUUBuGQBi01AhXddibXTVBXC4NIgcmMFQbheWlFYzu0brDnhKSVQydR0Ppj1DUC0LVMPV+4/kfrIZIALyZkN0OSgaDywNdLoLeJ7T0yJV5bVl8Ibim0NHZVLmJDtkdbB5RctH8PvSKCqLbt4MQ1H4zCy0tjWh5OVWffw51dRAOI4qL8HXrRvD7uezYvh3PI4/gLU7t814IQaAmSigQxeUSVJSGAMnu0hqy89MI1UZAgy3LyqirClFdHiIvqJNTmJp1K/eloEMnOvUbRGZBAdW7d7F9/RpCdbWEgwE0lwt/ZiahugBoGgsnf0qXIcPIbdu2pYdtipTf8YtU1xB9/OWEfbivuwhXuvUTMvzth+gzXo/bxnPF39FMhOw1Rd3OZWz+4Odx2whvJt1/pqbu+OOs37Nj05S4bcadPhmPJytum3g8/ZGZsEQPV5xkPZF2Zunn/HP5HxK2M1PoPR7jpz5AKIECx/Vdj+KCzqOV7Ly7aSUPLW965X5ScUfuGWg9X2RFRQW/+HZuwnZfTByntLs4zoRi558GlzC+JNeyja3VOnfPCFKxrxpmAwYVCW4/XC1X4e0366htQuR07DgPXbqqe7A75obZOj2+WE2nU93kdFfL8UwGwX9/h9zVYCEmzw9le8SeXJO64RnTMW4fzo7fgdGcO35TFm/lFy8kvmfE49zD2vHgOTblyyWbz/8A3zxq/fgTHoJRV9o3niQy6oVR1Opq6oR/PuLPnNbjwHcMWwNrzjyT4BLrQmft//U42UcdZeOIksvTN04lFLCmJn3sFf3peZh1nYiWZvOyJbx13x8JB+oO6LjM/AIu/9uTzV7AXfUZmTrLyE0QfXn/8LvGiDz7hmUbMhxC/yax4mbkM+tKmAClX96ReCyhaup2mlOzbPR4qSd0+gBWLUicb9gUkYhZVU81WXczTh/AsnLrISerq3ckdPoAHl37pWUb9fxjxby4r0/Zbk6VsylunGfuc3hqlXWF0lnbTchgAnf9oKb49cGqSFynD+DHHZKqA41Pa0BtrWzS6QP4do56WQI9Itk+K7FC6ebJrV8aO7pq995OH+zl9AFEp61DRlOjNIUD/OolNacP4PW51mThW5zKUvjG+nMQgCn3GGUhUhBVpw/gzpl32jCS5BNcs0bJ6QPYekdqvneADUt2WXb6AKa+sMzG0SSfb9546YCdPoDq3btYOnNaM4zIXlLe8SOQYPb3UzuFm280DHriiZesNSdl3xR6yNykOVqToG5hHKQ0p88dqNtu2UZET045B7NsrbMuTbwjEKeIm81EZPNOiANRc9/9drPXVCNsrDF3rKpKfLVJh06lnEM4gY2oDb6YHgHdhP9opk1LIytNXPcRHfTWH2XiYHCA0Z0HF4EKTNXqi0eoGqLW76cOLUNkx07lPvS6A3ccWgvVu9XO2UiK3zjqzNRxaoKAwrHJIuUdP+1Yk6Fvp1rfchf+DETnQQnbuQ6PV+w1MYVDf2GqXUanIy3b0DQPHl/icNTuA60Llvi9uZaPPRCG5JoLrZxQcpJlG6MLzakz9c1QD2s4ojB+UnCBRy184OKunU21u7JHN8s2zu1qLtfx6DbWw4gBJnRykyhjLMMDRenWb3E5ufGP7dpN/fbp9guyeyTuJ69/679Va4Pbgmufb2WfvD7RPQ/hSQ2FUgc4a6h6XnFBeopKCRT3gXaKIh39zwCf2r0ulTms+LCWHoIlMkaNRCioegLknHmmTaNJPr3HqOWq9RyeumGeAAMmHGPpOKFp9B7T+su3pHyOH0DwixkwL862fPdO+M4+TmkMMhwiPPN15IIpoO+zXyFcuI66GPdg9XjurXP+TvWSVxt/UbjpdMYreHPi58gkIhoNMfvTCwnUNh462Hfkn2nX2dqJX09N3U5e/jK+w/WLE75BUxTEuXLa8VTKsiZfv3fY83TL7qNkY0PNTs77rumCriXeLN4+/DolGwBRqfPnxbP4YtuG/daZO6Rl8uqYkxEK5QkA7lqwkCk7mi6y/ZeB/RnXVu2mvaSshqvmbGjy9QFZHv51hLrc8cLtUT5fE2Letv3X5Qv98MBRftI8ap9XIKDzzptB9t0s7dXbxcjR9tSr1COSXQsiBHZK0ooFVet0ajbryCgIF+QPdNFuQuuqjdkU+o4awh+vgOow2pC2uPoVEf5kJbKsDlePfNyTuiPc8Z1YJ8fvwGhuVc8zHpvB/E3WIh+yvC4W3nO8zSNKInXlMOVPMP9FY+dOaCB1mt4JFEabjEIYdRWMvhoUF+xaCl3XGfzCYMvH53vzmXZB6w97a4rw1q2sv/gSwhsPMMVCCHLOPYd2d9/dPANLErs2V/H2Q/MIBRLE5wj2uhx6jWrDMZeplYNoDSz7Zjpr532HlBJd1wkHDFEXXY/i9adRW1lO+dZSgnV16JEw2YXFnHT9LRR17trsY1N9Rjab4yeE6Aj8D2iDcVo8JaX8hxAiH3gN6AKsA86VMs7MneZ/sDk4ODg4tA4OBcfPeT46ODg4OFihNZdziAA3SynnCSGygLlCiC+AnwNTpJT3CyFuB24HblMxFHwggaiKEPhu/aWKCaKbVxJ54979d/sMA4jBR+Gd1FjNugNj8+Rbqds4vcnXs/tdSPGo65VszPniMqrLlzT5utffhiNPeV/JxpJ1bzFzcfx6gCN738jgHhdYtqHrOhdOHxO3TSa5PDPhM8s2AJ5YPZXnN37T5OvpLi9Tjvytko311RVcNOdjmoqMz9BcPD/6RErSEtdBi8eEL76Mm1/XKyODZw9XKxR/z7x1TN4eP7/hs6N7kqZYYuUvM+pYvKvx18Z3FPxqmPpK+8oVEb6dHaax9TFNgwmTvLRrpx66uG1OmB3fRpD75A16sqHXpX40d2qVQoiu2El48hqoCIAOuASiRz7eE3sh0lu/OmkSSNrzUZVuv/vIclqmS8Ciu48jzZui4Z6rpsDku2HncqNsw4Hgy4YbF0JabrMMrbmZvXk2V0y+QqmPBRcvwGVTfeNkUz1zJht/YW3e6O3di27vvIOwoTRSS1BbFeTVe76lrspccrnX7yK3TTq1lSH8mR5Gn9adzgMKmnmUzUdtRTlTnv036xf9QDhQhx6NIoTGgEnHcuwVqV2bE5oxx09KWSqlnBf7fxWwFGgPnAY8H2v2PHC6ip3g/94zMxjCM+MrJsY/XMZx+gAk8ocpRFZ+Z9kGQLh2V1ynD6ByyctEA9ZFZLZtmhrX6QMIBbaxaI45xcymSOT0AXy7/O9KNq6YkTh8t5pyVpcvtmxjV6AqrtMHUBsNccP8VyzbALj020+bdPoAavQoV3+vVsbj1rnzE4qqrKip4fudTXhTJqgKRxI6fQDHTV5p2QbAxyvDTTp9ANM2StaUqamvbN8WZc6sxp0+AF2HqVNCRBQEZACqN0bZ/s3+Th9AuBLWv5da4hCyIkD4jcWwuw6iEqSEiI5cttMIA3VI2vNRlZMfna6kxROVcNTDU20bT1Kp2QmvXghbfzhwpw8gWAn/Odb+cSUJVacPYORLI20YSfKRum7Z6QMILV9B6e8Tq7S3Vt77+wLTTh9AKBBl+/oqqsuC7NxYzSdPLKQmkex2K+azJx9lxZyZBGuq0WN5HlLqLJz8KUu+/qqFR6dOUpYjhBBdgKHAHKCNlLJey30rRqiLdUrNqU/q3/1o3Ub17jhO3x7k0vgOQiIql79jql3Finct21i39D+m2u3cYv29RJMkQVijm3OA/738z5ZtfLRtoal28yrWW7YBEDah6Lk9VEfYxHnYFLN3x40Y+4n/rF1n2cZHG8stH3sgTN+U+HP4Yq2admhpaeLvRNdh9y41BbOqdfHHWVva+vOwG6JvrGgyBUpfa+4cPJRo1uejIou3qCvUlabqBHDDbGsOX0N2qC1wpTohPTVLWYQ3NJ2jbpaa2bNtGEnLUFaqVsojGtEpXZU8RXS72bCo6dJXK2Zbrz3dWmh2x08IkQm8Bdwopdxrpi6NBMNGpwhCiCuFEN8LIb7fEUeMgsx0cwPp3snkiBshIxcSagiC6NjXug0go/MkU+0yO1sXkWnb+QRzY8mxLr7h0pITyuXCnJ1TOlxs2caR+eY+h05piZVS42EmkC/T5cajEDbTOS3NVLsTSqwreo1vmxwFuwGFiW9dw0vUQozy883dHnNy1G6j6W3jj9Obm1phnqJt0+HIWpzXDkWa/fmoSHGW+r0805eaoX60HWgItaiQWWTPWFIUYerJ1vpwt1NXs/X16mnDSFqGjBxFMTEBhR1T915f3KV7k6916DsgiSNpHprV8RNCeDAeai9JKesroG8TQpTEXi8BGt2yk1I+JaUcLqUcXlTU9M3Td83PTI3Fe/LEAxn6XgjNhXb0ZfEbteuFe6haWIc/vytagrIAvuIheHM6WLbRudcFuDzZcdsI4WXYeLXCtZ2KEn/eBZmJS2TE4/Ex5vIQx7c/0bKNrlnFjM6Lr9IkgP8Mv9yyDYA/DTg8YZu/DpmgZON/RyQuf5HhcnFKh/hlJeJRku6jrYm54rOjFBZigAv6eyiIk8LXJRsOK1HLK+rQUaN3n/iT1hGjPPj8apOb7B4aOb0btyPc0OXM1FD0rEcrzMB9bHfYV72zKB33ib1aZlCtkGQ8H1WZfqu6UvUn11svP9Si5HWGkx4GX46144UGl35o75iSyOX91J5pADPPn2nDSJKP5vVSdOstlo8XWVm0f+ghG0eUXE66djDavqV5EpCW5QEBvnQ3487rRW6xyU2ZVsixV15HUacu+/29fe9+DDvh1OQPyGaaU9VTYOQo7JZS3tjg7w8Buxokr+dLKW+N15cZ1bLg6o3w1SzwiFheCUb12XNPwJdn8ca9D1LqRHdsJIqAUB2u3DYQCqBl5KD5zO2mmCESDrBr0WsItx/N5UZKgduXQXbn8bhskoYOBnazc9tcMjI6UVe1Hl9GMUgdX3oJGVklttiQUjL1+wfZtP07NLePSKSWEEHy/F04e9K/bLEB8O2W6by64nECBMkggxx/LmnuDC7rfwv5afZMigKRCN+XrSGiR6kOBnC7XETQ6ZddQrcs+6KxFpZtR+qS2miYdLeHYFSnbUYmHdPt20lbWV7O2xs24NMFS6oqSXe5GFRQwNldOpPts8fJCEaj/HXBRlbvrqMoDaoiUB2BU7rkck4Pe84vgMpAlMU7QkQiUJKlEZKCrrku0mysFReNSqqrImguY/26vCJCbo6H9AwNTbNvRTsa1tHDoIcl4UAEd5oLf3aKimIAMqojozoitm8l/ObeyyGi6pnU56Mqc9fu5M3vN1BeG6Qgw8vqnTX0LMokO93LtqoAvYoyqAxG2bSrlnG9i9i4O8CEPkUM6mSurmerJhoxSjlEw1BXBu408KaDHoFANfgyoWoLaC7IKoFda8GfBSZrwLZ27v36Xt5a8xYhQqSTToAAOjpppKGjE8QI5fXjJ0AADx7uGHEHZ/U7q4VHro7UdWrmzydUWooUGprLhcjMxJWdBaEQrowMhBBEKiqQLjeaJvB17oynIHWFTRpSuauW6p115HfMRgiorQzhdmsIt6C2IoiMSgraZ6Lr4PW7CQejaG6By5Waojb7EqytwePzU12+C19aBr70jJYeEtC6yzmMBb4GFsJPuhW/x8hjeB3oBKzHkKveHa+vhHX8vpkLX8cRb7nwJHwd1bbudT1C+OMnYe0PsTo+GCt6OYW4+ozBNeQYhFfdKQtXb2X9e5dCaN/4aBeFh99Gbm/11QZdD7N26XNsXvUm4VAV/CT54aH/qLto2+loZRsAT3/UtDqkRhq/OGmqso03Vj3NW5ueafL1h4a/RMdMtQdwbSTEGbP+SWV0/1wVAdzb90wmtFGrFQjw75XzeX3jCsJSR8b6LvKmce+gsfTNsWcCNWVLKXctbrzmpQt4dewY2poMCW2KUDTK0V80LeLR1iN4fZL65zWvNMILi8Jsr90/Hm5YG/jtaPXFGCklPyyIsHFDBD0KLheEQuD1wagxXoqK7HEwa7dG2T4ngssLbcZ60INQuSaKN0eQ09OFsNHBTAb6unLC09dBREcbUIx7aInpwu2HiOOXtOejKl8u28ZVL84lZEHE6MLD2nHvOUObYVRJZtG78PkdULUVkJBeAMX9IFwDJYOh20RYNwNWTwUhYfjlMOpXLTxodQY+P9Dysf1y+vHa6a/ZOJrkogcCbLjxN9RNm0aTCl8APh8EY3MDIcDlIm3IYLq8+GJyBtrMbFiyi+3rKmnXM492PXMp21rDmgU7yCrw43YL5nywDo/XxYSLelPYITmpHs1N1e6d/Dj5U3Zv3kj7Pv0ZMOFovGl7djBrK8qZ9uJ/2Lp6JdmFxejRCAUdO3PkBZfg8TV/3c5W6/jZSbwHW3DRCvgocZFQ11Xn486xflIGn7gOauMkq+a1xXvJvQiX9RX6cPU21r9xWtw2BcOvI2+gufDWppjz+cVUVzQ9Me8x6AY6975QyUY8p28PgitOsp4A/cn613h+7SMJ2708bhaagqzymKn3Jmzzl75ncFQb6zmeN83/ijm7tzb5+r+GTWJwXrHl/gG+2rqN/1uYWOF08lHj8bmsOzTjPm3csWxIhgs+Ocb65/Xx6jAvLoqv2lmYBo8eq+b8ffR+gLKypu+Rx53gpahYzfmrWh9l3dsNRBA0DE82Zjanp4tOJ6dOuGdk0TYi7y7b62+iXRbey4ZibHTF51Bw/OykOR2/qcu28fPn1Po+ols+L10Zv+xOq+az38Osxw/8uH6nw7nPJ2zWWlFx+urpl9uP105LPedP6jrLDz8CWV5uuQ+Rnk6feXPtG1QL8O2Ha/nuw7U//T7oqA4smrYZPdr4M/HcO0ZQ1DG1nb/yraW8cPsNhOr2CNwUdOjERff/A7fHQ3XZbp69/goiof03AtJz8rjqieebvYyH6jMy9fdjTTh9ANHXPrJsQt9dGt/pAyjbir7enAJkU5QvfCFhm11zn1CyUV2xOq7TB7B2SdM7aGaIRs0qeaktOphx+gDumm995fWLbfFLX9Rz34qPLdsA4jp9AI+utF6OpJ77Fpt7Lw82sSNohrnbzSmt1qgJbvLBysSlGnbWga6wsFVXq8d1+gDmzFZXsN32zT596Ox1aVSsjBKqUFMOTSbR6fsr3MotVejry5M/GAclbnlTQQ07xsw1cTcsWzfhOpht8Zm75H0jTPQQZkmC0lGtldrvv1dy+gBkbS3RgKIqbAsidcmCL/ZWN1389ZYmnT6AmW+mvortwi8/28vpA9i1aQNr5xvl2hZPm9Ko0wdQW1HG2h9av7Of+o6faVIgVMrMEJPyNlLgszogUv/9pMo7MLGhkzocTO+lVeB8oA4ODocOqVrA/ScO+JZ9EN/jTU9uWv9nkOJnJXDSeFPNXOdbV3bU8ksgPYFATF4JWme10IjcAYnLDhQc9mslG5k53cnM6R23Tdf+1guXArhcZsPS1C6Qn3e72VS7u4Za3yU9pk0/U+3u6HWSZRsAo/PjC55c3+swpf4B7hhg7r3c2t96COawoviKsfVkKqbGndIzcUh1YRpoCp5oWppGXn7840eNVpe7b3PEPn1o7HVp5PRy4VUsGZFMXOM77/c30T4LrbM9IlsOyeOhswcr93Fkd7VSNy2KJw1GW3zm9j8dFFI/DgYG5qqHi7YE6cOHI/LylPrQMjLQvKkTor8vQhMMPWZv9e0BR7ZHczf9TBx7TuqWsKhn4KTj98rnAyjs2JluQ43Iyv7jJ+Hx+Ro9NiM3j66DhzX7GFVJ+Rw/gOCcBTD1u6Y7uPAUfB2t1yaDmLjLp0/DmgVGoq+UoAnILsbVd7Qh7uJp/GQ4EMI121n/7iUQKt/7BeGicOyd5PYwV4cvHroeYd2y/7Fp5esxcZdYOIrwMnD0PRR3sF76oiHx8vxcZHL5SVOUbby75r+8uqFpx+7hEa/RPqOLko3aSIgzZz9ORaRuv9c04P4BZ3NkobpM/VOrfuCVjcsI64a4iwYU+dK4d9CR9Mm2RyVsWuk27lzUeJ6fG3ht7BiKFcVdwtEok+KIu7TzaLw6Kf7igxkWbIvw/I+Ni7uMaAu/GWWPuMuPP+wRd9FcEAoa+fyjxngptEncpW6bIe6iNRR3WR3Fl6uR3UNLPXGXDeWEp6+HcBRtYBvcg9s64i7NRHOLu3y9YjtX/G8ugciBhxtfNKI9fz5riP2DSjaL3zdy/apLjZtNeiG06Q/haigZEhN3+RrWfGW0P+xyGHVFS47YFgY/Pxgda2Hmg/MG8+KpqStwogeDbLz5t9ROmRJf3MXvh/qQTiHA7SZtyBC6vPC/5Ay0mdm4dDfb1lXSrmcu7XrkUr6tdo+4i0cw5/21eHwuJl7Uh/x2qVu7ryHVu3fx45TPDHGXvv3pP34SXv+e+URtZQXTX/ovW1etILu4DXokQmGHThxxwSV4vOp+QCIOeXGXeoLrN8PHUyEchrwc8Hkh3Q+jh+ErVFu5qUdKCcFa8PggGkYGA+iREFpmDppNZRYAZDRMzbYfiYZrcPuycacVQDSEJ6cTmsue4uh6NEQkUkMoWB37PYDbk0l6pn1S+wDvf30j2yqXAhKBF8kOcvwDOHfSs7bZWLJrPp9ufJMMdzoFaSVUhHbTMb07R3c6FU3YMzEPRyOsrdmJjsSFoDJSS5rLT5EviyK/fcnMW2trcAFlkSDt0jLRpSTNrVa4fV82Vlfz1dZt5Hk8LCkvx+tyke3ycGKXjpQoOn317Kyt447v11FVB0U+WBMAH3DDwGKObG+f1PWu2gg7aiXd81yUVkeJRHWiuOiR5zIlJGKW2lodjwc8nubbeYsGdfQoeNI1ArujeDIELl/q7PQ1RAYj4DHUSPXaEDIYQctJM+XAOo7fgZGMcg51oSjhqM6PG8tI87rIS/ewaHMFuek+0jyCzHQPehSCIZ30NDcbdlbTq00WXYpSW+gBAD0KoWoQLnB5wb3PLk6gwsjlS8/fEw4WqARP+kGx43faa6exJrCGNNKow1j8bPh/Fy6iMWVwDx7ChLm679X8eqRadFJrIFpVRc2KlUR3bCd96FD0igoiu8vwdGhPpKwMl9eLKzMLNEG0LoDQo/h7HBxlPOIRrIvg8bmQUYmuSzw+++YnrQU9GiUcDOJL37P7F6ytweP3o2ku9GiUSCi43+5gMjjkHT9d1wk/lNiJ8N76S6WJoL51DZGP/40s32bc3Pf53ESvkXhPvtZy//XsnPc05T80/X5y+v+MopHXKdlYt/Q51ix+Cin3V9gQmp8xx79KWoaaA/j5d3ewfvvkuG2KcgZw+ljrDmA4EuLiGfGLAx/V9jSu7PN7yzYA/rlqCi9vmtPk6wWeTN4eczVezfpDvrSumkvnfEJNI2IAPs3FtT2HcmYHtTCKqJQcNfmruOu3XmDKMWpFm8d/ujShbM/b47tTmGY9DKYqJLnxiwB1cbQTrh7mZmxHtYWSigqdzz8NEowt6Hbu4mLsOI+tTiXA2neCVK/b/5tJby/ofm7zy0PbhQxECL+zFH31bvC7wSWgJiZeI8B9fE/ch8UvreM4fgdGczp+ui75w3uLeHnOBktSXB6XYO6dR5OtcK23KMs+hg9ugJrtxu/eTJh4B4y5Gqq3w8vnw5aYmENmWzjjSZj1GKz6wtgVPOEBGHh2y41fgUs+uoT5O+cr9fHOye/QoyD1HCEpJWvPOpvgEgviNELQ4cknyBo3zv6BtTB1VSE+e2YRm5eX4/G50KM6Uoc+R5Qw/oLetta1bUmWz5rBl/99gtqKcjoPGsqky67ii6cfY+OShWTk5dN7zFiWfD2VQHUV3YaN4KTrfptUB/CQV/UMP/O6qXahd+M7IYmIfPqU4fRBo9v+csW3RFer3SRD5eviOn0AFYtfIlJnXSWtcvdSVi/6d6NOH4DUA/ww4ybL/deTyOkD2FGxSMnGDXPOTNjmy63vURepsWxjZ7A6rtMHsCtczX3L1FQ9f//jjEadPoCgHuWR5d+zqbZKycZ9ixYnDNoJAQ8tsa7qOX9HlakJ4vnTV1u2AfD0/GBcpw/gifnqinozpoV+cvoA1q+LsnGDvQqb5csjjTp9ALWbJeXLU0cZMDJjveH0AQQie5w+AAmRT1ciw4qSrg5J44Mft/CSRacPIByVXP2SuiJxixCqgXeu2uP0gbHz99nvYPsymHL3HqcPoHorvHGp4fQB1O6E9641ir6nIKpOH8AZH55hw0iST8U771pz+gCkZNONv7F3QK2E2e+tYfPycgDCwSjRiLHjt+TrLaz8Nr4yeaoQrK3h03//jdqKcgDW/zif9x75CxuXGKr9NWW7mffx+wSqKkFK1sz9lm/fe6sFR3zgpLzjR5nJyfD6LZZNyEgYuTvx8XJL/DIJiQjuNieFGzLZrjGqypclbFNXs9ly/8lkd3iHqXbb6qy/nxVV5m5miyo3WbYBsLEu/nksgVXV5Uo2Zu00t2Aw22S7xnhhzS5T7UKKgQarEpRZANAlBC0UnW5IZeX+x+/aZa/jUr0+viNZbbOj2ZzIrdUJGoCsaFwK26H1sXiLufIs8fhxU4JSSK2VsvUQbGLs2xZBaSOlLgLle/8eqYOdqS9xf6hRM2uWWge1tYnbpCA7NzY9T9mxMcG9P0XYvWUTkeDez6jKHdubaG2wfZ3aQnaySX3Hr4vJkMTDzCkaNoZwexDtE4t3iB5q0UlpbYeYGQ3+YutKWXnFw0HE/9pzCgZZ7j+Z9Mjob6pdh4xulm0Mzu1oqt2kIuvnF8DgnMK4r3s1jcG5RUo2zu9s7r2c07mDZRu/G2DueixQzJUbWZI4pMSjgS+OApkZior3H2e7dvbmM+T2jd9fXoLXWxNa1wT51G4NkW9PHqlD83NEj/j3JTMc219NWK3FKOwF2e33/7vLC50Ph24T9n8tZ597bHoBtE1NZctDmZzTTlU6XitUv25aIx36NK3Q26GPPVoaLU1R526kZe+tQF3cpfvejfZJ9eg8cEgzj8peUt7x8513cuJGXg++I0co2fGc+Gu07sPAnwn+DEPerx7NhWvsObhKujfdgQnc6UW0PfphmixzINy0GX8Pmsd6LHF6ZkcGjr4XX1rjToQ/oxODDn/Acv/1jB94V8I2w3terWTjzyP+g5bgFL669924FXLvMtw+7u5zKq44pSeG5nTkqu4TLNsAuGfgWLpl7C937xKCTulZ3D9oHHletVyvi7t1Jd8d/7PonJ7G+Z33l+M3S1GGj/a+xM7WWxPV8hUvGuijYxzdCLcGfx6vnld05DgvhUWiXqyNIcPctGlrryOW2dFF0QgXov6rqT+lBRQM1cjokDqOn2tMR1xjOkC2D9pnITrm7LmdpbnxXDAw5RRKD2XG9yrintP6U5Rp7Vpql+Pj/jNT1PFxueGCV6HLkeDLNn7aDoLzXoLsdkau39CLjZIPLi90GQuXfgCHXw/ZHaDTGLjwdeP1FOTOkXcq9/H9z5pXdKi5yBw7lpyzreVmajk5B42i576MOLkLAyd2IDPPR367dHKK08gpTuPI83rSZeDB4ey6PR7OvO2PtO/Tn6yCIg476XTOuO2PDDnuZDILCunYfxDH/ep62vXqS1ZhESNPP4ehJ5zS0sM+IFJe3MXBwcHB4eDBEXc5MJzno4ODg8Ohg+ozMvW1hoHgZzNgQRxBirHD8B2hXgB7X/TdpUQXfAHRKK7BE9GKu9jWd+2Wb6la/SlC8yCljhAusnufjr+wj3LfUkrWLf8fW9a8RyhQhh6NxaMLNwXFI+kx+Doyc6yHRwJU12znlanxV0EuO/5r3KaLvTfOhxte5OU1/0Jn/7yrXE8Bfxr2LEVp6iUqfijfyIMrPmFd7S70BlIHXlzc0vs4Ti4Zomzj+91beX/LarYFash0e/FqGtluHye368ZAxTDPej7YuJkHly1v9LVCr5eHhg2hR5ZaLZ4Vu6v55bcbm3y9g0/j5YnqdfwAXlsS4uPVUcKxNDi3gDaZcNlAL/1sqrFXz4b1UTZuiJKZJejbz43Xa+/OVbhasnNehHCNROqS4A6JOwPaHO4ho33q7PqFZ64nOr8UdIx42/IARCX43bhP64O7p33lPByan/kbynjtu42keV1cdnhXFm2p4OHPl7O7JkQ4qhOOStpm+xnUMYe6UJQlWyqpDIQZ1CGXJy46jOw0e0oQtSg7VsB3T0M0DMMvh5JBhuLn7H9BxSZjVztYDe40GH4ZHKkukNbS6LrO4BcGWz7eg4d5l6aosA8gIxE23/47qj75BHQdLS8PLSuL6O7daD4fuN1Ey8shFAIp0XJy0NLTSRs6lJK778KVeXDUtGvIhiW7WPHtNjJyfAye1JH07BRV6z3ESfkdv9DKDci3P0vYh/ar8/DkZts2JllTQei524y6fgAuD56L/4yWr+5k1Gz6htIvbmbfstTC5aPjqc/hze2q1P+qhf9i/bLnm3xdc/kZc/xr+NOt52bEK97ekCtOiq+YGY/Jm9/hmZX3x23jEm6eP3Iqbs365GNx5WZ+Oa/pzwvg4YHncriCbPWcXaXctGBqo6+5hOCJw46hX47ahHlrbR3nzIyftC6AD8YfSY7X+uc17tPEqqCj8v08NFLtPH55cYgPVzUttPK3ST7aZNoTzb56VYRZM/coVBYWaRx/on2FWvWIZMXzQcKNiMkAdD/fR3pJ64/MD09dS3TGhrhtvFcehlbc9KTI2fE7MJpzx2/R5grO+NdMwlHjvMz2u6kMmFeZLcnxM+t3k5plbEmjais8PtKo1weGczfxDvgiTijkuNvgKLUyQi3NwOfVQ3TbpbXjs3MTz89aIxuu+jU1U6daOtbbtSvdP1FT+m5trFu4k48e3yNolNc2nfP/b9RBU8IhlTjkyznIj6eaaqe/ae/NR181d4/TBxANoy9TVIKKUbXyI/Z1+gBkNEjVms+V+9+y5r24r+vRANs2Wi9/EQ7XWT72QPhw48sJ20RlhIVl3yrZ+XjrwoRtnl33tZKNT0rXNvlaVEo+2dr062a510SZBgl8Wlpq2cacbeZUAOfsDiRulICpG+Kra3602r4yCKv3cTB37tCpqLBPbbNmo96k0wdQtiQ1SjpE5yc+dyIzm94NdmhdvDN/809OH3BATh9AaUWArRXq13qLsvSDPU4fGEqd3z0d/5gEC4WHClvqrKuptzQ106ZZPja0di2hjQfXfW7ZN3vf28u21rJ1TYoq9h7ipLzjR7rJVfc8+3b7AEjbf8VapMVRmzgAXP7cpl/zNf2aWdzexOP0+qwrNLncydn+z3Sb+05zvE0rUZkh14SYToGJzzQeOZ7453FugtfN0D7NnDhMoc+6rbYZyQv9SE+g2Jnvt28lct+PRAhsDfV0pcXvy53g9daC8CfOHhAWhUIckk++Dddzui91wpQbJb2RSIu03PjH+G2ebzgkH6/CuS8E2kEW6unP3D8KKK2Rvzm0flLe8XNdfJqpdt7Tj7HVrtZ9GKLDnnw7UdQJrf9YW/rOHfAzXOn753R583qQ1fMk5f57D/ktTSqHAll5fSnuaD08RxNmH/Rqk9kret+esE1JWie6ZfVVsnNW+8Mo8GQ0+bqG4Dc91c6vCzr1ocjXuPpbh7RMzuygpoIJcFOfxHl1bfw+xhdbzyfsnGnOufxDf/WQ6J8Pavqhk+mBE3vYl8I8cLBnr3lAvwFu0mx0xtLbauT0bvy6cWdA/uDUSMd2H9cj/mXt1nCN75Ks4TgocuHITnQv2nPvO7x7PmkHUIrllEElZPtTfHLY52TofMSe39sOhBMfBt/+KsyAUS7pxL8mZ2zNSLZL3Xm9dvC1NoykZWhzy28tH5t77rm48w6O8gb1DD22E+k5ex6C/ca2I69t0/Mih9ZLyuf4gZGEHP7XS1DTSEhJfg7eX56DEPavmEspkZuXQzSC6NgPodnnR+uRAHWlc3H585HRIFIPkdZ2GEKhNEFDgoEytqx5l0i0joodiwjUbSOnoB/tu55CXvFwRIJaf2Z4/ctLqahrvGB8+8IjOXGU+sOxLlLNE8v+wsryRehECOpBwnqIDHc2F3a/hvEl6o4yQFiP8uX2ZXy89Qc215UT1XWEJjiioAfXdp+Ez6X+vQSjEeaWbaMmEibN5cHvchGROofltcGj2bNqLqXkhm/nMr9y75DMtj4fP+/ehRPbtbPlWrly+gqW1TYeivnGuK60SVcrTVFPRUDnlcVh1lXo5Pgh1yfole9mYhcXms3XfCgk2bZVJytLkJvXPGtmtVt1InUSTyZUr9Px5Aiyu7vQXKmx4weg14SIzt2C8LnA7yaypQq2VKH1KMAzrnPC88vJ8TswmlvVMxzVmbV6F+leF8O75BOO6jz/zTp2VAXxugUrt1dzTN82tMtNIxTV2bCrlrkbyrhwZCdGdj1IhHykhPXfQDQEXccZ5ZyCVbByMlSVgssDNTuMUIARV0LGwfG+H/v2MZ5c+qSlY9879T265amJxLU0wQ0b2Prnv6BXVpJ9wvFoOTkEfvwRT7v2CK+X4Jo1hDash1CY7NNOJbJpE1lHH03awBQtYZKAcCjK5mVlZOT6KOpkT4Sbw4Gj+ow8KBw/BwcHB4eDA8fxOzCc56ODg4PDocMhL+7i4ODg4ODg4ODg4ODgEB/H8XNwcHBwcHBwcHBwcDjIcRw/BwcHBwcHBwcHBweHgxzH8XNwcHBwcHBwcHBwcDjIcRw/BwcHBwcHBwcHBweHgxzH8XNwcHBwcHBwcHBwcDjIcRw/BwcHBwcHBwcHBweHgxzH8XNwcHBwcHBwcHBwcDjIcRw/BwcHBwcHBwcHBweHgxzH8XNwcHBwcHBwcHBwcDjIcRw/BwcHBwcHBwcHBweHgxzH8XNwcHBwcHBwcHBwcDjIcRw/BwcHBwcHBwcHBweHgxzH8XNwcHBwcHBwcHBwcDjIcRw/BwcHBwcHBwcHBweHgxzH8XNwcHBwcHBwcHBwcDjIcRw/BwcHBwcHBwcHBweHgxzH8XNwcHBwcHBwcHBwcDjIcRw/BwcHBwcHBwcHBweHgxwhpWzpMSRECLEDWH+AhxUCO5thOAejjWTZOVhsJMvOwWIjWXac99L6bFix01lKWdRcgznYsPh8tJNknUetkUP5vcOh/f4P5fcOh/b7b+n3rvSMTAnHzwpCiO+llMMdG63HzsFiI1l2DhYbybLjvJfWZyOZdhxahkP5+z2U3zsc2u//UH7vcGi//1R/706op4ODg4ODg4ODg4ODw0GO4/g5ODg4ODg4ODg4ODgc5BzMjt9Tjo1WZ+dgsZEsOweLjWTZcd5L67ORTDsOLcOh/P0eyu8dDu33fyi/dzi0339Kv/eDNsfPwcHBwcHBwcHBwcHBweBg3vFzcHBwcHBwcHBwcHBwwHH8HBwcHBwcHBwcHBwcDnocx8/BwcHBwcHBwaFZEUKIhv86ODgkH3dLD0AVIUQ+cBUQAJ6RUla28JAcDjKEEC7geinl35rZzk2N/LkCmCulXNCctpsTIYQGZKbitSmEeEFKeXGivzk4ODiYRQgxCFgkpdRbeixJpjOwTjriEocMQogSICSl3NXSY2lOhBAiVc7rg2HH7y0gE2gPzBJCdGvh8SgjhLjBzN9ssDNXCHGNECLP7r5j/QshxEVCiP+L/d5JCDHSpr5vivdjh416pJRR4AI7+2yC4RiLGO1jP78CjgeeFkLcapcRIURGzBlDCNFLCHGqEMJjV/+xfl8WQmQLITKARcASIcQtdtqI2flACPH+Pj8vCCFuEEL4bTDRfx97LuAwG/rdDyHEo0KIw5uj70Zs5cUmn83V/49CiN8LIbo3lw2HgxMhRBchRHpLj6O5iO12/RV4N3Y/OeiJzQUygXlCiD80/HsLDqtV0PAzsPs53NLEnL6/AqcKIQpbejx2su+5W+/0pcI5fTA4fgVSyt9LKW8GbgKmCSEWCiGOFUK8bpcRIUSVEKKykZ8qIYTdOxmXNvK3n9tsA+A8oB3wnRDiVSHEcTaftP8CxrDHaaoCHrep76wEP3YzUwjxmBDiSCHEsPofm210AIZJKW+Onc+HAcXAOOz9/qcDfiFEe+Bz4GLgORv7B+gX2+E7HfgE6BqzYzdrgGrg6dhPJcZ51iv2uyWEEL8TQlQBgxpe68B24D31YTfKXOBOIcRqIcRfhRDD7excCDE15oznA/MwFhQesdNGA04BIsDrQojvhBC/FUJ0aiZbDgcJQogi4LdAfkuPpTkQQrikwbFALvDvVJgo2oAmpawGhgHXCSGuBmOyfIi8/yZp4DBcDjwohPilEGJgCw/LFqSUpRibM2OA42LO/0FBg+/tMiHEn4QQVwsh+qTCrl/Kh3oCVUKILlLKdVLKz2KTi3ZAGbDQLiNSyuZwJvZCCHEBcCHQVQjxfoOXsoDddtuTUq4C7oitwJ0M/AeICiH+C/xDSqlqc5SUcpgQYn7MXpkQwqvYJ7G+7rajnwNgSOzfexoOAzjKRhvFQLDB72GgjZSyTggRbOIYKwgpZa0Q4hfAv6SUDwohFtjYP4Antnp5OvCYlDIshGiOG+LhUsoRDX7/QAjxnZRyhBBisdVOpZT3CSEewAgfv1x9mKZsPg88H3PMzgIeEEJ0klL2tMlEjpSyUgjxS+B/Uso/CiF+tKnvvZBSrgcexJjI9AT+ADwAHBI7HA6W2YkR7XAjhgN4UBGLHkEIcR6wCjgbaCeEOCUVJoxWEEKI+vcNdAQ+AB4RQniklP84WN/3gRC7J/8cuA14FWOXzLb5a0sQ+94l4MNYiD0RcAshPkzlsE9hRMhVSimjQojrMeY4fwd+jxF9uKzlRmeOg8Hxuxz4yZmInWibY7/WNpdRIUQx8FMomZRygw3dfgOUAoXAww3+XgU0ywQtFu51GcZF+RbwEjAW+JI9zo5VwrFQlvqVkSLA1pyGWDjfLzBC8hp+H7ZO1qWUE+3srwleAuYIIep3lE4BXhZGuOQSG+0IIcQY4GcYnx3YPyF/ElgH/ABMF0J0xtiNs5vMmHO0AYxwYoybL0BIpWMppS6EGJG4pe30APpg5MMstbFfdyz05lzgDhv7bZTYd35e7CcK2Bau7JD6CCHSpJR1sf+3B7KllEuFENcCfxJC9JNS2nnfaxUIIY4D/oTxnL0dY6L/DsYE8qCiweQfIcQlGJPj84CvgL/FnL+/tuQYWxohhBvoC1wEHIHhODweey1DSlnTgsOzTGw39xyMBZyTMCLZjsXYXHg3tgOcUgghTsW4Tm+KRfp1ASYB1wDlwMOxOalHSlnVQsNMSMo7flLK5cm0F/viH8bYVdzOnslZ/3jHmSG2Sr5eCPEzYIuUMhCzmYYRBrhO1UZDhBBzMU7WZ4HbpZT1u0pzhBBH2GDiUYwHWrEQ4i8Yq5t32tBvQ17AuFEeh7Eb9zNsnCwLIS6SUr4omsgblFLaFionpfyTEOJToD7P6yop5fex///MLjvADcDvgHeklIuFkRf7lY39I6V8FOP7r2e9EKI5nOebgRlCiNWAwAgpvTrmLD9vQ//zhBAjpJTf2dBXXIQQDwJnAKsxJoN/klKW22jiHuAzYKaU8rvY977Sxv5/QggxB/AArwPnSCnXNIcdh9RECJEFTBVG/vcXwC3AYCHEG8A0jGiHDti74NUiNHR+YlQAU6WU22O/HxUL7/4YOKXB7lhKI4ToC5wphPhrbG6RDjwhpfwB+EEIsQz4Qgih2/kcTSWEoXmwAlgPvAGUSSmPib12Y+zv77TYANXpjPG82YoRwXIZ8EcgXQjxVqrs/MXCkTMx0smeANoANRjh2rOBrcAJMWf35xibT5+2yGBNcDDk+CWbPwGjgRVSyq4Y3v5sm228zt47Y1GMm4LdnCOlnCSlfLne6RNCdAWQUp6p2rmU8iWMVf77MHYyT5dS2v0+ekgp/wDUxELlTgJG2dh/RuzfZOUSzsP4rt8BttudFxXbgT1VSnmqlPIBACnlGinl9TbbaSOEeFYI8Uns9340nruqhJTyY6AnRmjYDUBvKeVHUsoaKeXfbTAxCkM0arUwBEsWNkd4ZOzBUgWMkVIeL6V8zmanDynlG1LKQVLKX8d+XyOlPMtOG/CTiuvbUsphUsr7HafPoSGxnb76fO+HgcOklDcCv8HIZz4dOA24TwjRsaXGaQf77Hj5You4m4E+QogBDZo+A7TFiPY5WGiHsSPym1iKRzUNdjVji5ofAzcLQ2zqkMr1E0K0A67G+N7nYywIPBt77TyMSCw7Iz6aldh9v/7/9RFE3wG5scgypJT/xdjAGIaxuJMq1O/gPQVcCXwlpQxjaCNEgHdjTt+lGDuczbKgahcpv+PXAoSllLuEEJoQQpNSfiWE+LvNNtxSyp/C1KSUIWFTbtw+vIlxAe77N1tUC4UQo4HFUsr6sIVsIcQoKeUcO/qPUX/zKI89SLdi5MrZgpTyydi/zZ5TKIS4DmM1bBuGsy8wwmRtU1+MxaWPtau/ODwH/Jc9IYUrgNeIPdhs5jCMCYYbY9cAKeX/bOr7OJv6iUvsoXGulPJPzWVDCNEL+DdG3uiA2MP4VCnln+20EwuRPQcjp8/B4SeEkb96jxDiTinlf4QQAeBFIcS1UspPhBC/wkjd0DGu607AxkZ2zVo9+zh9N2HcxztiOLgvAc8IIV4AijCiPE6RUm5rqfHahTBEz/piRC1oGFEM10opHxFCnC6E+BIjNG48xmLXMCllWYsNOEnsew5LKbcIIaqBu6SU58d2u4+JXQMe4CIpZavPF6tHxkqTCEOkpkQIsU5K+ZIQ4mzgHCHEUIyyawD3yRQp7xSbV04AHov9aSjwkRCiAzAD+AdwmxDiRIw0jbOllKtbYqxmESl2L21xhBCTMVat7sNYndsOjJBS2ibDLoT4AvinlPL92O+nYdSRm2RT/30wQlMfxAixqScbuEVKqRy2GrMzH+OmXv/w04DvpZS2qWEKIyn6LWAghrORCfyflPIJu2zE7DR7LqEQYhWGIE6zhj8IIf6NIaDwBka4AgBSyrdttFEvsDJfSjk09rcFUsohdtmI9fkC0B1YgOEsg+FH2baDKYQYDBwZ+/XrWKiS7QghnscQwmmWsFIhxDSM6/3JBt/JIinlgPhHWrJ1P4ZQx2vsfY7ZLlLlkFrEdvE8QHsp5ddCiPOBe4FfSyk/a9DuVqCPnffYliAW+nUhRs72ZGC9lPIiIcRZGKHp/YBHpJSLWm6U9iGEGIKxeOmVUq4XQkzAUPZeKKV8TAjxEMZcox9wjZSyWfQLWhNCiI5Syo2x/w/BqGs7I/b7/4DnpZRThKF6mQdUp6IzLIQ4F2Px+hHg/tj/n8HYvRyP8b3fnirnujDKEV2JsYitAWkY2iHHYpy//5RSLhJC5GC8tzop5c6WGq9ZnB2/A+c0jFWL32DkXeWwt9KjHVwFvCSEqC99sBG4xMb+e2OoeOZiPIzqqQKusNHOvitcujASmW1DSvlM7L/Tgeas4disuYQxNmKEezQ3fmAXeyuSSsA2xw+oEUIUsEfYZzTN896GY5SOaJYVLGHUz7yCPZ/Ni0KIp6SU/2wGc6OAnwkh1mM4SwLDibVrxzddSvntPhFVEZv63pfzYv9e0+Bvkua9Rh1aMbEIGV1KuVEIcTtGba9bpJSvxs7JR4UQN0opP4kdshY4VjQQgUkFYjsEXaSUH8b+lIGRG3QdRrjjL2OLoF9IQ2U35XYz4yGlXBDb2X1OCPGllPKBWBjnBcIQ7rk9FnmSLqVsNgG+1kDsfWcDjwshLsYQUbsU6CWEWIKh3rkKw4mYIg3Bk5QTPQEQQkwCTsDQJvg6ttA4CyOC7VHgSSFEpkwtURcXxg5fJUZ0WVvg/zA2G7KAq4QQL0kpZ5GcuZstODt+rZjY6g/NdaEIIcbETthmQQjxNjAVI7wMjHj2iVLK0220cS/wYH0+lDCkdm+WUtoqIlO/cyWE+FFKOUgYpQq+llKOttHGsxhO+Uc0KOsgUzDxPRbu809gAEYB9yKMEAhbV3dj4THXS6NekO0II59vjIwpqwlDNGaWjc5YQ1udG/u7NESf7Oj/E+Ba4A1plFk5G/iFlPIEO/p3cGiKeudGCNFOSrkl9rdfA2cCd0spZ8Qmxn/BSD8ow1hV35gquwPwUwHuYzBymzKklOtiTu4FGPL8l8QWQG/AiLq4A4ikuuO3r/Mac3jGYji7c6SUDwshxmMsos2LhX0eVA5vY9Qvdggjt3Ms0DEW4twWQyTkR4wad2OA4+t3AVOBBtd0/Xu8HmPB70PgKWmkRPXEWCD/vZTywRYd8AEgDK2L3VLKCiHEURi6G49h7PblY0T8pWM8T/0Y78/OklvNirPjZxIhxAwp5VhhFHFueLOqX5XPttFWAcYW+VhACiFmAPfYFQIohPgne3ZiLtj3dRvD5K7CUHa8M2ZvCsa2uZ2cIKX8ff0v0qgVeCL2q4c2ay5hjA2xHy8NSpTYjUhCrpeUcl7sQd8b4xpZLo1kaLspBJYIIb5lb2f5VJv6F+wJIYU9uZe2EwuLGgv0lFL+VxjlT+wseHsNRnJ6HyHEZowdlYts7P8nhBDpGLscnaSUV8YmAL0b7II4HELEJojHY8idf4+hKPzv2E7fHUKIB6SULwghJjcIlfqkyQ5bIbEJcBj4OBbO+n+xxZa/Y+S57QKKhBCnYDhAZzfTPTGpCCGyZEy6XghxEUbdts1Syk+FEDqG9H1USvl3IUQUY4frpwLYBytCiPwGoe3tMATunhNGCYsnY2GRvTF2kzpiRPykBPs47V2ANVLKR4UQ24HjgbFCiGlSypWx+UbK+Bqx8b4GLI9FIHwpjBzdozDmsNkYKRN/xVjcDqeS0wcp9GW0NFLKsbF/m72QO0ZS9HSMIs5ghBW+BhxtU//fJ26ijjTkqs9vZjMuIYRP7lElTcN48NjNU7HdxD8A72NMyP9gpwGZvKL0TxPL9YrZ/VEI8TKg7PgJIZpSg+0lDNEVO8NJAe6yub99+S9GeZN3MBy+02gegRqEEH/ECF3tHbPrAV7EqO2kjDTUNY+O7VpqsnnrDP0XmMue0iSbMXJKHcfvEKLBrkAhxiLDrzGiAI4SQuTFnD8vhpP0A8aCWsoRe5/14haXYEQ4TMdIDajGUP9+DmNHsw1wrkwh4Y6miC3oPCiE+B1G3d+7MO6PvxFCdI19vxJD0CcsY0JvhwgnCUPQZA2GUMvoWJTFC7FFgn9j7AIvFEI8LaVMmVDBeqcvFrp7Vmzhda2U8onYrvfpgE8I8ZlMPVXnNcBijJzEB4QQr2EsKq/BcNI/wshZvB6j5FLKLWA4jt8BIAyJ2sVSyj7NbKpE7q3u92dhyPvagjTKHjQbQohbpZQPNtxZ3Me+naUDXgKmCCH+G/v9Muyp37YXck8u4TRszlMSQvxdSnmjEOIDGv+87Nq9qqc5c71OifOa3XmESCmn2dlfI/0/IoSYSmz3HbhMSjm/mcydgZFPMC9me4sw6p3ZQrLComN0l1KeVx9RIKWsFeLQkmt3+GmnbwJGPa+IlHK6EOJrjJz1w2K7H/8QQrwjU1DMop4GE+EJwOUYjp4H4756TqzN2bE2qZbn1CSxHZ31GEIea4EzYwuJX2DoFMiYM3AHxuLPIUNsB/s2jHqUw2J/mxXbFX0utmD991jzlFC4bIgw6k2fh+HkPQccLoRoK6W8K7YAPxGjXEdKIIzSWX4p5Qph1FC8DkPQpSNGyahxsX+vwMjn25WKTh84jt8BIY2E5OVCiE5Syg3NaOpzYSidvR77/WyMwsu2Egsluw0jsbihUuVRTR5kjnrRk2bfWZRG4viPGA9aMFZgmuOzKsBYzTwCwwH4OmbLjvDbF2L//tWGvsywUxhqVfWTlbMxwlCUkVJeZkc/iUhm6HXDfmmmMM8YodhEuf57yUh0wAGSrLBogFDs4V//XrrTIBTX4dBACHEExqTweeBiIcSSWK7P87GdgcOEEB2a+XnabDQMeROGuMWVwFZpFGGPxkI9deBSIUSulPIVGqjcpiqxRRwhDbGeG4UQt2BEJs0RQiyVUn4fcww+EUJEGiycHtQ02OHWYjvAj2E4/n8QQvxaShmQUs7+f/buOzyu4mrg8O/sqnfJltx778bY2Nj03iH0klBDSWgJhJZK2peQBBJCSAIhoYcaei8GTAf3buPeu1WsLu35/pgrq/e7WpXzPo8ea+/uzoxkSfeeOzPneMHfP0XkEVXN7ggBRJWvTXCrqgQ4F5exNh63Yug2EfkVbqtScke5weGda38GxHg3oV4SkTW4RI7v4JbqjsL9jGer6vWRG23rWXKXZhKRWbi78l9RPU25b7My3sVsIpX7iQJV+vLtolZE3sEtIf0Rbj/eJcBOVb3Np/YnqepcP9qKNO8O5izc0jtwfwCOUFW/lt9WLJN8PdzrxUVkMG6v13RcEoW1uKUo63zu52Rql7/wOwNuWInIz3En7v/hfhfPwCVH8bX2ndfXj3B3FI/FbR6/HPiv+pRB1LtBMqXGsujZ6lP5lhp9HYsLKEfjTpwzgEtV9UO/+zLtk4iMwP0MvKmq/xW3N/oD4I9e8IeI9FHVDjkTVCPouxxXw6sIV3/wXuATdTV4u+P2B32sYUpC1ZZqfN2XgFtFJCK/xP29/xVuZVS5t9QxV9t5XTM/1Pi+TAfyVHWR9/g1IN9bBXEJLkP4HFUNV1Zl34lI0Ps/rbq1Jhn4D3CR97P+Mu4m8k+1A5Q1qEpcwp2jcGXOfovbi3oN8H+qOkdEeuBu7DylqqsiN9LWs8CvmcQlrKgl3EvOwkFE5qjqgeJlqvSOfa2qU3xq/wNc+tvngWfUx+xsbT3jI3XUOxORRao6zsc+Hsb94ZmFC8jfCueJQcK410tE/onLenUkro7P2cBXqnpFGPoK4vbN7F/B4NcMgoisACaoapH3OB6Yr6oj/Gi/jv6OxWUzFOBtVX3Xx7Zvwy3Frbos+hUNU7Y1b5Z8Gu5r+aKjXQiYlqkyM3AmblnUNtyF4GYRGQ3Mw2Xy/L+IDtQn3kX+nbisjCEvAOqO29P6uaoWV5kB6jTE7e+6DJepdIl37He4rRB34f5OdqqvuSlE5GbcXvA9uIQ+d3nLB1/Dzf6OAr7l5/VQOInINFX9wvv8h7jVVatw2VkfE1eW4o+4vazfAy5Q1e0RG3ArictIfhfwLu6GZSou+/XqzvJ7HIj0ADoaL8BbB0R7n3+NtyfHLyIyo2KZl4h8W0Tu8dYf+60io9hWEanYiJzhV+OqeiTuwn8nrobLIhHxZVmZVkm2o6opVT6Sw7DMD7zltyIS8D7Oxeflt94yyaG4C4YLgNUi4vsSGRGJFZELgRtxm/B/7s1s+Wm6ql4M7FWXtOZgYLjPfSAi1+OKBb+L23T9Ov4mENlClRlLvIx1Pra/n/c7P1NVb8El4In3lsP50bYAFQl8Rnkfvw5j0DcDKFLV13H1Qn8s9ZSrMB2feLyHvYGKRE6/xaVA/5aI9FLVpbj9Tl9HZqT+8b7kIbhZzXig4hz9K9zfpMuBg8DVsI3IIMNEXJ2+I3F7+paISByAqt6By055E26PY6cnIunezUdE5HTgWFU9DFgBHArcICJDVPUU4NfA4R0l6PPcLiILRORQ3P/533Ar3m4UkW/hkjZ9B3eT56aOHPSBy0iOu6GxG9iE29t3mrjam51ipsxm/JpJRK7ETfdmqOoQcVmt/qmqRzfy1ub0sRCYAIzH7Y94CJcFrM7Zxlb0cwpur1o/XFraFNyd2Ff87MfraxxwK3CeqvpSqkDaLtlO1eW3Idwvf5AwLL/1+orGpUS+DDhMVbv71bbX/lu4zclzqFKqQFXv9rGPL1V1qoh8gavVtQdYrKpD/erD62cVMFV9KnVSR/svAVNwgaXilmF+hTsh+JqoSETm4C4U0oFPcHtkS1T1Ip/a93WGupG+qv4NexiX6c/3v2GmfRGRE4FfAu/h/lb+Apcd7wxcqZr/amUdvw5Xx62uMYur83Ud8BLwjqpu885NtwCPqGqHzFTaEO8i+H/A86r6ZJXjE9UVcO8Wrr/J7Yl3Q/4h4Pfq0v6PAEpwGdjPwgVDTwB5uJJcX0VssM1UdXZLRB7DzWLeri4bKSIyDfe7fhZuVUeZqhZGarx+867D4oC7gbtVdUWEh+QbS+7SfNfi7uJ9CfuzWvldz63MWypzOvA3Vf23iPi+RE4ra2rl4O7k+EpERuGyPp2Fu3vyDHCzX+1r2yXbaZMyHt5F03nAEbjC9w/hNk/7ra+qnhCGdqt6TUTScOvl53jHwrHBfyPu5zdcXvQ+KnwYxr5EXfbLK4B/qMuMO9/H9ueKyBRVbYvZlqp/w+4P198wE1nial5N85Z8zcAlqDobl7XzbKAXcDXuWuNbVJkF6shBn7h9Wn1xicxew90IvAxXd/d9L7j9fcQGG0bezK7g9mv2q1gKKC4h3bdF5OKuEPSB21Igbv//zeJqFX7kfX/G4f7ubRS35WUwrhxAh+D9rFcEfXGqerGIPAncjqsBDG7Wfh+uHnCn28OprsZmKf7Xno44C/yar1jdJlYARCQK/6d/88TVxfk2cJh3d823ZRPSduUW/oOrSXh8xV3eMEgHloirIxOWZDuw/2R3ETBIVX8trkBvL5/v4F2MC46v1vAmePlMRMapt/HcTyIyBdioXjkSEUnC1SpaDvzZx35u8j5dA3woIq9TvYD7PX70oy5pQQwwEve7skJVS/xouw4iIgfjfs4qgqSgj+1PBS4Sl349n8r9sON97KNCWP+GmcgTlxX6aeC74pI8pOKCvb64mfHLcJnyHsAFf7O1sqB1h1Ml6PsBbgbzMdxy+Rm4PX7lwA+BUhF5Tl1mz84o4N10nYX7W3WHiJTh6o+e35H/j5uqYlmzOn8UkVLgJ+Jq1X4k3r43ETkIOBG30qnD7HGu8rN+EzBQRG5R1YtE5DURWYz73e6DW9Fh2Zo7GAv8mu8jEfkxbv/NscD3gVd97uM8XIrcK7xlI/1xm2f9EvZyC95Sl7Wqem+4+vD4WkS9AX/HLV06CrdOfx9wP24ZoC9U9QJxmaOO9c4rX6nqDr/ar+IQ4FIRWYv7o+1nAPAAbpkLInIY7q739bjivg/iLgz9UDEDu8H7iPE+fCWu3MEDwGrc92mQiFytqm/63RfuIvIO4EVv38xg3F11vxzvY1uNCfffMBN5PXC/c31wmW/vB3bgVnXcrK5m2VrcvuVR4bjR1Na8pXxjcX/jbsT9TQjilrz9FDfjuaozBH31LcX1gr4jcOeRioLs/YDVYbzB227UmPkdB3yjqn8Rkb3AT8WV46lY3nkYLvlNh5sRE5GrcbP051bciFbVU0TkP7gVb78DTlLVTREcpmkB2+PXTN6d6yuoknkPeKijLVtpC+IK9R4dxhmSin4GAMNU9T0RSQCC6nOmShGZq6qTRGSeqh7gHVugqhN87OMc3IXDh7ifrUOBW1T1eb/68PqpM8mGqq73oe393xMRuR9XHuRO7/F8VZ3Y2j4a6DsAJKmqb8VwRWQ5cIp66ZvFJXN4XcO8r1RcIVzf9waJyATczxW49PIL/O6jjj5PqbKs3HQiIvI03tJOdSUbknArPWYBi3GJTq5S1eURHGaL1Qx+RCQWt8pkLC7QOxp3k+OnuCWft3WGa4Eawc1FuMRcL+ISlqTi9iDfoqov1t9K5yYuq+mZuBvoyar6PRG5ETfb/WdVfV+8EggRHWgTibenr8q/9wOf4rLwHofbqzvLC3LvB+5V1ZWRHLNpGcvq2UzqCpb+S1XPUdWzvc99/UMvImeKyDcikiMiuSKSJyK+XcxW6eddcfuwKh6ni4ifmSrXAp+KyM9E5KaKDx/br0i28zxuVgbc3eeX/OzDU+rNYlacDDNxM4B++imuztol6jJiHkQYZjRVdb0X5BXivp6KDz8EveXP4C6KZlZ5zvcVBiLyXxFJEZcRczGwVFwxYb/kafWaPWtwd3LD7Q2/G/QuSp4EsryPJ8RlRQ23DlW70TTO+1sIbgn3o8AfxGUu3Ieb2T8O9/fsvo4a9EG1JW/nikuGNty7IROPm+kpx834vYtLANHhgz6o9nWfj1ux0RP3/3k2rlTFcar6YsWSx66g6tfqzXieC5yCu+ZIBfBWOH0AXCciCR0l6INqmWcP9v6djVvKW7Gn711giPfaay3o67hsqWczicgial8k5+B+SX6j/mxq/gNwqqoua/SVrZOpqtkVD1R1r/ibqGa19xGgcmme39oi2Q7AX3F3PLNE5Le4E6AvpSmqCNRY2rmbMNycEZHTcJmqeuOWZg3ALf/1o5D3U7jl0LtwgeXHXp9DCU8SltGqmuvdlX4Tt/l8Dv4tK5wtIm8Az+J+788BvhZXo6wiZX04hOOC6gpcBtR8ABG5C/gcl9E3nLrMxWFXUXFBW2U2/07c3uHp3sqLr4FyVd1X35LB9qzGjNfZuLIUHwMl3s3R94F/iytrMAVXw69Dp7GvSVzN4h8Cp6nqdhG5FLefUfG3ZE6HUOXnYTAuw/eTuMCoO3Ca99wUVb1bRP6jqgURG2wLeCtmYoE3ReReVf2ZuMQ1Baq6xzvnXSZdJGNrZ2aBX/O9idvE/V/v8fm4QtXbcKUXTvWhj+1tEPQBlEuVjJjeEkDfTtDq6rfh3fkK1x/BsCfb8f4grsWVozgadyF7Rhj+j97yLiqe8h6fh/t589uvcYW131PVA0TkSFwSjlZT1d+KyPu4bH7vVLngC+DuHPstWlza5TNwGXBLvT0WfonD1eSqKEOwE3e3/1Tcz1m4Ar9/haFNoUr5Du/ztgjKrm6DPkwbqBEQRXu/b7GqeqeIlAALxSWO2p/BsIMHfb2Agbj9setxF/qnAbtwN8ym4vayt3qZfHviBTfxuJuD3wd+oaqPiEgIOInKBDadqj5hXWr8PFyCWyp/P66e3V5VneQ9dw1wiIhcpap7IzbgZqry9UWraqGIjMTdxIlR1dtEJEZELseVJznbgr6OzwK/5jum4hfds0gq93/5cvGMm2V4BrdksWqmQr8vMn8CfCIiH1G5p8y31LXiMhT+G0gC+nv7i65W1e/71QdtkGynYr27t7cvbMuWVPUWETkLd1cV4MEw7aEoVdXd4hWjV9UPROQvfjWuql/UcSxcy0IeANYBC4BZ3s0L35ZFq+plfrXVFCJyCG6/6t+95cRJqrrWp+YfBr4UkYqfqTNwv5++E7fX9magv6peKa7e6Qjb69cxVbk4FLwba17QNxD4rYj8QlX/T9weuEF0oNT1VdW4yP8RrszRRGCdqq4RVwMV4AbgcQ1DzdtIqPF1j8fd0P4z7nrgGhG5VlXvV1e2oxS316vTB31Qa9nrAbjlywtE5E+4jMVX4W5sXglc2lFm+rxVODtVNUdEjgO6i8g7qrpFXHbuRSJSpqo/EZHduFVoqxpu1XQEltylmURkAXClemn8vV+Qh1R1glRJ/NHKPh6u47Cq6uWtbbuOvrrjZn8AvlAfUw6LyJe4JZGvaGVClMWqOtbHPtok2Y73R/5z4IVw38EWkRSq3JRRn9Nji8h7uIv+3wPdcMs9p6jqdD/7iRQRiVLVMp/aepi6S56E43fxF8BkXIA0XER6A8+p6oxG3tqcPibhsvGBS+4yz6+2a/TzDG7J7cWqOtYLBD/TMCb3MeElIsfg9jW9gftbuMv7/CNV/b8ar+1wyzurEpGTcTcRLwWuwZ3HLlSXbbcHLrvzh6q6NXKj9J+4vdIxuH2bz3uB3gm4oOZzVf1TRAcYQeKKmB8DnKOqn4pIT1y9vkuBLcAjqrokgkNsMhFJB36Oq1N3Jy5JzSnAc7igfqe4jNavAT9Q1b9GaqzGfxb4NZMX6P0HN4sluNmF7wJLgJNV9dkIDq9ZRPbXphusqr8Sl3K9p/pUm05EvlTVqRLGTJhtRUTycOv6y4AiKksgpPjYx9W4tOBFuMQxFX0M9qsPr59E3P67AO7/PxV4siMt4RCRb6vqE1JPsiD1qY6fNwNbIQ6X3nqL+lfrsmpf83F3lOdW+X1ZqK0ssyEij6jqpd7nl6jqo60daxP6nK2qkzvD735XVnETRUSm4WaA3sHtaZuJS2KRo5UZbwOdYRbImwn5A27P9RnesZ8BZwGXeLM9neJrrcqb0ToHtz96C26bwZWq+pm4feHn4pbrZ3fkoL4p6rtxISL/whVjP0N9zhzeFiq+Lu/a7wTcTcACdVs0zgZOB17BbWE4DjgC+I+qrojUmI3/bKlnM6nq18A4EanI4lQ1YUWrgj5pu8LqFarWpvsVLlvh//CvNt1GEZkOqLh9WDdSWUOwVaTuJDv7tfZiuY72wpWcpqofAWP9nHWti6rmS2UJjEe92Rg/C4W3hQTv37D+v6jq/6o+FpGncKnMw6HEOylXLC1K9KndqsHWjbi7+eFWIiLxVGbBHYIV+u0wRKSPqm72gr5huGRQd6nqSyIyA3fDSIHXvddLRw2E6gjiNuP2WX9XRK5R1X+q6q+938d/iMvoWBqBoYZbCJco7VFcNukngTNEZDZuJc376iWG6uyqLO/sjdvjHVDVUm/Z+j+A50Xk3BrXfx1BEHfzWlT1TW910a0iUo4L+EO4PayXACOBY33camDaCQv8WsBbBjIGiBMvqYiq+pGyPOyF1WuYql5tOtif1dPPItjXAPfi0h1vxt0tvtantk/xqZ1mE5E71ctm57PVQNj3B4grgXEVkIFLz9wH+CcucU1HMcT7d6mqPteG/Q7DlUIIh2dF5AEgzfs/uhx/krxE4u78L4C3gH4i8iRu3+qlERiHaZk/iMjvVHUx7uenDLhWRF73lrmFcEl7YkTkrx05IKgI+sQl7kgENqnqc965/TgRuVpVH1DV20Wku4a5Lm1bEJG+uFUf5cAI3P/xq7jMy5NwN397Axfgtjd8QRe7ceP9PBwFXKMu6cl04CB19fpeBh4WkbM6yuynt61ntogcpKo7vKD2BlxG9HTgx7ii7J/gfiY2W9DXOdlSz2YSkX/iZhuOBB7Crf3/SlWvCFN/YSnk7LX9JTAd+NoLADNxmRhbvU+xrYjIIGCrqhZ5j+OBHqq6Lox9ztXqCX78avcAvAQcVE/q4+tMr7ek8CDgyyrL8Bap6jg/+wknb8Z3PDAnHP8XVfrJo3rgtA24o+ZMoI/9HUuV/aqq+q4Pbe4AnvbaPM/7fL9wLFv1+u2G2z8s+Lx/2ISfN9P3S1W9UET64fYCFeH2/JR6F8K5XnDY4YhIcsVyPRE5F/gNLlnUd4BHVfXP3lLvc3Dnxf909L2LACJyOq7szQ7czb8puAv+JNzWleXAe0A0cBfw+6621E9cFstJuEQuK0RkKi4R1q2q+ob3mt6quiWS42wuETkV9399Pu6m/Auqer83i30a7kbAbzrgTKZpBpvxa77pqjre23vzSxG5m/Ck3K/wBu4PUDhU1KbrIWGoTScif8CdTAtxd//HAz9U1Sf86gO3GblqUpJy75hfy1XrEq4U+A/g9s4swv/i8FWFvQRGG3gL2AskiUjVLJ6+7r1soyW+AHj7FZ/xI9iroWpB+zZZTeAtB5yvqq+Ly3b8Y3G1oTpV2vtObhUwVUQeVdVLvHPEbcCD4lLWfxbh8bWYiAwHLhSXsGMQcBguectsEXkTeM6L8f4iImXAV9DxSlPUJK50zx9xM3lrcPu7H8MtmX8dt/IjDXhaVW8E2jSrcaRU3fvm/R8fgluhUFHjNAm4SVXfqdj32tGCPgBVfVVcVtaFwI9V9X7vqY9xNfwOxSX3MZ2YBX7NV+j9W+BNle/G1SwLl7DV2VLVJ0VkDpVL/PyuTXecqt4qIt/Cpdw/E5gF+Bn4RVVdeuMFNL7/4RKRGar6qffwwDqO+SFaVetMVuKzjyTMJTDCTVVvAW4RkZdV9fRw9VMlgMn3AphJQLgCmGTgHRHZAzyDy+jZ6qLQWkcyl3CuJPD8A5ggroTLTbi75Y9RWQ/RtGNSmRl3iIjMFZGnVPUC72beT3BLwTrkTJ8nHZfR+GxcJt0BwFfeyoelInIO8J6IlFa5OO4MpgN/VdU5IhLnbe/4NvAysBI4FpfEZ7x0kULdNWZx+wPrVfVyESkAXhVXl/L9iterTxmjI0VV3xKR44H7ROQfqpqjquXA2yLysXaQchSm5QKRHkAH9JqIpOHums3FBTRPNfSGVgpHIeeqKhJ7BHAFW/1UcWPhZNxFbDiWD+wUl3EM2L+MJRxLyiru/O3fE1L1mE/eFJGrRKSXiGRUfPjcB7hlPjtxM4tX42aVfZvpbUtVgz4RCce+z3/gbvJMwNWlW40LYHynqr9U1TG4fbC9cAH6e+HoC/d/Hk5l3sXU6cD93sVzm82emqYTkboSO+2f2fKWUg8SkRdUdTVwbUdd3llBVb/E3YBMxpWmWI7LcjjOC3qX4rZzvFV/Kx2HVCzvgL5Ad+/zYhEJquoG3Mzet4GtwHXAWV0h6INqiVyuA+4XkT+LyPdV9TrgU9wNgdiIDtJn3qqSH+K+towqxy3o6wJsxq+ZVPXX3qf/E5HXgLhwBDRSWW9LRWSSqs4NQx8/x+1f+B9uZvFhEXlOVX/jUxevichy3Czp97w9hEU+tV3hGuBJEfkb7mvYiNuj4QtxReinA5lSvXRACv5nwrzA+/eOKscUlz7aN17g+i/Cf1Ohrf0KV3fIT2XeEqDTgb+p6r9FJCz7eavYgdtLuJvwJZIJ20oCT56I3IG7mDxMXL3N6DD3aZpJROKAiSKyFLc8Pgp4V1XLxSUAuQO3JGyaiCwUkYmqOj+CQ24xb09if1V9Glzw5wW9J+KWQB+Auyl2t4h81Zn2tVWZ0XoeuF1EDvRm/Soybu/A3TCN005Wm7AppLJcxcnAS7gkP6jqZeIyOX8ETOsMezwrqMvqGYOb2Z7sDnWOr800zAK/FvBOIAPxvn8igqr6NgtQJSB7wTvkd0BW4SJgglYmRvk9MB+3L6/V1GVB+wOu1lO5t3TC12V53h3oaSKS5D3e52f7uIvVJNz/ddUZi1zcMiHfqOogP9urSdq4BEYEhCOYabMARkS+j7v4yMTtU73Sm3kIh3AH/ecBFwJXqOo2cTVC/xjmPk3zxeBmtn6EW8J+oaqGvFUtbwH/rrix2Qn+PqQD/yci5eplAlZXow7c+fZx3M3WG3H7u8ojNM5w+gI3i3WeF8TMBkIicgju+9NVrwmTceWtzsb9v18HICIDvSXOvaDj7/GsSVVfFpH3tYOWYjEtY1k9m0lEHselkp9P5YlB1cfMeCKyguoBWTxun9EIv/rw2v0A+JaqZnuP03BZno7ysx+v7QdV9Sq/263Rx2uq6utyP++P4tEi8qyqnutn24306/v3S1ztvnqFad9amxGXpvorn9vsiQtgvlbVj70A5gg/b/RU6et3uOQu831ut8Hlwqq6x8/+TMfi3ch8DngfuFlVd3ozYQer6ifeazpFwXIRORGXqfK3qvpMxQyOiHwP9/Ve3Nn3tolIH+C7uFIFnwMluIDnAlVdEMmxtbWKn2sRORSXUXu7qs7wnrseGI5LSNeh9/UZU1VXvbvTGpOB0WG+87MFiKNyWWQsrg6e33KAJSLyLm4m6Fjcmu+/gu9p3if72FZ9+oShzV7ehdE4ceUWqs0qhWMJrsf371dFYCf1lMDwu7+2ICJn1njcF/dzvUhVd7S2fS8Byj1e26eo6mv4vMdPRFJUNRdvRqxmoOZDYDYH9/stuOQFe73P04ANuKyGvpLqZTBicLOk+1Q11e++TPNVCXhigQW4IOAq4Ici8oyqLhCRhd5rO0XQB/uXtwnwW2+lzjPeU3uBEm/PW6cN+gBUdbO3EmcmcDywB3cDuNMsba2PN3O33Qv2LsDtXX0P+AyX4TwgIifhVl1cClxiQZ/pbCzwa77FQE/cJuhwaauA7EXvo8KHPrWLtyRumlam/G71RXgTzAtDmz8HfobbFH9PjecUd8EUDuH8fkWiBEa4XAEcDHzgPT4CF+gMEpFfqerjPvYVjj2EAP8FTqF6gFah1Xs8K5YQi8i/gBe1sg7VicAZrWm7gT73L4v2LrRPx9X0MxFWJeg7AZfcaRvuwvfHuIyO3xJX1+tcETm7s+35UtU3RKQcV5ZiCK5m6vnAZeqyG3Z6qlqIS+H/caTH0lbE1aK8BfhERBJwybpeBF7B5QX4N+5ccg1uv+OlHT2JkTF1saWezeQtj5yIq+tTtcj2afW9pwV9XNLQ81pHenYf+kwH+qnqQh/bnKcdqBh8Q0TkZ1US+4Srj3Mq9p40dMyHfuar6sQaxxao6gQ/+2kLIvI2cLF6ZQ9EpAduRu4CYJaqjvWxrw798ywuVf24xo6Fsf8O/f3r6KomphCXtOpfuJta+4AHcXuc7geuByYAz6vqC/U01+F5KzjOw53Hn1Z/SxmZdsZb2XIN7sb9IOBOrSzd8VNcEqPXxdW17fBlG4ypj834Nd+d4e5AVR/1si0N9w6tUNVSv/sRkQ+B03A/B3OAHSLyqfpXS+59ETkLt28wLHcYxKXw/zWuDlMUPhfwrqCqv/aC42G4ZbgVx2f52M0duJm3xo611k4ROU1VX4GwlsBoC/20eq27Hd6xPeIK1frpap/bq6ZiP2ljx1phi4j8lMo6mhfhlpX7rsYS3ABu6bLfGX1NE4nLqHyGuHp8+3A17F5X1Re95w/CLf17D/gTrqZoUdVgsbNR1XmEZ5WIaUe83AUxqrpDRGbiVulMA84WkbtU9TkRCQEPiMg13nJ+YzotC/yaSVU/Cncf3jKbR3E1AgXoJyKX+BxkAKSqaq6IfBd4TFV/UbGvwydX44o3l4tIIeEJyv6CKwy/KJwXKN736Ebcks/5uBPH5/iw1NNbcncS0KdiOa8nBQjHXcewlsBoYx+KK6tSERyf5R1LBLL96ECqZPEVkZGA31l843D1NLt7Nxcqlnqm4O++1QuAX+CWNykwi8oSIn47tcrnZbi/Zb5m9DXNMgOYCsSKyMO4IPzIiie9hC7vA/Hecsdy73inDPpMl3IAMN372xqLu3mfD4wEzhKXMf1/3o3CcGVRNqbdsMCvmURkGq5w9yhc0oIgkO9zMHM3cFzFZmsRGY4rEn+gj32Au5DthUsh/xOf2662zyeMNgKL2+AC5UbcHrgvVPVILwD4P5/a3oKrI3Uabua1Qh6uyKqvNPwlMNrStbhgb4b3+DHgf97Pw5H1vquJpJ4svvib4OVq4AdAb9z/f0Xglwv8za9OvCQxN4pIoqrm+9VuPX1dFs72TdN4yUrKgVdx56ojcEuj/yEiZ4vI17gkFr2AY3D7TY3p8LxEX/uAEG7FwUHAd1V1t7jafJd4x+NF5NGKFTDGdHa2x6+ZRGQ2biP4c7g/GhcDw1X1jgbf2Lw+FmqNmkl1HfOhn3Nwezw+UdXvi8hg4I+qepZP7QtuOdkgb6lkP6CX+phyX0Sm4JZ6fkT1PZc1E7G0tp+vVXWKiMwHpqpqsYgsUdUxPrUfBB5X1Qv9aK8Z/fpeAqMzEZFlhD+Lb0Vf16vqfWFsfzrwEJCkqv1FZAJwtap+Pwx99cXdIKsIyD8GblTVTX73ZeomIiNwafvfwe13LfZWF5yIu1n2oIj8Fjer3A+4R1Vfj9yIjfGHt33hDtxN1XTgMOC3uG0az6grXi/AbUA8cLe6zMrGdHo249cCqrqqyp3Uh0VkHu6PjF9mi8hDVN+LM9vH9gHwkoY8V+XxGtzsiV/+jrvbdhQuONuHSx7gZ/bI33rtxuFmYMNlk7dX4CXgXRHZC/hW905dgft+IhKjqiV+tdsE4SiB0Wa8vWR3AVm4mTK/lxO3RRbfCiERSdPKuprpuNpaf/ep/T/j0re/AqAuZf9hPrVd08O42aNzvMff9o4dG6b+TG09cZkLTwOerbixh1slkSkil6rqTwBEJFlV8zrznj7TNYjIkbif8wtwS8yTcddSacBa4FIR2Yo7ZyzH3RSxoM90GTbj10wiMgu3JOYhXBrsrbi0v75lRBRXW+la4BDv0MfA31W1uP53tbrPuao6KRxtVs3m53f2SBFZ7Gfmxib2eTiQCrzlZ5AmIo/hlhC/gtuDAPg/e1mjz/+o6uXhaj/cRGQVcKrfGflE5FXcks5kwpzFt0qfdWVb9S0Tpoh8qapTw/n7WKWvur6WWsdMeInIIbgSJFNxN/XSgW8Bm4ChuP1O/wHQTlKrz3RtIvITIEdV/yYicV6Sov64m9wbcKuDzsbt2z5CVddFbLDGRIDN+DXfd3B7Ja7D7b/qh7+zZHgB3j3APSLSS9umjpI0/pJmK/WWMFakEM/EzQD66Q0ROU5V3/G53f28r2GJqlYk9ghXgp/V3kcAF3C0hZtFZLz6WMajjW33O+jz/CkMbTYmWHXGxfu583MWe6O33FNFJBq3bzVcKex3i8i3cXuTwd1979SFsdsjVf1EXKHq54Hp3qzea8A4XMH2tRbwmc6gyt/OvkC0d7jYW521QUSuwF1XvQ/MBbZZ0Ge6Ipvxa+fCNBN3o6reKyIzVPVT79hvVPWnPvdzEa5O0iRcltKzgZ+qj3XpRCQPSMTNxpQSpnIOIvIycL2qbvCz3Xr6CmvSFamjjAfgZxmPNiMi9+KWtL1E9Rk5X+qPicggYKuqFnmP44Ee4bhgEJE/4sqSPOAduhrYqKo3+9R+d+Be3IoFwe39ulFVfQ/IRGQAbo/fwbgbP58BN7TF74+pTUROwv1/TPGS/FQt5G7LO02nISJHA7cDt3t7+QK4m/U9cFnAL1PVvAgO0ZiIssCvmaSN6sZV6c+3pV5V2pyvqhPDEVTW0ddI4Gjc9+n9MM3OhJ23xPcA3JK/qsswfVvyJyJjgceBDO/QLlwGviV+9eH1M09VDxBXoqKfemU8/E4e1BbEpaavSf1avuolc5pesaRXXH3NT1XVz32qFX0FcMFeRd2+d4GHvL3ExrSKiJyAy0Y7QlX3Rno8xoSDuFI+t+BK5DyrqrO94+cC3wPOtJ9/05VZ4NdM3p6isNeNq9Lf931M7lDR5lO4jKS9cUsL9z+Fu2j2LQDwlqv1oMqyYj/u+otIgwGrqs5tbR9eP0OpMX7PobiZoH/70Y/X12fAT1T1A+/xEcD/qep0v/rw2l0EHIebhf2Jqn7dUQO/cKtnr1pY9sV5bccD/dUr5eJz24OA6/FqElYcD9N+xUzgyjr66rD7STsDETkZV37ow0iPxZhwEZE+uIy2R+Hq7ZbgVhxdoKoLIjk2YyLN9vg1X5vUjfM25Q9T1b97F1FJqrrWj7ZV9QIR6Qm8jVvyFxYicj2uYPR2XA00wS378iPAuNv7Nw4XxC7w2h+Py4B6sA99gFsacoeqLqp6UET24Or4+Rb4AYkVQR+AqlYUIvfbL3H/9594Qd9g4Jsw9BM2InKrqv5BRO7D20Nalare4FNXO0XkNPVqPIlLE77Lp7arEZHTcNnoYoBBIjIR+JWPgdlLuJ/XV/F/r21NL+OSUr1HZf1DE2HqlWuw5Z2mM1PVzSLyB2AmLpPxHuBb4bihZkxHY4Ff892KSygStrpxIvILXDAzApcCPRqXjnhGQ+9rDlXdBkzwlq4N9w6vUNVSv/rAJY8YEY49RKp6JICIvABMqgjMvOWSd/rYVY+aQZ/X/yIRGehjPwBrRORnuOWe4FLgr/GzA28Gtl/V2T31v4xHW6hYMux7mZMargGeFJH7cQHmJlztznD4Ba7I8IcAqjrfm6XzS5Gq/tXH9hqSoKq3tVFfppks6DOdnaoW4m4+fRzpsRjTnljg13xtUTfuW7j9ZHMBVHWLiPie5dErS/AYrtaNAP1E5BJVneVTFxuBHJ/aqs+IqoGZqi4WkVE+tp/WwHPxPvYDcDluNq4iMcnH3jHfqKsXeAGupluHpaqvev8+GuZ+VgPTwp1wx1Oqqjki1RLs+nmBfq93U+kdqt+08mVZdA2vichJqvpGGNo2xhhjTAtY4Nd8vTX8deNKvGxrFWndw7HcD1xq4+Mqlj+IyHBc+vUDW9OoiFRkh1wDfCgirxOm2VFgodQudu/nGv7ZInKlqv6r6kEvMcocH/vB23B+g4ikAqEwZh77VET+BjxD9UQ14QgAwkpEJgM/oTLZEgB+7VcUkR64Jb29VfVEERkNHOzn3s4qlojIhbiyDsOAG3DZMP0yDleO5igql3qq99gXXpZdxd1I+rGIFANlFX2FKwmWMcYYYxpnyV2ayVs3/p6Gt27cj4BhwLHA73CzPv9V1ft87qdWQg8/knx4swr1UVX9VWvar9FXHC5T16G4i805wCBVvcKn9nsAL+I2h1cEepNxs73f8pbM+kJEpuCKKVfM7uYAl6uqrwGmiHxQx2FVVd8CgLYiIitwGdwWUWXfmqqu96n9N3HLrX+iqhNEJAqYp6rj/Gi/Rl8JuCD2OO/Q28Cv1dX19KP9VcDoigylxhhjjOlaLPBrphp148J2J1tEjsVdAArwtqq+62f7Xh8P4xIvVJ0tC/qYCv8crVGzr65jPvRzAHAhcC5ulvF/qvo3n/s4EqiY6V2iqjP9bN/rYyFwrap+7D0+BPi7Zdusn4h8oqqHhKHdKFUtE5GvVXVK1bIqdWX69KnPsP6+iMhLwFWqusOP9prR752qemdb9mmMMcaY2izw68JEJBa4Fqi4cP4YF2j4NcNQq06gX7UDvWWpF3gfu3DLFn+kqgNa23ak1FWzMRy1Ftt4+WJYiSvWewHwPj4WcK/4vosrdn8W8K73eBpwl6oe3pr2G+qzsWOtaP9DXNbbr6n+vQpbZl+v37DXCzXGGGNM42yPXyuE6062iJwJ3AVk4Wb8fC8S72V3XKCqI3F7/XwjIicCJwF9RKRqFsEUKmdJW2s5LlA9RVVXef3+0Ke2I+UjEXkAt89SgfNweyQnga978B7BW77oPV6JC5w7XOAHXAaMxGW+rbpvrVWBH+53DuAm4BVgiIh8CmTi6kH5po1+X8BlDY0EafwlxhhjjAk3m/FrhXDdyfb24pyqqssafXHr+nkZuF59KKheo90JwERc8Pob73AZrp7fh14Sk9b2cQZwPq7ExVvA08BDqupn+vs2Vc/euwq+7cFry+WL4SYiK1R1RBja3UTlDZEAEIsLYIqBcp/Lt1T8vvwK+HmVp/KAD3z6fQniliiPbG1bTezvTOB1VS0WkYCqhrtuoDHGGGMaYTN+rROuO9nbwx30edJxmQS/onp2x9Yu/VqK2y8YQ2U5gv64WabXWtk2AKr6EvCSl/H0dOAHQJaI/AN4MZzJd8KlojZhG8gXkW54pQK85YvhLrsRLp+JyGhVXepzu0Egidq/4wk+94OqLgAWiMh/vf58r6vplfFYISL9/b7RU49TgT+LyCzgGRF5S1X9nL00xhhjTDPZjF8rhOtOtojcC/QEXsLHfUt19FPnPiVV/aiV7f4Zd9F8U0VJAhFJAf4EFKrqja1pv4F+04FzgPNU9ehw9BFOInIjLjjOA/4FTAJu9zuI9ZaO3odLVrMYb/miqi70s5+2ICLLgCHAWtzvSsWy6NZmpm3zfWl11dUELlGf6mp6QdgBQNUbPaqqp/vRfh39RQMn4pYsH4LbJ/ndcPRljDHGmMZZ4NdMIvIocKOqZnuP04G7/cqE6bX5cB2H1cdsm3HANcBQXBr8f/t5N15EvgGGa40fLm+52XJVHeZXX52JiCzwSgYcj/v/+SnweJiWE0cBI3ABhm8zS21JRARXxqNW6YbWlnOoK9FOuInIHOBCrVFXU1VbVVezSvtVb/RUfO/OV9UxfrRfT5/RwAm4vZiHqWr3cPVljDHGmIbZUs/mG18R9IEruu2VE/CNql7mZ3t1eBQoxSVHOREYDfg5C6c1gz7vYLl4RelNnSqWFZ4EPKaqS7zgxp/G3b6rugwXEd9nlMNNVVVE7g9HTT0gEjPG0RVBH4CqrvQCJ1+o6kdVSp+cg5sl/adf7VflJaw5DzgC+BB4CFduxRhjjDERYoFf8wVEJL0i4YKIZODT91FEblXVP4jIfXj7r6pS1Rv86AdXxHmc1+e/cUu//LRURC5W1ceqHhSRb+OycZq6zRGRd4BBwB0ikkyVouQ+OLWB5/zIhBkJc0Vkiqp+7WejqrrHz/aaaI6IPET1upqzW9toPaVPJMx7Si/2+rnar/IwxhhjjGkdW+rZTCJyMfBjoKKo8jnAb1X1cR/aPlVVXxWRS+p6XlUfbW0fXj/V9i/5vZ9JRPrggohCYI53eDIQD3xLVTf71VdnIiIBXHbHNaqa7SVg6dMR9961FRFZjluyvB63b82XPX6REK66miIS8tq6okrpkzWqOrg17RpjjDGmY7HArwW8gtcVqfVnhiGjYFiJSDmVyR0EF5AV4HO9QBE5CqjYP7RUVd/3o93OzAuaB1BlFtnH5B43NfS8nyUK2oqIDKjreGv3+LW1cJZbaMvSJyLyiaoeIiJ5VF+14HstUmOMMcY0jy31bJkMIF9VHxaRTBEZpKpr/WrcW5r1I2Ag1QMAX+q4qWrQj3aa0M9MYGZb9NUZiMhduH1RS4Fy77ACvgR+QLL37whgCq4wObgloH4v920TFQGeiGQBcREeTouFs9xCW5Y+UdVDvH+TG3utMcYYY9qWzfg1k4j8ArdscYSqDheR3sBzqjrDxz4W4JIuzKEyAEBV59T7JtPhicgKXPKgsO6J8tL6n1yl1EYyrtj2YeHsNxxE5DTgbqA3sAM3W7osnJkqw6Wecgt+1NWsq6+wlT5p62LxxhhjjGkam/Frvm/hLs7mAqjqFu/C2U9lqvoPn9s07d8aIJoqtRvDpAdQUuVxiXesI/o1MA14T1UPEJEjgW9HeEwt9bO26shLTvWg9+F3221dLN4YY4wxTWCBX/OVeGnkFcBbPuULL0MowKsi8n3gRaoXcI9EpkHTdgqA+SLyPtX/3/3K5lrhMeArEXnRe3wGrsRHR1SqqrtFJCAiAVX9QET+EulBNUe462pGSDqwRETCPntpjDHGmKaxwK/5nhWRB4A0EbkSuBxXo8oPc3B7uipqt91S5TkFLAtf5/YKlfvuwkZVfysib1GZPfIyVZ0X7n7DJFtEknD7IJ8UkR1UCTQ6iHDX1YyENpu9NMYYY0zT2B6/FhCRY4HjcAHa26r6boSHZEyzePuwelA9eVCHWZZXsYzQm3EvBAK4unepwJOqujuiA2wGEVlUpa5mFPCVn+VV2lInnb00xhhjOgUL/JpJRK5Q1X9XeRwEfqqqv/Sxj2txF6/Z3uN04AJV/btffZj2R0SGAb/Dzfjsz1Dpd701Ebke+AWwHZc8qMPVvqtae1JE/qeqZ0V6TC0V7rqabUlEnqH67OV6Ve3os5fGGGNMp2CBXzOJyH+BNOAKXFmHR4CPVPVHPvYxX1Un1jg2T1UP8KsP0/6IyCe4gOzPuBILlwEBVf25z/2sAqZ2pFmxmqr+PnT03422qqvZFjrT7KUxxhjT2dgev2ZS1QtF5DzcMqZ84EJV/dTnboIiIupF5d6sYozPfZj2J15V3/f+79cDd4rIHMDXwA/YCOT43GZb03o+73Daqq5mGymt+ERVy0SkodcaY4wxpg1Z4NdM3nK8G4H/AaOA73gzDgU+dvMW8IyXRAbgau+Y6dyKRSQAfCMi1wGbgaQw9LMG+FBEXqd69tB7wtBXuEwQkVy8GTLvc+iAs2SdzIQa/xfxVf6f7P/FGGOMiSBb6tlMIrIcuLZiZga4Cbjcz4LR3sX/1UBFYeV3gYdUtbz+d5mOTkSmAMtwS4l/DaQAf1TVL3zu5xd1Hfdzn6oxxhhjjGlfLPBrJhFJUdXcGseGq+rKSI3JdHzect67/NwraowxxhhjTIVApAfQUYjIrQCqmisi59R4+lKf+xomIs+LyFIRWVPx4Wcfpv0QkShvNveQRl/sT3+ZIvJHEXlDRGZWfLRF38YYY4wxJjIs8Gu686t8fkeN507wua+HgX8AZcCRwGPAEz73YdqPr7x/54nIKyLyHRE5s+IjDP09CSwHBgG/BNYBX4ehH2OMMcYY005Y4Nd0Us/ndT1urXhVfR+3FHe9qt4JnOxzH6b9iQN2A0cBp+BKOpwShn66ebUoS1X1I1W93OvTGGOMMcZ0UpbVs+kaSh/v90bJtsruaNqHLBG5CViM+1mqeiMhHJtwK1LubxWRk4EtuJqUxhhjjDGmk7LAr+kaSh8f53NfNwIJwA247I5HAZf43IdpP4K4wL6umeNwBH6/EZFU4GbgPlz20B+GoR9jjDHGGNNOWFZPYyJMROaq6qRIj8MYY4wxxnReNuPXjojIKw09r6qntdVYTJvye49o3Z2I3EcDM4iqekNbjMMYY4wxxrQ9C/zal4OBjcBTwJe0UUBgIu7oNupndpXPfwnUWcjdGGOMMcZ0PrbUsx3xingfC1wAjAdeB55S1SURHZjpdERknqoeEOlxGGOMMcaYtmHlHNoRVS1X1bdU9RJgGrAK+NDL7GmMn+yOjzHGGGNMF2JLPdsZEYnF1ey7ABgI/BV4MZJjMsYYY4wxxnRsttSzHRGRx4CxwBvA06q6OMJDMp2IiORROdOXABRUPAWoqqZEZGDGGGOMMSbsLPBrR0QkBOR7D6v+x9iFuTHGGGOMMabFLPAzxhhjjDHGmE7OkrsYY4wxxhhjTCfXIZK7dO/eXQcOHBjpYRhjjAmzOXPm7FLVzEiPo6Ow86MxxnQdrT1HdojAb+DAgcyePbvxFxpjjOnQRGR9pMfQkdj50Rhjuo7WniNtqacxxhhjjDHGdHIW+BljjDHGGGNMJ2eBnzHGGGOMMcZ0chb4GWOMMcYYY0wnZ4GfMcYYY4wxxnRyFvgZY4wxxhhjTCdngZ8xxhhjjDHGdHIW+BljjDHGGGNMJ2eBnzHGGGOMMcZ0chb4GWOMMcYYY0wnZ4GfMcYYY4wxxnRyFvgZY4wxxhhjTCdngZ8xxhhjjDHGdHIW+BljjDHGGGNMJ2eBnzHGGGOMMcZ0chb4GWOMMcYYY0wnZ4GfMcYYY4wxxnRyFvgZY4wxxhhjTCcX1sBPRG4UkcUiskREfuAdyxCRd0XkG+/f9HCOwRhjjGlv7PxojDGmrUWFq2ERGQtcCRwElABvichrwFXA+6r6exG5HbgduC1c42iJvfklfP/JuXy+ZneDr4sSEIHSUPXjY3qn8ML3phMbHQzjKNuZZa/BomchuRdMvx5Wvg2rZ0LWaJhxA8Qmw76d8Nm9sHcdjDodxp8D2Rvhs/tg33aYcD6MODHSX0mbWrFnBU8se4KyUBknDzqZ2dtnsy53HUf0O4Izhp4BwK7CXdw37z5mbZxFaaiU8Znj+fHUH9M3uW9kB2+MaZGOfH7syMpDyqOfreODFTvYV1RGVkoso3unsGpHPsWl5ewrLmVrTjH9MxL43hFDmDa4GwCvL9zKS/M3sWtfCclxUUzom8bOvGLyS8q5YEo/pg/tXquvRZtyeOSzdSjKpdMHMr5vGp+u2slPXlrMztxieqTEMbB7AvnFZYQUhmYl891DBzEkM6mtvy2mK8jbBp/eCzmbYOxZ0G0IfPFPCJXCgZfDazfCrpUgQYjPgJh4QCB3s/s3qQeEyqG8CGJTobwYCrPdv6rufQnp0G8a7P4GyksgOh7ydkBaP5hwAaybBTHJrr2SXBh3Low6JbLfly5IVDU8DYucA5ygqld4j38GFANXAEeo6lYR6QV8qKojGmpr8uTJOnv27LCMsy6H/eEDNuwpaFUbAzPi+fDWo3waUTu37FV45tuVj+PToXBv5eNhx8GFz8IDh8K2RZXHT/kLfHIPZG+oPHbB010m+NtRsIPTXjqN/NJ8AARBqfx9vP2g27lw5IWc+cqZrMpeVe29abFpvHv2u8RFxbXpmI0JNxGZo6qTIz2OcOrI58eO7P/eWMaDs9Y06bUBgZeuncGanfn84Jn5Db7uuWsO5sABGfuPbdhdwHF/+Ygi765wXHSA/145lbP+8TkNXXKlJ0Tz4S1Hkhof3aQxGtMkoRD8faoL7CpExUJZceTGVOHcx2H0aZEeRYfS2nNkOJd6LgYOFZFuIpIAnAT0A3qo6lbvNduAHmEcQ7Ot2bmv1UEfwLo9hT6MpoNY8HT1x1WDPoBv3oENn1cP+gC+/nf1oA9g4TP+j6+dmrlh5v6gD6gW9AG8uvpVVuxdUSvoA8guzuarbV+FfYzGmLDokOfHju6FuZub/NqQwivzt/DCvIbfE1J4ef6WasfeXLx1f9AHUFQa4q43VzQY9AHsLSjlwxU7mjxGY5pky9zqQR+0j6APutQ1X3sRtsBPVZcBdwHvAG8B84HyGq9RoM4/hSJylYjMFpHZO3fuDNcwa0lPiEGk9e10qaw5yT0bfj42BVL6uqUA1d7Xq/ZrkxppqxPpHl97eVBVmfGZZMRlINT9A9nY+40x7VNHPT92dJnJsc16fVZKLFlNeE/N12Sl1H5Pv4z4JvXZ3DEa06jETKjnOiLikuzeVlsLa3yiqv9W1QNV9TBgL7AS2O4tYcH7t87bW6r6oKpOVtXJmZmZ4RxmNemJMVx12OBWt/O9I1rfRocx40ZI7V/5ePS33BpwcMHesb+E9P5w2C3s/+OT1AOO/w1MubLyfWkD3P7ALuKIfkcwo8+M/Y97JfYiIO5XMj02nWsPuJashCyuHH9lrfeeMPAERncb3WZjNcb4qyOeHzu6H580koSY6jcgowJ1XxCP7pXM+Qf157ojh9IzJa7e94zsmcy3pw2o9vxJ43pxsLc/EGDqoAx++61x9EtvOPg7ucb7jPFF+gCXa6FCcm/oP73ycVvccK9rW0pqfzjkB+Hv21QTtj1+ACKSpao7RKQ/7s7mNOAnwO4qm9czVPXWhtqJxB6GNTv38beZ3/DN9n3ExwSICgTomxbPjn1F7MovISspjjF9UkmNi2LWN7soDYVIigkSFQxy2/EjGNjVNmiXlcDGL9wfkMzhUJwHm76G7iMgtU/l6/asccs7+02DaO8Pwc4VLrlL/4Mh2PX2NizZtYTSUCkTMiewJX8L63PXc0DWAcRHVV4kbMjdwFfbviKvJI+Dex/MyIyRERyxMeHTFfb4Qcc+P3ZkOQWlLNiUTVx0gLKQMql/Ogs35ZAUG6SwNMSG3fn0zUjgwP7pBLwAr7isnNnr9hITFaCwpJyJ/dPYtKeQfcVlTB5Q+bqa5m/MRlU5oH9lctY3F21l8eZcpg7KICs1ll15xYgI6QkxjO6d0ibfA9NF7VrlkrX0n+b2+G2eC6Ey6DsF9qyFt25zAWFSFgSioPswt5UnNtkdL9wFRTmQOgCKcyF/J2Svd0lfEjLc9d/o02H9p1BWCD3Hw8q3oN9U6DO58hpRBPK2uuvAqJhIf1c6nNaeI8Md+H0MdANKgZtU9X0R6QY8C/QH1gPnquqehtqxE5sxxnQNXSjws/OjMcaYZmntOTJs5RwAVPXQOo7tBo4OZ7/GGGNMe2bnR2OMMW2tS+UgMcYYY4wxxpiuyAI/Y4wxxhhjjOnkLPAzxhhjjDHGmE7OAj9jjDHGGGOM6eQs8DPGGGOMMcaYTi6sWT07ulcWbOGhj9cgIgzPSmLR5hzSEqK56dgRHDQoA4C3l2zjHx+upjykfPfQQZw+sU8jrRpjjDGmI3tj0VYe+Gg1Clx56GBOndA70kMypmWK8+Ddn8PaWdBrIhz3G0jpVfdr5zwKX/8LohPh8Ftg6DFtOlTTehb41WPehr3c+PQ8KsocLtiYvf+5Sx/+is9uP4odecV8/8m5lIfci258ej590xM4cEB6HS0aY4wxpqNbsiWH6/47F+/Uzw1Pz2NAtwTG902L6LiMaZE3boUF/3Wf714Fedvgstdrv+6b9+DVGyofP3UBXD8X0vq1zTiNL2ypZz0+XLGT+mrbF5SU88WaPcxauXN/0FfhoxU72mB0xhhjjImEj1bupOqpXxU+WrEzcgMypjW+eaf64/WfQElB468rL4E1H4ZtWCY8LPCrx4ieyfU+JwLDeyQxvEft1wyr45gxxhhjOocRdu43nUnWqOqP0wdCdHzjr6vvmGnXLPCrxwljenL+lH4EA0JQoG+a+yWIiw5w2wkjGZyZxKHDunPp9IFEBYSAwLmT+3LSuHrWRRtjjDGmwztqZBbfmTbAXR8EhAsO6s9xo3tEeljGtMxJf4SMIe7z5F5w2t/cDEdNEy+CMWcCAsEYOPRm6Du5TYdqWk+0vvWM7cjkyZN19uzZEek7u6AEQUhNiGZnXjEJMUESY6tvjcwpLCUUUtITYyIyRmOM6SxEZI6q2tVEE0Xy/NjV5RSUoihpCXbuNx2cKuRuhqSeEGwk/Uf+Lhf4xaW0zdhMNa09R1pyl0ZU/YOemRxb52uWbsllxbZcDhnWnaFZttzDGGOM6exSE6IjPQRjWmf9Z7B1IQw+vOnLNhO7h3dMJqws8Gul37+5nH9+tBqAYEC4/8JJnDC2Z4RHZYwxxhhjTD1m/hZm/cF9LgE4698w9szIjsmEne3xa4X84jL+88na/Y/LQ8rfP1wVwREZY4wxxhjTgNJC+Oy+yscago/vjtx4TJuxwK8VylUpr7FHsqQsFKHRGGOMMcYY0wgNQais+rGy4siMxbQpC/xaISUumrMn9a127PIZgyI0GmOMMcYYYxoRkwiTLq5+bNr3IjMW06Zsj18r/d+Z45g+tBvLt+Vx2LBMDh7SLdJDMsYYY4wxpn4n/QkGTIdti2DIkTD4iEiPyLQBC/x8cPrEPpwe6UEYY4wxplUqSlxJXXXMjOlMAgEYd7b7MF2GBX4ttHrnPm56dgELNmZzQP80/nzuRAZ2T4z0sIwxxhjTAg99vIb7Zq6itDzEJdMHcuvxIywANMZ0KrbHr4Vuec4FfQDzNmRz6/MLIzsgY4wxxrTIgo3Z/Ob1ZeQUllJQUs4/PlzNW4u3RXpYxhjjKwv8Wmi+F/TV99gYY4wxHcO8DXtrHbPzujGms7HAr4WmDMyo9vigQRn1vNIYY4wx7dmUOs7hdl43xnQ2Fvi10N3nTuCQod1JiAly2PBM/nD2+EgPyRhjjDEtMKZ3KnedNY4+afFkJsdy6wkjOHpUj0gPyxhjfGXJXVqob3oCT3x3aqSHYYwxxhgfnDelP+dN6R/pYRhjTNhY4NeID1bs4P1l2xncPZHoYIAv1uymqCzEmF4pXDRtAD1S4iI9RGOMMca0oZKyEM/O3sjybbkcOiyT48f0jPSQjGkbZcUw9zHYsQyGHQcjTqj+fEkBzHkE9qyGkae4GoGm3bDArwHPfr2RW/9Xd7bO95ft4NnZm3jv5sNJirVvozHGGNNV3Pr8Al6avwWAJ77YwJ2njubSGYMiPCpj2sALV8LSl93ns/8Np/wZJl9e+fzTF8KaD9znXz8EZ/3bagW2I7bHrwFPfrm+wee35Rbx3tLtbTQaY4wxxkRablEpryzYUu3YE19uiNBojGlD+btg6SvVj83+T+Xne9ZUBn37n384/OMyTWaBXwMSmzCTZ7N9xhhjTNcRHQgQGxWsdqwp1wvGdHjBGPdRVUxy5efRCSA1QovYpPCPyzSZBX4NuP6oYcRG1f8tmjIwnSNGZLbhiIwxxhgTSfExQa47auj+x9FB4QfHDIvgiIxpI3EpcMgPKh8HY+HwWysfJ/eEg66ufBydCIfe3GbDM40TVY30GBo1efJknT17dkT63p5bxCff7GJoVhKx0QHmrs+mrDxEv4wEDhueSTAgERmXMcZ0RiIyR1UnR3ocHUUkz49d3eLNOSzflsf0Id3onRYf6eEY03a2zIMdy2Hw4ZDSu/bzG792yV2GHAVJWW0/vk6stedIW5tQj6LScjbsKWBQ90QGZyaiKFnJcUwbnEG/jATW7sqnpKyc5VvzkIAwsV8aAKrK4i25lJSGmNg/zQLDmkLlsGslpPWHmMRIj8YYY0wXtGF3ATmFJXRLim00aAuFlNU799ErLb7a9o6xfVIZ2ye1Rf2Xe232SYu3ZaKmbZQWuT14cWlQVgjdhrjj2RsgEA0pvWDXN5DQDRIy3HO5WyBU5q7Zqup9gPuoT78p7qOm/F1QlFPZt2lz9temDh+t3MmNT88ju6CUgECoxqRodFAoLVcEqHiqV2ocD35nMtc8MZvN2UUApMZH88zV0xjZM6VNx99u7VgG/z3X/ZGJSYbT/wZjzoj0qIwxxnQRhSXlXPnYbD5ZtWv/sdMn9uaecyfWeaN23a58Lnvka9buyichJsivTx/LWQf2bdUYVu3I4/JHZrNhTwFJsVH87sxxnDqhjlkTY/yydhY8dykU7K481m+aW7r5zTuAuGCvYLfbw3fEHS5InPcEoK4sw9kPQ1RMPR00wczfwCd/doFk/+lw4dMQ17IbJ6blbI9fDarKj19YRHZBKVA76AMoLXcHqz61NaeIG56auz/oA8gpLOUXLy8J53A7lnd+6oI+gJI8eO2HUFYS2TEZY4zpMp78cn21oA/g5flbeHvJtjpf/4e3l7N2Vz4ABSXl/OKVJRSUlLVqDL97Yzkb9hQAsK+4jJ++tJjisvJWtWlMg177YfWgD2DjF17QB6CVz5eXwPu/gnmPs/9Kd/lrsOi5lve/YxnM+qML+gA2fAZf/LPl7ZkWs8CvhpLyEFtyClv03h15xbWOVZwwDO7uUVWFe6AoOyJDMcYY0/Ws311Q5/H6ztXrdlV//b7iMnbWca5vjnW7q/eVU1jK3vzSVrVpTL1UYc/a5r6p9qE9q1s+hprXf61tz7SYBX41xEYFOWJ4yzJ1Hl7H+04e36u1Q+o8Rp5c/XHfg2zTrzHGmDZz3JgetY4FBY4ZVft4Xa8f2TOZAd1atz/9uDE9qz2e0DeVnqlxrWrTmHqJwMiT6nuy7sPxGdXLNkgARpxc92ubYuAhtZd1jjyl5e2ZFrM9fnX483kT+dM7K1i4KYfoYIBVO/ZRHlJ6psaSHBdNUmwU2QWllHqzg0ERLpo2gJuOGcZfZ67i8c/XUx5STh7fiztOHBXpL6f9OOrnrsbLN+9Cj9Fw1M8iPSJjjDFdyKHDMrn3/In8/YPV7Mgrol96AjcdN5wRPZPrfP11Rw4lKiC8u2wHQzITufm4Ea0ew03HDicmGODDFTsY3iOZHx3f+jaNadDp90NyL1jzkVvKmdgdDrzUBWNfPgBRsdBtKGye65K8HHEH7NsBn97rXj/te9D3wJb3H5cKF78CH/3BLSmd9B0YfZpvX55pOivnYIwxpt2wcg7NY+dHY4zpOqycQ5jlFJRy7/vfsGRLDocM7U6vtDhemreFzORYooPCu0u3Excd5PYTRzJtcDe+98Qcvtmxj2FZSfzj2wfSI8WWbxhjjDHtxfbcIv7y3jes25XPcWN6cOn0gYhY6SXTxexYDh//CXK3QjDaJV4ZfKRbGrroeSjOhcyRrkB7v4Oa1/aq9+DLB127M25s/vtN2NiMXyMu/s9XzFq5s0mvzUyOrbbpu1dqHJ/fcXS4hmaMMZ2Ozfg1j834Nd8Jf5nF8m15+x//5KRRXHnY4AiOyJg2VpIPfxkPBbsaf21UPFz3NaT1a1rbW+bBv44GLW/Z+02DWnuOtOQuDcgrKm1y0AfUyvS1NaeIrS3MEGqMMcYYf63eua9a0Afw2qKtERqNMRGy7pOmBX3gir2vfKvpbS97tTLoa8n7TVhZ4NeA+Ogg3ZOaXqyyZu3XYEBIT2hFsUtjjDHG+CYzOZbYqOqXPn3T4yM0GmMiJK1/M18/oHVtN7c/EzYW+DUgKhjgl6eNJT46CEBGYgwDvTTOAkQHKyO9YVlJ/ODo4dXef+PRQ4nz3muMMcaYyEqJi+anJ48iJuguf/qkxXPzscMbeZcxnUzWKJh+gyvTAOwv65DQHRK6VX/tuHNg6DFNb3v8+TDkqMrHY8+Goce2arjGP7bHrwlyCktZuyufUb2SiQkGWLo1l4zEGHqmxPHW4m10S4rhoEHuF2VnXhEfrdjJYSMyyUq2xC7GGNMctseveSJ9fuyodu8rZnN2IaN7pRAVtHvgpovK2QQFeyClD2Svgx7j3PHti6C8zJV96DakZW3vWO6Su7T0/aZOltUzjDbuKeCprzawPbeIIZlJJMYEGdYjmX7p8Tz0yToyEmI4c1IfXp6/mQ9X7GRfURkZSTGM6pVCYox9a40xkVGUX8rmFXtJ65FAtz5JkR6OMe1Ot6RYuiXFVju2euc+VmzL46BBGXSv8VxzhULK52t2U1oe4pCh3S24NJFXlAtrP4LUvtD7AHcstS/EJrv6fqFSyNkMfadA3jZI6uGCtvJS93wwCgYeBoEAqLp9gqWFMPgIiKqyramsGJa+AjuXQ3JPV7cvcySs+RDSB0CvCZH46o3HopN6PDd7I7c8v7DasT+8vYKLDx7Ak19uoDzkZkrvfHVJne/vnhTDs1cfzOBMu+gyxrSdbWtyeOXe+ZQWu831U04eyEGnWsZCYxryr1lr+O0bywCIiw7wn0umMH1o9xa1VVxWzoX/+pI56/cCMLJnMs9/bzpJsXbJZSJkx3J4+EQo3OMeT7kSTv4TbF0Ij54CRTlVXiyAtxpwzJmwcwXs8K51+02D77wET53ngkiAbsPgincgIQPyd8E/D4G8GgmTgtEugASYeg2ceFeYvlDTGLsFVY+KE0BNj3++fn/Q15Bd+0p44KM1fg/LGGMa9PXra/cHfQBz3l5PUX5pBEdkTPtWVFrOn99bWeVxiLvfXdnAOxr29pLt+4M+gOXb8nhx7qZWjdGYVvnknsqgD+Drh2DvOpj1xxpBH+wP+gCWvFAZ9AFs/AI+/F1l0Aew+xuY+6j7fPbDtYM+qAz6AL58ALI3tvQrMa1kgV8dQiFlX1FZnc81Z0dkdmGJPwMyxpgmKsqv/rcrVKbVAkFjTHXFpSEKS6v/jmQXtPz8nVPHe/cW2M0XE0GFe2scUCjMruN4E+TvqL/9JrWnUJTd/H6NLyzwq0MgIJwzuW+dz43smdykNkTgvClWrNIY07ZGz+hV7XG/UekkZ1iiKWPqk5oQzQljelY7dv6UlqefP35sT1Ljo/c/jo8OctqE3i1uz5hWO+A71R/3muA+Jl3S8PvSBkB0QuXjuDQ49GZIzKw8FoyF8ee5zyecD9JINvvek6DnuCYP3fjLsnrWo6w8xIOz1vDkl+vJLSqjW2IMZ07qy3cPHcSrC7byr4/XkBgT5OTxvXhz0TY2ZRdSWl5OQnQUE/ql8e1pA5jRwv0BxhjTGmvm7WTtgp2k9Uxg3BF9iYnrOHuLLKtn81hWT38UlZbz+OfrWb4tj8OGd+f0iX1a1d7aXfk8/vl6ykIhLpo6gBFNvGlsTNiseg8Wvwhp/eCgq9yePICVb8PC5yF/u0vokjUa9qx2iVkOutrN8M1+2O3Tm/Jdl/Bl73r46kEoLXDBY++Jlf1sngvv3Ql71kF8Cgw+ygV6az509fymXgXx6W3/9XcSrT1HWuBnjDGm3bDAr3ns/GiMMV2HlXMIowc+Ws1f3vuGotJyspJjCaHkFJRSUl49WA4I1JXv5cAB6Tx15TRiorrQitqCPfDGLW7jb68JcNKfIGNQpEdljDHG8PL8zdw3cxUlZSEunT6Qyw+pPD9tzi7k5y8tZsGmbA4alMHPTxnNvz5eywtzN1FcWk5pSAkGhMykWIrLQmQkxnDzcSM4dnQPAGav28Nv31jG5r2FnDqhN7efOJLoBso4zFq5k5++tIgt2UXExwS5+rDBXHfUsLB/D0wXUlYCL1wFy19zj0edCt96oLL8QqgcZv4aFjwDSVlw7K/g8/vgm/ddcs+oWFfe4cQ/QtbIlo3hf1fC4udBQ650RN+DYN3HoOUw5Bi46FlfvlTTNDbjV4+lW3I46a+ftLqdi6b257ff6kJrmZ+/HBb/r/Jx70lw1QeRG48xpkOxGb/msRm/plu5PY8T/jKr2o3aRy6bwhEjsgA494HP+WptZebDoVlJrNqxr8E2o4PCrFuPJC0+hoN//z7ZVZK43HL8CK49cmid79uTX8LBv3uP4rLq12D3XXAAp9p+QOOXmb+FWX+ofuzw2+HIO9znXz4Ab95a+Vwg2tXzq6nbULhutktg0Rxf/Qve+FHDrznkJjjmF81rtwtr7TmyC01FNc/7y+rIWtQCH67Y6Us7HcbaWdUfb5kLxXmRGYsxxhjj+WLN7lqrcz5bvRtw+/qrBn0Aa3fmN9pmabny1do9LN2aUy3oc23vqvd9c9fvrRX0NfYeY5pt5dt1HHur8vM1H1V/rq6gD2D3Ksjd3Pz+l77c+Gu+eaf57ZoWs8CvHgcNyvClnfF9U31pp8PoNaH644whEGNF7I0xxkTWmN61z8dj+7hjUcFArazdWSmxTW53aGYycdHVL6nG1tFfhdG9UwjUMXlSMR5jfNHvoIaPVU3KAiD1hAVJPd1Hcw2Y3vhrek9qfrumxSzwq8fUwd04d3JfKv4ux0UFmv3N6pUax11nj/d7aO3bSX+q/CXuNhTO/FfzlwYYY4wxPjtwQDo/Om44iTFBYqICXDp9IKeMqyx/8qdzJjA0y92oHNM7hQe/cyDHjHL796qexRJiggQFUuKiuPPU0QzNSiI1IZq7z5lIZnIsInDMqB5cd1TdyzwBeqfF87szxxHvBYsCnH1gX86bbGWgjI+O/hn0mlj5uNdEOOqnlY8Pvg5Gn+ECvoRucOq90H1E9TbSBsBZ/4JgC9KCHH579cBOApA+uPJx5kg4+Z7mt2tazPb4NaK4tJyCknLSE2MoKi0nKiDkFJZSUlpOqYbolhADEkCAPQVFxEZFERAhIJCe2LS7hZ1ScZ7bxGuMMc1ge/yax/b4NV9peYjykBIXXXe9sX3FZSTFVl7kFpa4c39pKISqC/yKy0JEBYSoGslbykNKSVmI+JhGaplVeX1hSRlRwUC94zGm1YrzQIG4eq7LSgpcIpeA9zNYuBeCcS4BS0xi62/gF+dBaTHEpbjEMiUFUF4C8Wmta7cLatdZPUXkh8B3cT9ui4DLgF7A00A3YA7wHVUtCec4WkOB+2Z+w6JNOfROiyO/uIwFm7LJLSzbn91zWI9Epg7sxqItOWgIYqKEoVnJnDaxDwcP6RbZLyBSLOgzpt3QkLJ2wS52b9lH/zHd6DEwJdJD6vI6w/mxo4oOBogOwvvLtrN4cy4zhnYjLSGGt5dso3daHCePc8lVikrLeW3hVrbnFnHi2J4MzqzctlBfkBYMCPExQT75Zhdz1u/lwAHpHDKs/pq+O/OKeWXBZhJiojh9Ym+S46Lrfa0xLZa9EVa8DqqweY4L5o76WWXW9RivSPuKt1wdvuwNsPFLF/AFoiF9ABx2M+xaBUtedLOCh93sZvAWPQdlxTDsWJfnYdtiF+ANPx4GHuLaDcbC8jcgZyOMOg0yh8PGJbDmA+gxFkacaKvD2kjYZvxEpA/wCTBaVQtF5FngDeAk4AVVfVpE/gksUNV/NNRWpO5oqioH/24m23KLWtzGz08ZXS1dtDHGtLUPnlzO0o+3uAcCx10xhmGTe0R2UPXoCjN+neH82NH97o1lPDBrzf7HQRHKveuhw4dn8ujlB3H+g5/zxRqX8CU2KsAzVx/MxH5pjbb9jw9Xc9dby/c/vu2EkXzviCG1XrdhdwGn/u0TcgpdQo2hWUm8dv0hNvNn/LV6Jjx5DoTKqh8PRLlMnRXB3zs/g8/+2vR249MgJgVyNrjHEnAlG6o68Y+uYPsTZ7kC8gDBGDj4evjk7srXTb0GTryrWV9WV9Xes3pGAfEiEgUkAFuBo4DnvecfBc4I8xha7Is1u1sV9AE8WOXEYowxba0ov5Rln26tPKAw/90NkRuQqdChz48dWVFpOY98tq7asfIqN8E/WrmTV+Zv2R/0ARSXhXi0xnvq88Cs1dUeP1jjcYWnv96wP+gDWLVjHx8s9yejuDH7ff732kEfuGMfe/vryorhqweb125hdmXQB7WDPnCB5PYllUEfuCWeX9foa/Z/oLjh0inGH2EL/FR1M/AnYAPuhJaDW7qSraoVP4GbgD51vV9ErhKR2SIye+fOyJRECPgw7VxX1i5jjGlLtf4M2ZKaiOoM58eOTKTxX4G6zt1N/a2pee1Q37VEXcftV9P4rr5MnbWeC8cPn9TTf12/YPbD3xbCFviJSDpwOjAI6A0kAic09f2q+qCqTlbVyZmZmWEaZcMOGpRB77S4VrVxTR3LO4wxpq3EJUYz+tDKgtAiMOm4/hEckekM58eOLDYqyOUzqm/BCFaJ9I4ZlcUpE3pzyNDKvXlx0QEum9G0bRvfO7z6eb+uZZ4A5x/Uj/SEyj19I3smc+TIrCb1YUyTHXyt26dXUyAaDr3JfR4VC9O+17x2EzIgvcrvhNSxRPmQH0DWKBhe5c9bMBamfZ9qwd9BV7l9hybswrnH7xzgBFW9wnt8MXAwcA7QU1XLRORg4E5VPb6htiKa1bOsnL+8+w0LN2XTJy2e/OIy5m3MJrugmMJSJSAwuncyUwd1Y+GmXFSV6KgAw3skceqE3hw4wJ96gMYY01KqyvpFu9mzNZ9+ozPI7Nd+ky91kT1+neL82NHNWrmTxVtymDGkO6nx0byzdBu90+I5fkxPooMBSspCvLl4KztyizlhbE/6ZSQ0ue0v1+xmzoa9HNg/namD60/ytiOviNcXbiUxJopTJvQiISasOfdMV7XrG1jxhgvONn0F0Ylw5E8grW/11616H7bMg5wtsP4T9/pAFGQMhENuhr2rYfH/oPtImHG9e37JC1BWAsOOg7UfwrYlEJ/qHlfUDCwvhWWvQs4mGHkydBsCW+a7/Yc9x7nEMKZJWnuODGfgNxX4DzAFKAQeAWYDhwH/q7J5faGq/r2htiJxYisuLWd7bjGJsUHW7trHoO5JhFTJLy5DRIgJBthbUEK/9AR25BXRLSmWuOggIVWKS0OkxkcTsHWedVN1qYITLCg2xlTXRQK/Dn1+7AyKSsspDymJVco2lJSFKCorJ8XLrBkKKblFpaQlxDS7/byiUqICQlFpiPTE5r/fGN8V7oWYZCjOrX39VbAXCnZDWj+330+CECqB+HT3fNXrNlXI3QaFuyAmFRLSXBbP+hTscYFfMNqu+3zQbss5qOqXIvI8MBcoA+YBDwKvA0+LyG+8Y/8O1xha6p53VnDfzFW0JiTumx7HX847gMkD7Ye8mi3z4PkrYM9qV7jznEfcMgBjjOkiOvL5sTP487sreWDWasrKlXMm9+M3Z4zlma838vs3l5FXXMaxo3pw4dT+/OTFxWzOLmRcn1T+ftGkJs34FZWWc/NzC3hjoUuopMCoXin846JJDOxuS9lMBOzbAc9eAhs+cwGdlkP34e76q8cYeORUWDerxpsEUBh4KBx2C7x+E+xeBan9oXAPlNRIxDL0GDj/KVejr4Iq/Od4VxaiQs8JcN5jkD4wPF+raZQVcK8hu6CEA371bquCvgr9MxL46JYjENuwWunv02HHksrH/abBFW9HbjzGmHalK8z4+clm/Jpn9ro9nP3Pz6sd+8Wpo/nN68soD1We+ZPjosgrqsyEeMyoHjx0SeM/lg/OWs3/vbG81vFDh3Xn8SumtmLkxrTQy9fCvCdqH+9zIEy5Al76fsPvj89wwV5jKko3VPjsfnjnx7VfN/xEuPDpxtszdWrv5Rw6nAWbsn0J+gA27ClgX3EdKXS7qlCoetAHsG1RZMZijDGmy1m2NbfWsS/X7qkW9AHVgr763ld3+3nNOm5M2NV3nbVtMaz5qPH3NyXoA9g6v/rj9Z/W/brti5vWngkLC/xqmD64W7XsXq0xsV8ayXF1ZFLqqgIBGHR49WNDjozMWIwxxnQ5Bw/pXqtUwxkT+5AYUz0jYc/U6hm9Dx3Wnaaomgm0Je83xneD67nOGnIkTLyw8fc3dVnm0GOqPx5/bj3jOaJp7ZmwsMCvhuioIPdfOInU+OZtfwwIpMZFkRwXRWp8FMeM6sHfLjwgTKPswL71AIw6DVL6wLhz4NS/RnpExhhjuoihWUncf+EkRvdKYUhmIr8+YywnjO3Jvy+dwqT+afTPSOAHxwzj6SunctTILHqlxnHe5H789JTRTWr/rAP7csvxI+iTFkdKXBQZiTGcNakvd542JsxfmTH1OOIOOOhqSO4NiZmQmAVjzoTT/uaCsEN+6DJ3AkTFQUI3iE12r512LVzyGow+3V23DT/RZeGsKhjj9gGOPbP68TFnwNRr3PMIRMfDAd+B4/+vDb5oUx/b42eMMabdsD1+zWPnR2OM6TrabVbPjm7uhr08/dUGtuUUsS23iOyCUnILSygtV4JBIShCQISyciWkiojL3qWqpCfEcPL43lxxyKBm1f3pMla+A4ufh5Te7m5SkhUgboqS8hL+8PUf+GTzJ/RN6sud0++kb3Lfxt9ojDGmXl+s2c1vX19KXlEZFxzUn6sPr11w/fPVu3l+zibSE6K5/JBB9E6Lb1Lbu/cV8+CsNXy+ejex0QHG9Uklu7CUtPgYLpsxkJ6pcTz2+XrmbdjL1EEZXDh1gG/bTYwBIH83fHYvrP4AYpJgwvkw4mR480eweQ50GwapfUBDMOkS9+/cx92s37Rrai/1XPUeLHwOknu4Gb3lr8P6zyCtP2xbCHvXwYBDXHH4BU/Bxq9g50q3VzAQ5WYShx7tirun2jVMW7MZvzos2ZLDGfd/Sml56743mcmxfPCjI0iKtfh6v2WvwTMXVT7OHAnf+9zt/zMNuubda/h0S+Vm6YSoBD449wMSou3mguk8bMaveWzGr3VWbs/j+L/Mouql0M3HDuf6o4ftf/zFmt1c+K8vqMj/0js1jpk/OoK46CANCYWUk/76Mcu31Z3YJSs5lsOHd+e5OZv3H/vuIYOavKzUmEapwj8Phe01ErzEprh6fjUFotx7tNw9TsyCG+a6IBBgxVvw1HmVr49Lg6LsuvuOioeywvrHltIHrp/jloCaJrOsnmHw0rzNrQ76AHbmFfPRip0+jKgTmf9k9cc7l7s7TqZBJeUlfLbls2rHCsoKah0zxhjTdE99uYGa97+f/GpDtcf/m7OJqkk/t+QU8emqXY22vWhzTr1BH8COvGJenLel2rHn5mxqfNDGNNXWBbWDPqg76AMIlVUGfQD5O+Cbdysf17yGqy/og4aDPoDczbDmw4ZfY3xngV8dMhJjfWwrpvEXdSUJ3eo4ZkXuGxOUILHB2j+XGXH2vTPGmJbKSqnj72pC9WzcGUm1z+Pdkhq/TshIjKGxMr41VwR1s2sG4yc/rq8Su9f9uR8SLNttW7PArw4XHNSPYVlJrW7nuNE9mDbYLsyrOeSHkNSj8vFBV0G32vspTHXBQJAbJt1Q7dgBWQcwqcekCI3IGGM6voumDSAruTKIC4pw52ljq73m8hmD6JdRuRzt1Am9mdgvrdG2+2UkcMnBA+t9/oQxPfnl6WOI8vb0xQQD3HbiyOZ9AcY0JK2/y6VQVVQsDD6q7td3GwrpgyofjzgZBh5a+Xj6DZDcq/LxkKO8rJ116H1gw2Mbcyb0m9Lwa4zvbI9fPcrKQ3yxxhWt3JZbyJ78ErbnFrJuVwEjeiSxu6CUXqnx7Mgtorg0RECEqKCwt6CEGUO7M7ZPKgf0T2/TMXcYJQWw7hOX3KXn2MZfb/bbkLuBV1e/yoTMCRzS95BID8cY39kev+axPX6tVx5SXpy3mZ15RVxwUH/SEmpfyJaUhfh8zW7SE6IZ3zetWe0v35bLks05xEYFOaB/Gqt35pMSH70/eNyaU8iiTTlM7J9GVnJcw40Z0xLbl7ptNTGJrp5yYjfYNBe+eRuGHesSupTsg4GHAQprZ0FcKvSt409xaSGs/RiSe0Kv8ZC3HTbPhp4T3PadrQtgxAnQYwzsXAF71kLOJtgyDxIyIX0A9J4AfezGdUtYVs8wWbIll6e+2sAVMwaQk1/KvA17GZqZxJEjs9ieU0xqHAREKQuFGNQ9gYTYaMb2SWHT3gIEoW96F0+4kb8bdn8DvSbU3rhblA3xaS6xi2mW/in9ufaAaxt/YRdVvHo1WlJC3KhRkR6KMaYd25lXzJpd+wDol57AsaN6sHJHHtHBAOt25ZNbVMq4PqmIt1YzJirA4cOrZ6Dem1/Cqp37GNs7lY9W7qAspPRKjaNfRkK1AG5kzxQSY6LYnV9Cr9R4+tS4PuiVGk+vVEtwYcKkvNQFdf0Pho1fwu5VUJIHonD4bSACW+dDan+3HzA2BfpOge1LIHsj7F4NqLueS8iAvK1uyWfWaNj4tQsA49JgzQcQnw7dh7uPsmIo3At9DoSBM1x20L3rIGOQe64oF+JSIvqt6Yos8KvDhf/6gs9W7wbg9UVbqzyzvcltCPCL08Zw6fSBvo6tQ1jwDLxyPZQXQ3wGXPQ89PWm/D++B2b+xm0eTusPF78MGYMjO17T4WkoxOYf3kTe228DkDBlCv0efIBAvF1MGWOqe+KL9dz5yhLKqmRsCQagPATRQdmf3G1snxSevGIaqTX2/AG8PH8ztzy/kJKyEIIr57S/LYGfnzqGS7zz/69fW8p/Pl2LKgzvkcST351GZrJ/uQSMqdfu1fDY6ZCzse7nM0dAIKZ2AphAlEv0Uu1YtAse181yj4MxUF5Sd7vRiRAdBwW7QYIuc3t5afXXxCTCOY+6GUfTZmyPXw2quj/oa1U7wP+9sYz84rJGX9uplJXAW7e5oA9c3ZZ3f+4+37cDPvhtZcao7A3w0R8jM07TqeybNWt/0AdQ8PXX5Lz8SgRHZIxpj/KLy/i/N5ZVC/rABX1AtYzeizfn8tjn62q1UVoe4pevLqWkzL2p5oaZcoXfvbmMvKJSVm7P49+frN2fOXTl9n38+5O1fn05xjTso7vqD/rALcWsK+tnzaAPIFRaGfRB/UEfQGm+C/rAXfPVDPoASvLhzdvqb8OEhQV+NRSWlDf+oiYqKQuxt6CBX4zOqDTfTe1XVfFHJ29b7T8mDf1BMqaJyrZurXWstI5jxpiuLbuwlIJmnOe35NROSV9YWs6e/IbP7UWlIfbkl7Alu/b76zpmTFjktPPyIO19fJ2QBX41JMRG7c+w1Vpjeid3vb1+8ekw5Ojqx8ad7f7tMRa6j6j+3Niz2mZcplNLOvJIJKHK71pUFCnHHxe5ARlj2qU+afFM6p/WpNeKwKnje9c6nhIXzREjMut4R6UJfVMZ0C2RaYO7VcsaCi4rqDFtYuyZ/rYXqL3suVUqrg9Nm7GsnnVYv3sfp973KXlFZUQFhbJy3b+Uo+Za/grRAYiPiWEVemYAAQAASURBVKI8FCIYCHDo8O786rSxTar10+kUZsPHf4Jti2Ho0TDt+xAIuudyt8CsP0H2ehh9Bkz6TiRHajqRwkWL2fPww2hpCekXXUTitGmRHpJpAcvq2TyW1bP5du8r5v4PVvPp6p2Uh2Bi31TiY4Os21XA0Kwk9uaXsq+4lPOm9OfY0T3qbCO3qJT7Z65i6dZcEmKCzN+YTWFJOVkpsRwyNJPrjhpKd+/8v3ZXPn//YBW780s4a1JfTh7fq842jQmLOY/C0pcgZzMU7ITYVJdbIRAFB1wEUXEw5xEozgPUldyKTXVJYMpLIX87qMLIk2H06TD7P+46L32QS+KHws6V3n4+cQlbJl8BMUkua2i3Ya6ExKLn3Pui412Oh+EnwCE/qJ0A0DSotedIC/yMMca0Gxb4NY+dH40xpuuwcg5hUFhSzhn3f8rKHXmgdc/wNUaAk8f34q/nH0DAp6WjHdKeNfD+r1xmqZGnwGE/crN/ZSVu0/E3b7uyDkf/AtL6RXq0xhhjuoD84jKuf2oen6/ehSrERQeJCgrDeyZz87HDOXBABgAb9xRw6/8WsnBjNvExQXqmxIIIJ4/rzdWHDa52fn9n6TZ+8PR8CkvKSU+MISsphvV7ChARMpNiOXNSX646bBB//3A1ry3YSkFJGcnxUSTERFFWrhwxIpMbjxlGbFQwUt8W01l9+SDM/68r61C4B4pyIFQOEoCUPhCT4K7XABBI6AZJWS7z5sHXwciT3KzezF+5xHwjT4EVb7jafBXiM7zkfQIZQ2DfNpfAJT4dQiH3uCIhTCDKZQVNyIDJl8GMH7rMnybsLPCrw3kPfs6K7XmtakOB1xZupU96PHec2EVrioVC8MTZsGe1e7xtofvFPuwWl93z0794xxe5op/XfBKxoRpjjOk6rn9qHjOX79j/uMjL0Llr1W7mb/iKT247ivSEaC7+z1es3ZUPQH5JObv2uQvXxZtziYsOcNmMQQCUloW4+rE5+28U78kvqZYAZv2eAv783ko+W72LL9fu2X98e17x/s+Xbs2lPKTccVIXvWYw4bHgaXjzlrqf03LI2VD7eN4W9wGw4XP47gfwzEWQ6yVj2bqg9nsKK3+u2TKn8vOi7NqvDZW6j5x8NzkQjIXp1zXpyzGtY+F1HZZsyfWtrTcWduHMgrtWVgZ9FVa8Wf3fCtsWWXYnY4wxbeLTVbvqfa6gpJxPV+1i/e6C/UFfXd5dWlnbd+aKHU1aHbRgY3aDz1dt0xhfrHijde/XEMx7rDLoC4fWjtE0mQV+dUiN928idFBmkm9tdTgpvV0Rz6q6D/f+HVb9eHw6JDacJc0YY4zxQ++0hhNKDMlMIislloSY+pddDqlyfh/XJ7VJ/XZLimnw+cFd+ZrBhEfFdVdr9DnQLc0Ml5rXhCZsLPCrwz8uOhA/tuUlxUbxhzPHtb6hjiouBU6+G2KS3eOsMXDkT9znx/7KZXoClz3qlL+4rE/GGGNMmP35vInER9cO6oIBuP6ooYzunUJCTBS/O3Mc0cHKC4KKz8b1SeX6o4fuP947LZ5jRmY12OeIHkncc95EhmRWvyEa9C44BndP5McnjWzhV2RMPQ6+DgbM8B7Uc3Er9V30Cky4ECZcACfeBdFe2aTuw2kwhJBmhBc9xsLhtzf99aZVLKtnPcpDyttLtjG4eyIbdu/jo5U7CakSDAjxUUFG9UklgDCqdwprd+azaPNeCovLiYuJYkC3BAZlJnHQoG5tOuZ2q3gf7NsO3YZUP67qNhMn93Ibi40xXZ5l9Wwey+rZcmXlIeZtzCYrOZbykBIMCqlx0aQlVJ/ZKCwpZ8X2PLKSY0iJj2HPvhL6d6v7nLU1u5BPV+/i9Il9KCgpZ83OfXRPiqE8BAO7u4BPVVm/u4D46CCloRDdk2LZmlPEwG4JSL0X4Ma00t71EJfq9uIV7HXXYMW50GeSC+jWfQKZo2D3SnespMC9L7lKSZPiPMjfBRmDXHKYFW/C9qXQbzL0meJt2VHIHOGSwJQVuyQxJfkuqd/ub9wY4tNccBiMdqUlTJNZVs8wmbt+L+8v287nUUFeWbSFfUVlJMYE6J0WT2pCDDNX7mL64AxeXrCZz9fscfdQNERpOfRJj+eF789orIvOKXsTvH6T+/zku12mztgk91GTCCT3hFl/gKJcl/EzxQrb1hTSEJ9u/pQ9RXvondib9za8R/f47pw74lxSY5u2vMgYY0x1UcEAUwa67J0bdhfwxOfriI4K8O1pA9iSXcQ32/OYMbQ7QRGem72RqKDQOzWevfkljOqdQlFpOX3SEpgxtBsLNuWwbGsu04d0Y/KADJ6fs4kxvVPISIzh3aU7yCkqZVzvVI4YkUlUMMDA7ols3FPAG4u2klNYwmHDsxjUPbGRERvTQnvWwus3Q1QMnPJX6DsYNs91mT7nPAIHfAdWv++yrR98ncu6uf4TyN0KqEvwsnu1q7136M2w5GVY+jIEo2D6DbB9Mbz2A0gbAOkD4Zt3Yf2nlbX9ErNgxo3Qdwq8eqMLIE/8owV9EWAzfnW4b+Y33P3Oyla388ltR9I3vQvNZG1ZAA8eVv3YVR9B74l1v74kH/44DEq9zfMShKtnQc+xYR1mR/P9977Px5s/rnU8MSqR5057jn7JVgbDdB4249c8NuPXeu8v2853H5tNxeWQUFnGKSgQaqSs08ieySzf5jKBV2wTCdXRFsC0wRn897vT+OibnXz30dmUhyqfvfjgAfzqdDv/GZ9t/Br+fUyVAwKH3ASf3F3/e2KSoaSe7PYS9Mo2+OA7L8GQI/1pq4to7TnS9vjV4R8frm78RU1w87PzfWmnw3j1+trHXqnjWIWP/lgZ9IH7Q/L2Hf6PqwNbuHNhnUEfQH5ZPv9d9t82HpExxnQud7+zkqr3wKsGauVNqOVbEfSBC/hC9bQF8MWaPXy+Zjf3vf9NtaAP4PHP17Mjr6hZYzemUa9cW+OAwid/bvg99QV94F/QB272z7QpC/zqUFoe8qWdvMIyX9rpMEoK6zhW0MDr6/jD0tDru6DCsjq+p8143hhjTMMKS328kG2CgpJyCktrX2coUFzHcWNapbSumwnt5OesrLjx1xhfWeBXh9Mn9PGlnd+fPd6XdjqMY+6sfezYX9b/+kN/5JYMVGWZnaqZ3GMyw9LrTnMcIMDZw89u4xEZY0zncvkhg1r1/m6JTU9zP7BbAocN787FBw+o9dyRIzLpl9GFtoeYtnH0z2sfG3lKw++peW0WLoff1jb9mP0suUsd/nTuBIZkJfHawi3kFZawcW/R/uUasUGIjgpSHoLeqbHszi8hu8bMXlRA+NuFBzC+b1qbjz2iRp0MZz8C7/7MZYs67jcwqoE/Lim94JqP4a0fuyWfh98Gw45ts+F2BMFAkEdOeIT/rfwfuwt3ExcVx5fbviQtJo3rDriOERkjIj1EY4zp0L4zbQA9kmN5+NN1BAPClYcOYmtOESu253HEiCxKy0Lc/8EqykJKZnIsxWXlDMxIIBAIMKh7ImdN6sPbS7azdGsuhw/PpDykfLJql0vukhDDKwu2kFNYyuSB6Vw4dQCxUUEuOKg/vdPiefqrDeQWlnHs6CzOP6h/pL8VpjMadzaEyuD9X7mA7sQ/wojj4csHYfZDUF4KI072krlsdkHhjBth/pOwa6V7fstcKMyFHqPgxD/A0ldg+Wuutt/k78KORbD+C5etM3ME5G2FrQtdLgcRd/ygqyBrLLz+AzfTd/gdMPmSCH9zuh5L7mKMMabdsOQuzWPnR2OM6TqsnEMYPPLpWu58dWmr2hDg4ukD+MUpYwj4UQ2+vVs9E968DbI3wphvwSn3QHQ8rPkQ3rgVstfD6DNg2HEupXDRXu+N4u4sNbQk1Jh6ZD//PDv/eh+hwkLSL7yQzB/caHWwmiFnZyEzH1vGtjU59BycytGXjCKle3ykh2VM2L26YAu/f3M5OYWlnDSuJ+t25fP1ur11JnLJSIwmu6CUkLqsndcfNZQfHjuCTXsLuPX5hXy9bg8T+qbRLSmGd5ds3797akLfVB74zmS+WruHO15YSH5JOSlxUfz1ggOYMbQ7339iLu8t3w4Kkwdm8MhlU0iMtcsy0wa+fhjeuNklapEAzPghrJsFm772XiAw9Fj41j8hsRu8+wv47K+gITdrmNYf9q6t3mYg2j1fX/IXCbp2tcoqOQnA1Gvg+P9roIi88ZPN+NVQVFrOqJ+91WgWr6b63ZnjuKCzL98o3gf3jHKFQCscdisc8kO4ZyQU5VR5cYA6NxVf9iYMmB7ukZpOpHjVKtacehpV0/H1ueduUk46KYKj6lhevHsuW77J3v+4z/A0zrhpUuQGhM34NZfN+DXfluxCDvvDB5SFWn6mf/bqg7lv5jd8/M2uBl83Y0g3Pl+zu1qmz9ioANceMYR73vum2mu/M20Avz7DyjmYMMveAH8Z17TXjj8PDvg2PHpqeMd05r9g/Lnh7aOTsHIOPlu9c59vQR/A7HV7G39RR7djafWgD2DjF7BzWY2gD+rNJLX+s7AMzXReBfPmVQv6AArmzovQaDqmratzGnxsTGe0YGN2q4I+gNnr9zTp/D53QzY1uyouC/Hesu21XvvZ6oaDSGN8sakZN4o2fOE+wq0t+jCABX61DMlM8rW9Awek+9peu5Q1yhX7rKrvQZA5EmJTa7y4nh+5/geHZWim80qYOLHWsfg6jpn69RycUuNxzd9XYzqf8f3SCLZyC8aB/dOZNCCt0ddN7J9Gza5iowIcNbJHrddOHdytVWMypkn6HNj01/abCv0OCt9YqvZj2oQFfjXERQf52SmjfGnr4oMHcN6Ufr601a7FJsO5j0C3oS7D0/jz4dCbISbROz7MHR93Lpz5YI1gUGD6DTBwRoQGbzqq2GHD6PmrXxLM7E4gMZFuV15Jysm2zLM5jr5kFL2GpiIBodfQVI662J+/fca0Z33S4rnn3An0To0jPjrIWZP6MLmBIC4tIXp/8Ca4PX5TB3fj92eOZ9rgDIIB4YD+aRw7OouqMd64Pqncc+4E7jl3AgkxLj1+clwU//j2JK49aihHj6x8/eQB6fz4JPv9M20gfQCcdHdlyQYJwPQf1A4IhxwNJ/wOBh/hrtMq9uBJAFJrlyMhEOWeq48Ea5eJEIGpV9syzzZke/yMMca0G7bHr3ns/GiMMV2HZfUMk+dmb+TXry8ht7Ce7ER1ENi/P7Bvehy//dY4Dh+eFZbxmY4vpCEeWvgQMzfOZET6CG476DYSousu3lsWKuOp5U/x9rq36ZvUl+sOuI6+yX3beMTGGNNxLduay3+/XM/63QWoKtmFZfTPiOeyGQP5cu1eNmcXgEKv1HhiooTd+aUcP6YnBw5I58kv1/PMVxvp3y2BHx47nLeXbGPz3kLW7sqnqLSciw8eyBkH9KGgpIznZm/is9W7WL8rn6KyEImxUZSHQvRKjSc6GGD1zn3ERwcZ0C2BcX3TOH9KP9ISml4E3phm270aZv4aNs+F5J4QnQg7l7ssnNFxUFoEqX0hdyvs2+qOA0TFQyAIMUkQnwGhEug+AroPh0XPQeEeSOoBEy+Ckn2QmAmTvuPq9M1+GDbPce8PxEBZIeRucbkfglGuvzFnwcQLIcp+/tuKzfjV4S/vreQvNbJttVSXyOppWuSHH/yQ9za8t/9xz8SevHPWO3WWI7j1o1t5c92b+x/HBeN45YxX6JXUq03GakxbsRm/5rEZv6aZt2Ev5/zz82YndRGBE8f25I1F26odq+vS6fYTRjJz+Q6+WrenWX0MzkzkrRsPIybKdt+YMNi9Gv5xsAvG2kLmKCjKhbzNTXv96NPh3MfCO6ZOxLJ6hsF/Plnb+Iua6JFP/WvLdB5loTJmbpxZ7di2/G0s2b2k1mvzSvJ4a91b1Y4VlRfx6ppXwzpGY4zpLP775YYWZfJUhXeWbK91rC4PzFrd7KAPYM3OfD7+Zmez32dMkyx4qu2CPnAZ3Zsa9AEsfRnytjX+OuMLC/zq4Oddt7joYOMvMl1OQAIEa25yBmKDsbWOBSXY5NcaY4yprTXn4kATM4C25trBrhVM2ETFRXoEDQtEuQSApk1Y4FeHW08Y6VtbNxw9zLe2TOcRkAAXjryw2rGx3cYyLL32z0tCdAKXjLmk2rFucd04fcjpYR2jMcZ0FpfNGEhqfHSdzwUbiOvio4NcPmNgtWP1BXg/OWk0p0/s3eyxTR2UwcFWysGEy6SLIaENf76GHA29Jjb99QddDQkZYRuOqc72+NVj6ZYcfvHKYuZvzCEAxMUEyCssJyBufX9plTrkASAQgISYIMVlIQIiHDMyix+dMJIB3RLbdNymY/l086e8tuY1JmVN4qzhZxFoIBXyV1u/4o21bzAodRDnDD+n3kQwxnRktseveWyPX9PtyS/hzcVb2bC7gJioADtyixjYPYlzJvdl9ro97NpXggJZybHERwfZnF3IkSOy6Jkax8JN2Tz86TpG9kzmkukD+WjlTvbkF7NhTwF780u5dMZARvZMQVX5ZNUuFm7KZu2ufPYVldEtOZZ9hWUM65FEMCAs3pxLSlwUA7snMqh7IkeNzCIqaPfhTRgV58HsR2DdLMgY6gKtdR+75+K7u4QuvQ+A7A2w/lMoK3UXu+n9IVQOyb0gtTcU5kCv8S6w+/pfsHedS/Qy7fuwd61L7jL0GPeelW/C1kUueYwEIVQGe1a75C4SBd0Gw/DjYcD0CH5jOp7WniMt8KuHqvLI52spKCzjmFE9eOzL9ezKLeLoMVlszi4iJSaKXfml9M+IY09+KUu35BAbFSQgkBofw6WHDKZfRhe8MN/n7VNIyqz9XHEeFO6FNC/ZTd52CEa7bFG5myBtoIugu4ji8mJ2FOygb1LfOhO6AKzauwoRYUjakDYenTGRYYFf81jg1zy79hWxdmcBkwemszWniOS4KJLjotmaU0gopBSUlJMY6xKe78wrJiYqQEiV3fuKSY6NJjpKiI0KUlIeol9GAilxlbOIRSVlzN+Yw8T+qZSUu/cERQChR2ossVFBtuUUER8dJLuwhH1FZYzpk1rPSI3xUagcNn7hrrfydkJpAQw72tVbBgiFYOsCKCuBTV9Dcm/oe4AL2PJ3QkovV6Nvz1rIHOECx73roTDbZegsL3Op7Qv3uvem9oV92127+Ttg3w7IGOiyhO5ZAym9obwEohOgx+gIfmM6HivnEAZfrtnNeQ9+sf/xH9+tzPD59rKmbcD+92fr6ZsWy7PXzKB3WrzvY2x3QiF49XqY/1/3eOKFcOp9lYHcV/+Cd3/u/tj0mQxJWbDiDfdHJeil+U3rD+c96e4mdXIzN8zkZ5/+jNySXAalDuK+o+5jQEplQdRt+dv4zpvfYVu+2/DcO7E3j5/0OFkJVh7EGGNa4kfPzef5OS7pREAgpBAbFaB3WhxrdxU0uz0RuOmY4Vx/9DAe+Wwtv3p1KSFlf1H2qrfVU2KDDMpMYsGmnGptZCbH8t5Nh5Eab3ucTJis/hD+e44LtGo6+k4YeRI8dAwU5za9zfgMV8qhXlULnDUirT9c/THEpzW9f9NiXWd6pRkue+QrX9rZlF3Mn95Z4Utb7d6K12HeE672i4bc5yvecM/lbYe3bndBH8Dm2ZXPabkL+sAtMXjz1rYfexsrLS/lzs/uJLfE/ZFdm7OWu2ffXe01f57z5/1BH8CW/C3cO+feNh2nMcZ0Fqt35O0P+sAFfQDFZaEWBX3gsnve/e5Klm/N5TevLdvfplL7kje3uLxW0AduVvHHLyxuUf/GNMkLV9Yd9AG8/0v433ebF/RBI0EfNDnoA3ft994vmte/aTEL/OpQUBJq/EVNtHrHPt/aatd21hHg7vKO7Vnj1na3tJ1OZm/xXvYW7612bG1O9bIf3+ytXUdyZfbKsI7LGGM6q0Vbmnlh2wzzN2a3qFREhVVd5TrBREbBrgaeVLc3L9K22c2PtmKBXx0GdfNvb95RI3v41la7Nuw4t/67ggTcMYA+kyCpid+H4Sf4P7Z2Jishi1EZo6odO7zv4dUeHzfwuFrvO37A8WEdlzHGdFZHj8zy9tv5KyE6yEnje5GeUHfG0KY4dUIvH0dkTA29JtT/XHQiDD+x7cZSn/HnRnoEXYbt8avDmz84jGn/9x7ZhU2cparH9w8fwrVHdpGkHL3Gw7mPw2f3ucczboCe49znUbHw7Rdg5m9cEpexZ7sMUV89CIGg21yctw0GHgpH/zxyX0MbuvfIe/nz3D+zKnsVh/Q5hOsmXlft+e+O+y57ivbw6mpXpP20Iadx2djLIjFUY4zp8JLjonnw4gO544VF5BSW0is1joTYKLKSYxnZM4X3lm5jR14xpeVKdBDKFYpKygG3LLRiPs9l9haCAWFwZiK/+9Y4UuKief5707nqsdls3FtIj+RY0hKiWbe7gPKQEh8dZMbQbozpncrri7aSV1jKjrxiFDhlfC+uO8rKPpkwuvhleOJs2DK3+uqrxCz4zgvQbSiUFbksnOWllc8Hol2NvfIyiIl3a5vLi937Bh0Gq95xyV0qkkSqt1ouGO2SuxTvg4I9oBV9Vt396pIeER0Lky6BqVeH9VtgKllWT2OMMe2GZfVsHjs/GmNM12FZPcMgu6CEKx75mrkbspuzPbWWgwdn8PgVU7tGfZ783fDx3bBrpavNkrsVouNh+vWVM3/fvAtv/RiKc2DMmXDcb1waYNOgwrJCHl78MAt3LuTAHgdy6ZhLiQ62fFmRMQChkLJw5kY2LttD977JHHjCAGLi7ffRdG7Pfr2RJ79cz659JUQFISYYJCYqwKDuiWzeW8CybXnERgW46rDBXHukm4m744WFPPP1RkLq6vUOyUziqJFZnD+lHw9/to7Fm3PYmVfM7n3FDOyexLg+yazbXcjEfml8uWY3s9fvJaSKAPExQYIixEQF6ZUWx/i+qXz/iKFdI/u3iYy37nCZ1UNlbjYuVO4S61Uj0G8q5G11s3+BKDdjFx0H/Q92s4ILn4H8XW4VV6jMvS46wdXx03JX3qE4r3LmD1zW9oQMV0YiaxTMuBHWfw4f/8m9NjoBxnwLjvpp3WXAjO9sxq8Ox9z9Iat25vvS1uQB6Tz/vS5QnPKhY2FTHdlQY5LhhrmuDsw/ZlAt09PkK+CUe9psiB3VbbNu4421b+x/fN6I8/jptJ9GcESmM/j8xdXMfXv9/scDxnXjlGsb2AvSRmzGr3lsxq/pHv9iPT97qelJJH52yiiCItz56tI6n++WGMPu/HqyJTbDoO6JvHfT4QQD/u9BNF3cJ3+F934W6VFUCkZXX05aofcBcNWHbT6cjqi158guMBXVPNtzi3wL+gDmbdjb+Is6uuwNdQd9ACV5sPJtWPgstdL7Lv5f2IfW0YU0xDvr3ql2rGoQaExLffP19mqP1y/eTUkr9zUb0569Mn9z4y+q4qmvNvL3j1bX+7wfQR/A2l35LNyU7UtbxlTz9b8iPYLq6gr6ALbMg931/64Z/1jgV0NyXJSv35S46KCPrbVT8eluur4+Kb0hbUDt44k2rd+YgATontC92rEeCV0kU6wJq6T02GqP4xKiCcbYKcF0Xr1Sm7ecsk9aPL1T4+p93q/5uYBAj5T6+zGmxVJ7R3oETRPwloSasLOzfA0JMVHccfJI39r71eljfGur3YpNhmN+6daEQ+W/4NZuDzkKJl4A3UdUHg9EwalWkLwpbj/oduKC7qIgMTqRW6bcEuERmc7g4DOHEpvgflcDUcIh5w4j2BX2I5su68ZjhjU5wIqLDvCzU0bzwLcPpK4qEHHRAS6c2p/oYO0nK1ZsxtTxXF2vve6oYbbHz4THaX8D8WECIhjT+jbAZW+PqmOi4Ng73SSCCTvb41ePHXlF/H3mNyzblke3xBjiooPM35jNjpxCMpNjiAoGKS5X+qXEs2rPPsrKlJLycgIBYXL/dAZ0T+S6o4aRkRjbeGedRd42V6y99yTYsdTNAmbVCKLXfAQ5G11AGJMYmXF2QDnFOazcu5JRGaNIikmK9HBMJ1FaXM7ODbmk90wkPtmnE3sr2R6/5rE9fs1TUhZi/sa97CsuIz46SDAgCEK3pBhio4K8PH8zvVLjOHl8b2Ki3I2QUEj50zsr2LQnn3On9CMqGGRUzxRSE6LZkVfE2p35ZCXH8MmqPRw8JIPuSbEs35bH2D6pFJaU8dhn6wkEITYYYFhWMjmFpXRLiiU5LoqeqXH0TfevdrAxtZSXulJb2RtdreSNX0BZCWxbCOmDYO9q6H2gS7Cy6l0oK4aMwbB5LqT0gYyBbtXWxi9gy3y3Hy97A+zb4Wo0Dz0K9qyF0kLYOt8FmqqujENyHzfrGIhyM3o9xrj2l78JO5ZB5nAYMB1SrJZlU7XbrJ4iMgJ4psqhwcDPgce84wOBdcC5qtruNsLFRQVZsCmHZVtzKA9BUKCkHKICUKawI7uQkEJOfhEFpUpAhJiAkFNczserdlFcrmEpFttu5WyCuY/DgINdpqd9O2oHfQCDD699zLB532ZW7V3FhMwJrMpeRUAC9E3qy9I9SxnbfSzd47szpeeUSA/TdDLRsUF6D7O7rJHQ0c+RHdWGPQXkF5cTFx1EgQMHZBAMCLv2FfPOkm2kJ0aTXVjCs19v4IxJfVm2NZenvlzPEcOzOHRYJjFRwuheqXyxdjd90+IZ1iOZjbsLuOedbygoKWPdrn0MyUoiKLBm5z4m9Evj5uNHkFNYyvOzN5JXVEZcdJAX523i6FE9WLEtj9LyED1T4zhseCYJMZZZ1/gsGA2H3gS5W+Ctn7ggLa0fZI5wNZjj01wCvucugZJCSB8A6z+BnO2Qsw4mXATdhsC6j93M35cPgIgLGg/4Nnz9b5cNdNr3YdcqWPGmC/J6j3fHS/NgzzpY+RYE4iE6xs38dR/qJgziUiP8Depa2mTGT0SCwGZgKnAtsEdVfy8itwPpqnpbQ+9v6zuas9ft5ux/fuFLW49ePpnDh3fyPVnznoCXr618LEGX2lcCcMLvrTBnI55a/hS//+r3hDREQAKEvFTIgqAo0YFo/njYHzl6wNERHqkx4dcVZ/xac460Gb+m+9PbK/jbB6uqHRvZM5nvHTGEm55dQHmo+vWQUCslGQDRQaG03D0zqHsCa3cVNNjvEcMz+WTVLspCDV9vpcVH8+w1BzO8R3KjX4sxzbLgGXjxqkiPom7BGLh6liv3YBrVUbJ6Hg2sVtX1wOnAo97xR4Ez2mgMTXb143N9a+vGpxf41la79U6NVMEV9WE0BO//yk3/mzoVlxdz79x79wd7oSr1b9S75CgNlXL3nLsjMj5jTJvoUOfIjmhHbhH/qCND5/JtefzylSW1gj6oO+gD9gd9QKNBH8CHK3c2GvQBZBeWct/MVY2+zphme7Md5wYoL4E3bo30KLqMtgr8zgee8j7voapbvc+3AXVOh4nIVSIyW0Rm79y5sy3GuF9+iX8pzQtLahbJ7IRKGzjxleyDksZPjF1VUVkRBQ19/zx7iva0wWiMMRHSrHNkJM+PHVV2YWmdwR3AvuL2c57eva840kMwnVF7vwFfsCvSI+gywh74iUgMcBrwXM3n1K0zrfMvsao+qKqTVXVyZmbbpv2/dHodpQda6IwD+vjWVrs19Nj6nxt+AiR2a7uxdDCpsakc3q/xfY+nDzm9DUZjjGlrLTlHRvL82FEN75HM+L619xJFB4WTxrU8sUQTEneS1IwyKWcf2LfFYzGmXiNPjvQIGjb1mkiPoMtoi13EJwJzVbWiWvB2EemlqltFpBewow3G0Cy3nziaDXsKeWPRtla1c/rE3tx11nifRtWOnfc4vH4TrHzHbQoecSJsngNZY2Da9yI9unbvrkPv4ollT7By70oGpw5me/52EEiOTmZr/lYm9ZjEeSPOi/QwjTHh0eHOkR3Vo5cdxEOfrGHpllzKQ0pWShwXTu3PhL5pjOqVzPNzNrGvuIxQKERyXAznTO7LW0u2sXxrLukJMYztk0JmchzDeyQxZ302fdPjOW1Cb3728mLmbcimPKTEBIXUhGhio4LERgU5aFAG1x01lFcXbuGpLzcQFRDyisvIKSglOTaKhNggxWVK3/R4rjhkECe2Igg1pl5nP+xq5S16DggB4vbWxSa7hHylRZXbdAi45C1aDihEJ7pkMDmb3bLMkFeEPSoe+k9zxdfLiiFzpMvsXpTtcjzEJEEg4DJ6Fu6FUJXVdIFoSOzusr9P+x4ceEmbfju6srAndxGRp4G3VfVh7/Efgd1VNq5nqGqDi3tt87oxxnQNXS25S2vPkXZ+NOb/2bvv+Diqq+Hjv5nZXtS7ZFm25d6xjW0w1ab3EloI6SQhIXnTCckTCCEJIZUQEiAQSugQIPTeDTYY996LrN6l7Tsz7x9jbKvYkqyRZsv9vp+8eGdnr87us9LMmbn3HEFIHwnbzgFAkiQvcApwcFnHW4AnJEn6KrALuGQoYzgSb22s5Sv3fzrocaaUZPD0Ncfu7wWU0tqq4OWfwLa3jatHsgLOTKNXn81pXE0aczKgG/sUTDAqfuaOsTpyS7y9+23uXH0n4XiYyydczmUTLrM6JEEQhlmyHiOTkarp/Om1TbywuoaSLBejcr08vWIvkbiGBEY/PwnkfdWUo/sKuGS57Tz77fnc/OIm3thQt388CbDJEjFNR5bgpPH5zB+Tx+9f2dil+EuWx04wouK0y3zl2AounTOCax5ezrq97TjtCk6bTGsoRo7Hzp8umcHx48TUXcFEagxe/yV8ev++dX693OyRZKMY33CQZKPH32dxSDIcfTWc8fvh+fmCaODena7rjPrZS6aN96VjRnLjuVNMGy9h3Xua0dxzIPInwLeXDk08CWxP+x7OffZc4vqBaQ93LLyD48uOtzAqQUgM6XbHb7DEHb/+ufu9bfz2pY1H9FqnTSISN+dcqSTLRXVruNfnbLLE8l+eQobLbsrPEgTevRXe/o3VUfTtwn/BNHGNqz+SpZ1D0tjZZG4FyhdW1fS9U7KLBgee9AE0bDTuFKaZpbVLuyR9AB9Vf2RRNIIgCKnvvc1HXjXQrKQPOGTSBxDXdJbvajHtZwkC296yOoL+WftfqyNIGyLx66Yky2XqeL1VEUs5djfkHMGUTW8B+FK8uX0vxmeP77FtXPY4CyIRBEFIDxOLj7wputyPyp395Xcqh31eNG8XTFU42eoI+mfEXKsjSBsi8evGaVP4skntHDx2md9fPN2UsRKaJMH5/4SM7q0rJOM5275kunCq8T8AfzFc8E9Q0m9Ky9T8qVwz4xpcigtFUjhvzHmcM+Ycq8MSBEFIWd85aSzHjc0DjHV344v6l2DJEvzx4mkUZzoPu19RhpOFEwp6bD84Zzx+bB53fWE2fteB8gqfJZWyBD88dRwlWe5+xSUI/XLi9TDiaKujOLzS2TD/21ZHkTbEGr9DiMVV/vPRTtZXtxCIxinJ8DCm0MeaPa143XYWTiyktjWC0yazvamDutYwbrtCeZ6PTLedqaXZVOR7hzVmy2kahJqNkr2SBM4Mo/Sv3QvhtgP9/AJN4M4yCsCksVA8hKqp+Bw+q0MRhIQh1vgNjFjjNzCtwSgehw2HTaYtGKU1GMOmSHidNnRdR9PBpkjE4hp7moPMHJmz/7XVrUEaOyNoGpRkufE6FZo6o9htMsWZRsLWGY6xraETh00m2+Mgz+ekoTOCx2Ej021c6NQ0nerWEFleB267wu6mICXZLpy29D4mCkMo2AyRgHHeVb8ekMDhMWotqFGj4ErNSvDlG+ds/iJjKU5mGexcCpEWKD8GmrZC8RTQVKNo32dFWhQ7NO8Eh984B3R6IRYwWj6E24zxs8tAcRn7tuw22kJkjwJfnnWfSxJK6KqeySoa17joH4tZU91x0NamLvvc88Huw46R4VJ4/trjGJmbJslfLAzr/2es25MVKJ0FY08zpoF2NsCqR6B+A+SNh846aNkJWeVGHxckyB8H488CJX2+km6buLIrDI94TGXb8gbCgRgjJmRTvaUV2SZTOasAhyt9fucEoaYtzHubG2joCLNsVwseu0KWx8GS7U1IwLgiH02BGEUZLr4wr5zvPLIcn9PGnJFZvLCmlo5IjD1NQSRJ4qjybMbke1EUmcoCHxuq23l25V6y3HZG5/tYuaeVcEylJNvN2Hw/R43MYu3eNrbWd9ISjBKJayyozKci10NFnpdFEwuRzZxXKgif2fgirPgPRANGXz1kqF9rVPP0l+zrzxc3Ho8+2UjKNr2MMXMLozqow2uct+lA+x5j22evUeyQOQJCrcbPcPqN/6kRyJtgJJQbXwBJgRFzQLJB626jCvycr8L8ayz9eNKJuOPXi8qfvYhZa7nf/8lJjMjxmDNYotJUuPdU2Nvt/0YzroQTr4O7T4BgU++vPdiEs+Gyh4cmRkFIU5qm8/QfPqVuR7uxQWL/RdqsQg+f+9nshEr+xB2/gRF3/PrvxdU1XPvocrQEPe25cGYpf750htVhCKnmv1/b17g9gU08By59yOookoKo6mmyJduaTEv6AH7+zBrzBktUO97tmfQBrHwYltzRv6QPjKtBDZvNjU0Q0tzejS0Hkj7o0saptS7I9hUNwx+UIFjgzne3JWzSB/DMyr1Ut4asDkNINclQMXPji1ZHkDZE4tdNXDO3iaWayEcZsxyu8edAP09dHVwsgiB00desDi0d/kYJAol/PNZ10JJgFpYgmE5874eNSPy6WTA239TSzb8+Pw2at486EYqm9tw+5SKY9y2jyEt/VC6CgolmRiYIaa9sQjZ5I3ovIOTPdVF5VM9KhIKQir5+/CirQzisM6cWUZad4ktDhOE37kyrI+hb5SKrI0gbYo1fLwKROGf97T12Nh35lAunIvPMt49hUkka9PEDiHTCmiegbr2xcLhsNkw63yjW0lYFnz6wr7hLJXTUGtsySow+fpIE+RNhyoVgO3zJbEEQBi4ajrP54zoiwRil47Op2dKGbJMYP7cIlzexWqqINX4DI9b4Dczy3S28u6mBvS1BVlW14rIr+Jw21uxtA6A8x01HWKXA7+KSOWW8uq4Oj0NhWmkmb26ooy0Uo6Y9jCxJTC7JZEy+F7siM7bAx5q9bbyythafU6E818uGmnYicY18v5PKfB8zy7NYV93OtoYArcEIcQ1mV2QztsDP6HwvZ04txq6I6/HCEPjw77DqUeNcTbYZd9hadoKkgzML0Ix6DbpmtH/QVNi12FgaIGHMxlKcxnmbpkGgDuIxjB10Y0xPPkQ7jIIuNrdRNVSLQ/Zoo5L7jvdAkqFwCtjsxnmgGoMZn4eTf27dZ5NkBnuMFInfYXyytZH2SJTOSBSXoqDJEAipeB12cv12wnGVzqiGyyYRiqhsrW8nx2XD63EyY0QOowv7eacrVQSajCpOgUbwFxq/8DYnxCMQaYdYCDLKIB4yqkMJvYqpMZDALh84IY9pMaDrNkE4HE3V0HVQbMl1IikSv4ERid/A6LpOWyiGQ5HxOG10hGI47QoOm4ym6QSjcVRdJ8Nlpy0Uw21XaAsZJ7heh51oXCOsxvE77GhAhttOOKaiSBId4RiarqOqOrl+J4os0RqMkem2E9M0djR0MCLbR0ckhlORaQtHsckyJVkeWoJRcn3iwqcwhJp3QnudkXz5CoA4ZJYbSZ3NCfWbjfOzkunGBflgi1GlXbHvW9IjGa9t22v8119otGrQNCPhQwFPlnEu6MqAzkYj+VMUIz/UNMgph84miLQZ54TubMguN36e0C+incMQuOvdLfzuZXOKjLx47bFMLs0yZayEVbcO7jsTwq09n8ssM67qdFcwCS78FxSlwVTYftJ1nT8t+xOPbXoMRVL48pQv883p3+S25bfx0PqHkCSJL0z6AtfOvNbqUIUEt+L13Sx7cQfxuMakY0s4/tJxSKJMvJDmXlpTzfceW0lMNS54KxLs+yfTyzLZWNtBJD6wdeleh0IwqtLbJXSbDAMZzuNQuPeLs5k/RvQ1E0xUtxH+OQ96/ZYeguICNTxkIfVw2eMw4fTh+3lpLLkuBQ8Ts5I+gIvv/Mi0sRLWY1f0nvRB70kfGA1En/3WkIWUjN7a/RYPrH+AiBohGA9yx8o7uG/Nfdyz5h7CaphQPMTdq+/mw+oPrQ5VSGANuzv48L9biYZVtLjO2nf3sunjWqvDEgRLReIq33981f6kDw4kfQCrqtoGnPQBBA6R9MHAkj6AYFTlWw8vH3AMgnBY95/GgJI+GN6kD+DxK43ppcKQE4lfN+GYuV+8UMzcKqEJqb36yF5Xu3rgVT9T2LqmdT22La1d2mPb+qb1wxGOkKQadnf03Lar5zZBSCd7W0JHlNgNt7ZgzOoQhFQTarM6gr7pMeisszqKtCASv25cdsXU8TLdaTCbNrfyyF43cgHI4iv4mTlFc7o8lpA4reK0PvcThIOVjM3qsVyidHy2NcEIQoIYmevF50z843FhhljnJ5jMX2R1BH2zu8FfbHUUaUGcdffiX1fNMmUcWYI3fnCCKWMltC88DTmju26TZHDnGdU9pW5fM5sHxp4KF9w5fDEmgfkl87nu6Oso9ZUyMmMkNx17ExeMvYD/m/d/lPnKGOEfwQ3zb2B6/nSrQxUSWFahh1O+OpnsIg++bCfzLxjD6Bn5VoclCJZSZIn7vzyHbI9RIEsCfE4FCXDaZM6aWkTBQUlXf4trFme68LtsPdpAKRJkuGxIgK2fy2uLMpz852tz+7ezIPTXNz84fMV0xd1zm6+k2wZp3/+GgGyHr7wmCrwME1HVUxAEQUgYoqrnwIjjoyAIQvoQVT2HQH1HmDNve4/GzsHNtZ83KptHr56PlA5XMSKd8L/vwKYXQY0a22S70bfPmWGU//Xkwdyvw8wrIdgML/4INr5o9HyRbTD6RLj0P8Yt/zQUUSM8vvFxtrRuIc+dR3O4mZgWQ9d0xmSP4fIJl+O1izYYfQlv3kzrE08i2WxkX3E5jvJyq0MSBCFBvLqulhdWV7O+up3a9jCqppPnczK1NAO7olDXHqaqJUhHKEZU1Ymp2v4iMBKQ6bFTnu1GB3Y2BVEk0HRw2GQmFGXgcylsrO6gviOCJEFhposJRX7CURVJlli9p5WWYAy3XSa2b3yPQ2HWyBxuvXgaBRkuKz8eIRUtuw9e+pHRYkuSwZFhtG3QYiA7oHQ2BGqNvn5afN+LJOPcTY0aPf+06L6WDkdIthvjSBg/U1aMGGQ7HHOt6OM3jMQdv15UXv/igKtxHcqoPC9v/+hEcwZLZHfMhYaN/dv3xJ/D6keheXvP57JHw/dWmBtbkvj+29/njd1vHPL52YWzue/0+4YxouQT3bWL7edfgB4KAaBkZTH6xRew5eZaHJnQX+KO38CIO3799+jHu/nZ02usDuOQMt02Vv7y1PS4WCwMj61vwUMXWB1F3065CY79ntVRJIXBHiPFGr9uPt7RZFrSB7CjMWDeYImqdU//kz6AT+7uPekDaNkO4fSrQNgabuXN3W8edp9ldcvY1b5rmCJKTm0vvLA/6QNQW1vpeP11CyMSBCFRPPbxbqtDOKy2UJwl25usDkNIJa/9wuoI+ueDv1odQdoQiV83OV6H1SEkH4eXAS36dWYe/vnDLUJOUQ7FgVM5/PtWJEVM9eyD4s/ouS2j5zZBENJPhttudQh9yvWm3/FPGELeJJnt4vRZHUHaEIlfN5UFfspzzFtjduHMUtPGSlieHJjx+f7tKylw2m9gysW9Pz/lIrClX/LtsXv45vRvHnafqyZdRZ47b5giSk6ZF5yPc+yB9iLumTPxLVpkYUSCICSK7y0ci8dhbssmM80sz2Jckd/qMIRUcn6SVE9PljhTgFjjdwj/fm8bf3h9E6HYwD8fBRiZ6+am86eyYGwalVHfuRg++DM0bQfFYVxpmvUliAahaavRS2bKRZBRfGD/xX+F1irw5sOC70PlSVa+A8tta93GltYtTMiewOaWzWQ6M2mNtFLuL2di7kSrw0sKeixG5+LFSHY73vnzkUSvyKQi1vgNjFjjNzDNgSgfbmukqTPCh9uakCQYmePllImF1LSHkSVYVdVGWzBGIBKjviNMXUeEjlCcsiw3syqyKc/1Uuh38szKaipyPDQFomS4bcyuyMGpyGxt6GB1VRuSJDGtNJPKAh/huIamwe6mTl5eV8fxlblsqQ9Q1xFhQqGXEyYUcva07iX0BcEE0SA8dgXUrIH8sVA0DQKNUL8BckbBlM9BoAHWPwMdNRBug4JJUDQFWnaDzQVtVdC6AxQX2D3QsRfsPqM5vBaFzBJANloyhNsh3ALYjDt5dofRt7mzDtDBV2QUjmncZIx1wV3gExe1+0tU9Rwi58wo4+/vbCUUiyOzr6ePZhREiu5bAygDdtnoBRSJq8RVo3dfXIc8n5NjK9Psi5xVDrO/BmhQPh/c2VC3zvjjMu5UyBtn/LHxF4GmGlNEL7jLuGMoAJDlzKLYW0xHtIMFpQvw2D3sbjfWpWxt2YrP4cOhOKgP1jMuexxy9x6JaUrt6CC6azeucWORHA78J55odUhJQ9d1mvZ24vY78GaKaWZCavM5beT5HDQHIpw+uYioqjF/dC5toTiypLNsRwsnjM9jT0sYr93G9qZOttR2cN7MUt7b0sDm2g46o3HmjKzgnGnFZLjtVDUHKc/1UpTpYlyhnzENPs6aWkpM0whGVOP8QNOIqjoSPr5+rJtnV1bjcSrcfN5kQnGNcEy1+qMRUpXDA+fcBisfASRo2wPBJuOcLbsS1j4BOZXgKQDFCe5ciHbA5tdBdoLLv68aqB+KpxtJmwREAtBRC3mjQZfAta8KqDMDsiugvQpKZhrngqsfN24IlM0yqofKdiieAbGgEZ8wbMQdv15895FPeW51rSljPfSV2SwYV2jKWAntue/C8gcO2iAZd/baq3vumzsWogHoqDauJJ35BzjqqmELNVHdv/Z+/rr8r6i6cQLgtXsZlz2OFfVdq5xKSOjoVGRUcOcpd1LqS4PpxIfR/sorVF//c/RgECU/jxH/vBP3lMlWh5UUAm0RnrttJc3VAWRZYs7Zo5h9ZoWlMYk7fgMj7vj139q9bVx+9xI6IvG+dz5CmW47baEjawWV7bHz1g9PIFus8xPM9Mw3YdWjVkdxeGffBrO/ZHUUSUFU9TRZXNVMS/oAvnz/p6aNlbB2fdQt6QPQe0/6AJq2GEkfQDwMr/zM6AOYxhqCDdy2/Lb9SR9AIBbokfQB6BgXa3a27+TOVek9L16Px6m96dfowSAAakMj9bfeanFUyWP5K7torjYqD2uazsfPb6ejOWxxVIIwNH7z4oYhTfqAI076AFqCMW58br2J0Qhpr2Fz4id9AC/90OoI0oZI/LoJmTzdIqYl/h3VQWvZObjXRzsh2GhKKMmqLlhHXB/4CUlVR9UQRJM8tGAQtbm5y7ZYVXp/JgPR3hjq8ljXoaNJJH5CatrTErQ6hD7tbEqDFlDC8GlN7BYm+2lDe0FGOEAkft34XfaBNCbo0/iCNChRW7kIbIOohFo8w5gPnsYm5kykzFfWY7vUx7fx1IpThyqkpKBkZOCZP6/LNv9pp1kUTfIZc1RBl8e+bCeFo0T7CyE1nTm12OoQ+nT50eVWhyCkkpHHgJwEldIzR1gdQdoQxV168dF1JzPvlrcGPY7fKfPqD04wIaIE58uHL79kTNmsXW0sAq5YAKNPhKV3QnuNsZYvuwLcmTD1Ugg1w+ZXIG8snPgzq9+B5RRZ4e5T7+aOFXewvH45NtnGwvKFzC6czZObn6Q+WI8kSeS4crBJNjpjnZxacSqXjb/M6tAtV/rnP9P49zsIb9qI95hjyPv6160OKWlMmF+Mpups/qQWX5aL2WdWoNjE9UAhNf34tPHYZYkHl+yiM2zcYVAkyPI6kNFp6Izx2RwdCTjcfB1FApssEdd0QMKmSFQWeDlpfCHrqttoCcSIqiotwRiRmEpU1YjFNeKqzsHzimTA67JhVyS+MK+Cy0TiJ5jJ4YGr34aHP3dgic1wkm2g6cBhZtP5iuHanstahKEhirsIgiAICUMUdxkYcXwUBEFIH6KdwxBYtaeF8+740JSxPr1+IbkZLlPGShqf3AtrnjTaNuSMgRUPQrDFKPV74vUw+QJ4+2aoXgUONzRuNUoAjz8DTr/F2C/FbWrexF2r76I53Mx5Y84jrIZ5ctOT7O3ci47OtLxp/PmkP7O2YS0Prn8QMBq4H1N6jMWRC4IgJJ+YqvG3N7dw7/s7CHZbyy9JxvrW3nw22b770zZZQtN0FFlC1XV6W86/rwtUl7H0bo+zPHYicY2iTBd3XDGTicWZA3lbgtC3xbfDG78CfQCFh2SbMXtLjQ5dXJ/JqYTvpkEhxAQh7vh1o2k6o69/ydQxd95ylqnjJbQVD8P/rjn8PkXToXZV789NPA8ufdD8uBJIIBbgtP+eRluk7bD7VWZVsrNt5/6iLzbJxpPnPEllduVwhCkIlhB3/AZG3PHrn1te3sid726zOozD8joV1v3qdKvDEFJJ1SdwzyKro+jbhHPgsoesjiIpiHYOJltfc/iTcaEPG1/oe59DJX0AG543L5YEtax2WZ9JH8DW1q1dKn3G9TjvVL0zhJEJgiCkplfXmdemaagEIiobatqtDkNIJUvusjqC/tn8itURpA2R+HVTmuWxOoTklj2q730ch6l0mj3SvFgS1Ah//6pXuXuplFruFwv/BUEQBqo8J/GP7RJQmjWICtmC0F3xdKsj6B93ttURpA2R+HWT7XUwtyLLtPEund2zRH9KW/B9KJpm/FuygSev6/P5E+Dc28G5bx2fpBx4zu6Gc/46LGFaaXTWaK6edjU2yVhiOzFnIpVZXadvKpLCTcfcxOkVB6b9nF5xOgvLFw5rrIIgCKng+jMnkutN7LL2Xzymggy33eowhFQy9xuQWWp1FH372ptWR5A2xBq/Q9jTFODiOxfT0BHDoUBMBZsEkW4fl4xR1lnXwalATIeoBqUZdl75/kn40/WPeMMmI+nz5kLdeqOAS3Y5lMwwno90Go3f88ZBwwaIBqDkKLCnTyGcxlAj7dF2RmeOBmBb6zZiWozqzmrml8zff8dvb+deJCRKfCVWhisIw0Ks8RsYscav/+KqxqbaDpZsb6K6LURrIMKFR40gEI3TGoyhSBJOu0xdR4SYqpLjduJ2KhT4nazda0zBLMp00RqMMbM8k52NIXJ9RjK5ak8LuT4Hm2o7aOyIMGtkDsdW5vLsymryfU62NQQ4bUohdkXm2eV7Kch0Mak4g1kjs/lwexMzR2RRlCnu9glDZNdHsOUt2PwyOP2QMxb2fAilc0DSQdPA4QKHH8rnGRWPcsZA9XJw5cCOtyEahJKZEGqBhs3GOKOOg9o10FkDHfWADnaPcVKcMxrq1kDRVGjYCO2N0FEFxdPAlQmBBuOc8NSbrP50kspgj5Ei8TuE/3tmJf9ZuveIX68AT3zrGGaNTJPb1xtehFeug6yRcMn9xoJiMJq7K3ao3whrnjDu9EU7oX4TjD8dNBVWPAS6avTzG5sEi5CHSEyLcfequ3l3z7t4HV6OKjiKcyvPZWTGyP3PL967GIBjS47FrqTpRYXD0ONxAosXo8dieI87DtnptDqkhKVrOrs3NFO9uZW8Mh+jZ+Sj2K2fBCISv4ERiV//NXSGueHZtbSGYpRlugnGNcYWeDlrWgnrq9vZWNvOkm1NVLWGkGWJPI+TY8fmsrGmg0AsjqpCpsvGsWPz2dMc5KMdTYzO9RCIxtneGMTjUFAkiWAkjsdhoyUUJRpXyXQ7Kcp0cHRFLtWtIZqDMdx2mallWehAgd/JwgmFZCf4HUkhSYXb4KGLYO8Ko6cyulG1U9eNyp2RfetK7S5Q3JBTYSR+DRuNZM/hhXgUtMiBMRWXUYFdtkOw2TiHk23G/xQ7xMLGeN4CiHRAoB60gyqE2jygOCAehjEnwhWPD+MHktxE4jcEpt3wCu2RwzSbHIDvLxrL9xaNM2WshPX0N2H1o70/VzgFpl4Cb/yyf2PNvArOu9282JJEMBZk4ZML6Yx1dtkuIfHrY3/NKSNP4aqXr2JTyyYAxmaP5aEzHsJjT/x1K8NFj0bZ9YWrCK0yigc5KiqoeOxRlKwsawNLQLqu8/xtK9mzsWX/tox8N5+7bjYur7UXFETiNzAi8euftdWtnP23xVaHcUg+h8Jj35jPlFLRzkEwUeMW+HsS/DmV7fDLRqujSAqiqqfJPt3VbFrSB/CXN7aYNlbCWv3YoZ+rWwtv/6b/Y61Mz3K+j298vEfSB6Cjc9vy23h156v7kz6ALS1beGmHuW1Hkl3HW2/tT/oAojt30vrMs9YFlMD2bm7tkvQBtDeE2LQk8SsfCsKR+NETq60O4bA6oyr/eGer1WEIqebNX1sdQf9oMdi91Ooo0oJI/Lpp7BiGZpUpp4+7xgNpAKprh+6km8Jao62HfK4z2tlrUtgZ7bktnWmdPT8PraPDgkgSXzQU73V75BDbBSHZBaKJ/93uCCd+jEKSCTZbHUH/tR/58iqh/0Ti181pU4pMHe/4sbmmjpeQ8icc+jlXJkw+v/9jFU035panmSsnXolE7+/70gmXclrFaWQ4MvZv89v9nD5KNPo9mH/RIpTcA79vksdD5rnnWBhR4iqflIM3u+v6R5tDZvzcQosiEoSh9f1FY60OoU9XHC3a9QgmO+FHVkfQf1MutDqCtCDW+PWiti3E8b9/i6g2uHGOq8zhwa/OQ0qHRObfZ8Gej4xFvSdeD8F9c7Vnfcko+LL0n7Dmv8a2aCeEWyF/PKiaUTVK0qHyNLjkAZDT83rEpqZN/PT9n7KrYxeKpFDqK+ULk77AhWMvRJZkdrfv5qnNT6Gjc/G4i/cXfREOiO3dS8vjT6BHo2RdfBHOysq+X5SmAm0RPn1lJ7Xb2sku8jDrjApyir1WhyXW+A2QWOPXfw8v2cWfX99EMKrhsktISBRlujljaiHbG4Ks3N3CnpYg8X3HfpsskeW2E4rFiarGuZJDkSnPcdPYGaUlGMOuSGiavv/5z0iAdtC/HTaJXK+TmKoRiKo4FIniLDduu0Jxposr5o7k2Mpu7Y8EwQzrnoenvmgUYOkXySj60u/9B0lxwbc+hLwxw/Pzkpwo7iIIgiCkDJH4DYw4PgqCIKSPwR4jbWYGkyr+9e42fvPyRlPGuv2yGZwzIwmaZw6GGodHL4Otrw/sdZIMBZOMNX3tVTDhHDjzD+BIj0qVd626i8c2PYZNtuGxeagP1jM5dzLBeJAdbTso9BbSEm7BZ/fx7Rnf5szRZ/LYxse4d+29AHx58pe5YuIVFr8LIRnsXtfE4v9uJdgWZdzcQo69qBJZSc8760J6qmoJ8pX7P2FzXd9ro+0yxAY542egZo7I5KlvHYsip8EMIWH46Dr8bSa07LA6kkPzFsBXXoFcccdvOIjEr5tYXDUt6QO49rGVqZ/4vfO7gSd9YBRyqVt74PHKh8CTDafebF5sCeq1na/x95V/77F9ae2BqladrcYJSnO4mZ998DMkJH6z9ECF1N99/DvG54xnVuGsoQ9YSFrhQIyX71pDfN/c9dVvVeHPcTFjkVhPJKSP7z22sl9JHwx/0gewYk8b976/jatPENPTBRM9993ETvrA6PH36OXwnY+tjiQtiEu+3azY3WZ1CMln6xvmjbUzcfssmWlZ3cCmZmm6xmu7Xus5Tq2Y4iUcXsOujv1J32f2bm61JhhBsMjyXS1972Sx51ZVWx2CkGq2vWl1BP3TuMlo+i4MOZH4dTO1TDRPHbCR880bqzQ97l5NzZs64NcsKF1gyjhCeskt8yHbuk4fK6zIOMTegpCaJpcm/nd+4URRVVcw2Yi5VkfQP1nlYHdZHUVaEIlfN26Hwpfnm1ct8aenjTNtrIS18EYoOcKELaMM/MWABOPOgJN/bmZkCeus0Wdx5cQrcSpOfHYf+e58AMZnj6fcb0zBK/QUYpftZDozuX7u9Vw07iKumXENXrsXj83Dt6Z/i2NKj7HybQhJwJPhYNGXJuHNdCDLEuOOLmTGKSOsDksQhtVfL51BYYaz7x0tMjLbzTUniWmegskuugfcOVZHcXg2D1z2iNVRpA1R1fMwdtS2UtceJBzXkCWNUEQlHFHxeOx47Apo4Pc6aeyIEAhHsTtsKJKGrikUZ7mYOjJ/2GO2VDxmlP/VVLA5IR4GxQHRAEgKONwQj4CsGI8lyWj/AKDGDvw7jaiaiiRJyJJMTIthl43P4LN/q5qKLMldWoJouoau6yiyYlXYQhLSdR1d0xO+qIuo6jkwoqrnwETjKp3hGKqmI8sSNkUmrmn4nXZUTcemyNgVmZiqEYzECMdUsjxOZFkiHlfpjMbxuxxG11VdpzUURZEl/E4bbeEY+X434ZiKqmpEVZ24ppLpciLJEpquIwE2RSYcjaPIEm2hKLk+F7YE/70Uklw0BB31RvE82Q6SZmyze4x2WqFOCLZAyWQId4IaApsLdECxQbgdZNuB4nvhTgg1GRfvI+3Gdkk27tqF2wEJnJnQtgs8+RAPgivbOB+MBY19FbtR10Hc6RsQUdVzCLSHohx10+vEB5kT57oVPr0hTZpsv/ZLWPuUkcCpUeOXW9cBGewO8BUafxjCHcYfhWgHaDHj+dxKGHsKTDzH3GmjCawt0sZz254jGAty1uizqA/Wc+eqO3HZXFwz/RpWN66mqqOKcDzMno49jMkewxUTrqDQU8jfV/ydZXXLWFC6gKunXZ0efSKFQZMkCUk5/HelsaqTbcvr8WU7GT+3CJtDXFwQUseSbU38e/EOQjGVWFwlGtdx2GWqW0K0h2O47Qpep426jgjBaBxNA69DIcvrwO2QicV1dF2nqTNKXNOJq9r+8wSPXSKq6qgaZHvtnDgun493NNMciKLpENd0JHRimtHXT5GNQ6SmG/+eOTKbf35+Fnm+xL0rKSSpPZ/CA2dBPGR1JL2Q4cxb4eivWx1I2hB3/HpRcd2Lpo3lUmDjb84ybbyE9MA5sOM9c8a64G6Yfqk5YyWocDzMxc9fzK72XQC4FBdhte9FzV67lzJfGZtaNu3fdlzpcfxj0T+GLFYhfezd1MJzt61E04xjQum4LM7/wVHDHoe44zcw4o5f//z30yp++OQqq8M4LLsiseznp5DpSb/ZL8IQadwGfx/+v+MDdsx34dRfWx1FUhjsMVLMLejm3U11po4XVk0dLjHteN+8sZakfhLzXtV7+5M+oF9JH0AgFuiS9AF8sPcDVC0dvmTCUFvzTtX+pA+Myp8NezosjEgQzPOv97dbHUKfYqrOS2trrA5DSCUvfN/qCPpnyZ1WR5A2ROLXjdMmpjZZKg3W+dlk82ZYS5IkpnoKppB7mQba2zZBSEa2JPku28VaP8FMtiSZOiyJ7/1wEZ90N/PG5Jk6Xo47DRLJieeaM46kwIIfmDNWAjuu9Dgm5kzc/zjDnoHEgZOSg/99sBxXDrMLu97dP6PiDGTxB1MwwfRF5dgcB75Lo6bnkVviszAiQTDPd04ae4i/rInD61A4Y0qR1WEIqeTcv1kdQf+c+FOrI0gbYo1fL+JxjWNueY36zsFNoTt6ZCZPfKtn77WU9On98Mm9oGkQ7YRwq7FyXZKNqlG5o8Duh1AzhJuhs+FAtc+KBTDmRBh7KuSPt/iNDI+IGuGNXW8QjAc5pfwU2iJt3LX6Ljx2D9+Y9g1WNayiurMaXdfZ1raNyqxKzqs8j0xnJk9uepIP9n7AKSNP4ewxZ1v9VoQU0tEcZseqRnzZTiqm5SHLw3+qLNb4DYxY49d/W+o6ePCjXURVlbiqE4jE8bvs7GjspLEzit9pI8drZ1tjkLZglLiqketzUpjpwmNXiMQ1AKpagkTiOnFVpS2sIgHl2S6agjFiqk55jpvzZ5Tx+oZaalpDqJpRTVSRJQJRFVkChyIbBWI0HZdNZtGkQm6+YCoeh6i5J5isbS/8ayF0DmYasQ2IDz4WyWb8T9u3xMXmgUsfNAr8Cf0y2GPkkCZ+kiRlAfcAUzCKwn4F2AQ8DlQAO4FLdF1vOdw4VhzY2gIRLr/nQzo6wzQENKN1gxtkWaEzoKIrEFdBAcpy7YRUnZa2OJoOXhfMqyzg9s/PTp9peGocAg0H2jfUrAanF0afCE1bwZVhlAYOtRr/q10HigSjFxqvyyoDV6bFb2J4heNhArEAue5cABqCDYTiIcozyvfvE4lHWNO4hhJfCT6HjwxHBsFYkIgaIduVbVXoCUVtbwdJQvH7ezwXq6vHlpuDZEu/k6lAWwRJgkg4joyE3WXD7lSwOw89CyEeVYmGVTwZjmGMtKt0SfyS+fiYrDRNZ0djgGyPHZsis6c5QH1HlNH5HjRNZ+n2FsYW+nDYZOrbI7gdsvGapgBnTiuhPRSjIxSjJRQj02lnbXUrGS4bqg6b6zq5bE45eX4nb26oJcNtZ1Sel7q2CHabhMMmo2kwrtBPZySOx2EjHFP5aGsDLeEIR1fkM7aw598wQTBF3QZY+Rh48kBRwJ0LsXaj0nqwFSacDqF2+PB2cGZBwXij5ZY7B3Z/aFRs9xeD02ecz5XNgk2vGYlb/hgINkGg3mgRoUYgFjYu/jfvgJKjwOGESADc2YAEgWbw50EsACdeD570Ov8bjERP/B4A3td1/R5JkhyAB7geaNZ1/RZJkq4DsnVdP+w93uE+sB1986vUd5pwZQO46ZzJXHVshSljJaydH8BTXxvk1SRg1pfhnL+aElKie3zj4/xl+V8IxAIcU3IMoXiIFfUrACjyFPHs+c/y8IaHuX3F7V1eNz1/OpuaNxFWw5xYdiK3nnArbpvbirdgOV3TqL3xV7T+978gy2RffhmFP/sZkiQR2b6Dqu9eS3TrNmyFhZT8/vd45821OuRhEWiN8NKdq6nf2bMwi6JIzD57FLPPqOjx3PoPqln81BaiYZWyCdmc9vUpuLzDv+Y2jRK/pDw+JqtVe1q58t6ldITNObYPBb9L4c0fnEhBhuhrJpgk3AZ/HJ+grRwOUjwLvvGW1VEkhYSt6ilJUiZwPHAvgK7rUV3XW4HzgAf27fYAcP5QxXAk2kMx05I+gF8+v860sRKSrsOz1ww+6QP49D5o3Dr4cRJcXaCO3338OwKxAAAfVn+4P+kDqA3W8ov3f8HfV/y9x2tXNazaXwX0nap3eHjDw8MTdALqeO11Wp94AlQVYjFaHvwPgQ8+AKDu5puJbt0GQLyujprrr0fXNCvDHTZL/ret16QPQFV1lv5vO017O7tsD7RFePfRTUT3lSGu2tjC8ld29TaEYIJkPT4ms+8+uiKhkz6AjrDKDf9ba3UYQip54YeJn/QB1HwKgUaro0gLQ1kVYhTQANwnSdIKSZLukSTJCxTquv5ZllALFPb2YkmSrpYkaZkkScsaGhqGMMyu1tW0DdvPSgnRALSaeIJY9Yl5YyWo7W3bUfXDrx/d2LIRnb7vxm9tTf1E+VAiW7b03LZ5S6/Pxaqr0YLBYYnLak17A33vU9018WutC6Kperd9+h5HOGJJeXxMZrubk+P3f211u9UhCKlkbxLNBqhJ7D6bqWIoEz8bcBTwT13XZwIB4LqDd9CNeaa9nt3qun63ruuzdV2fnZ+fP4RhdjVvVO6w/ayU4PRB+XxzxpJkGH+6OWMlsOn50/E7Dr+W4/SK07HLfU+zW1CaJsWDeuE7rtt7l2W8C44FwHv8cV2ecs+cieJLjwqVI6cc/m+YYpcpHdd1fWhBRUaPaZ0jp+SYHpuwX1IeH5PZ3FHJ8X0+Y2qx1SEIqWT65VZH0H+jTrA6grQwlIlfFVCl6/rSfY+fwjjQ1UmSVAyw77/1QxjDgEmSxLeOrzBtvGXXn2TaWAnr4n/D5AuMxcL2buvNZLtR8MXmAlfWIXq17FtAfNG9+xb+pjaP3cOdi+5kbtFcRmWO4tqZ13LtjGvx2Dw4ZAenV5zO92Z9j3tOvYcMRwZgtHgo9hRz9dSrmVU4izGZY/jR7B9x9uj0rerpnjGDkj/cinPSRFxTplD65z/jGm9UhS382fVkXXYp9pHl+E8/ndK//NniaIfP7DMrmHlKOe4MO7JNQpKMNfo2h0xBhZ+zvj0Nb2bX3k52h8I5351O2YRssos8HH3OKKaeUGbRO0gLSXl8TGZ3fP4o5o/OxWmTcdtlHBZ1WvI5bZRluRmR7erRXuL4sXn8+LT0qGwtDJMTfgIj5lkdRd9OuwWU9CvCZoWhLu7yPvA1Xdc3SZJ0I+Dd91TTQYvXc3Rd/8nhxhGL1wVBENJDGhV3EcdHQRAEYUAGe4wc6vT6WuDhfRXLtgNfxrjL+IQkSV8FdgGXDHEMA/bc8j1894nVpoy17bdnoljQC2tYhdvhoYug6uMD2yQbKHZwZoAahngYCqfBWX+Chy82yv4igcMHGcWQMwpmXAmTTGoGn+A0XePxTY/zxq43aAw1ElWjlPnLKPOV0Rxu5ujio7l47MXcs+YeXtj+Ajo6+e58JuRM4IuTv0iZX9yNEQYuFlVZ+fpuGnZ3UDYhh6knlFK9tZV171djdynMWDiC7CJv3wMJZkjK42Oyag1EOOO296lpj/R4TqLnnNoCvwOvw8bOpmCv8239ThldlwjGVLRuO8gS2GQJuyIhSzLhWJy41vNnyIDPqdAZVdF1qMj18Or/Ow6HXdz5EEz00IWw9S0OMXM8MXz9PSidbnUUaUE0cO9FxXUvmjaWIsG2351l2ngJ6W8zoXm7OWNdfB9MudCcsRLY7Stu5+7Vdx92nwnZE9jYsrHH9gJ3AS9e+CIumyj5LQzMK3evYdvyA8VAJswrYtPHdej7zlydXhtX3jTfkjYOn0mXO35mEXf8+mfqDa/QETl8Ua1EkO9z8skvFlkdhpAqHroYtr5udRT9c0OrsS5BOKyEbeeQrG55aYOp46mJn1cPTqDJvKQPYPXj5o2VwJ7f9nyf+/SW9AHUh+pZWrO01+cE4VBiEZXtK7pWgNy2omF/0gcQCcTZtbZpuEMThCEVV7WkSPoAGjp73pEUhCO2/W2rI+i/9c9ZHUFaEIlfNzPLs6wOIbk4vJj6NfIVmDdWAstz5/W5j1069F2X/rxeEA6m2CScnq7fKYe7Z4ULT6ZjuEIShGFhU5LnVEfc7xBMlUwzg/LGWh1BWkiev4bD5LQp5pZSXjAmOUpIHzG7C475Tv/39xwmYckohQU/GHxMSeD7s76Px+Y55PNum5tvTP8GitTzxPy8MecxOW/yUIYnpCBZkTnmokrkfWuO7U6F4y8fT27pgTYXo2fmUzY+9SvrCunntMm9tkRMOFccPcLqEIRUclaSVLR250LhJKujSAtijd8hfOXfH/HW5uZBjfH0t+Zx1Mg06QvYsAnevBnq1oKvEMaeBtEO4wqOZIMdb8GxP4D8sbDpFfjob+AthLLZkD8BZMXoB2hz9v2zUkR7tJ01DWvQdI2GUAMVGRWM8I9gc8tmpuRNIdOZSVukjdd2vobf4SfTmUmuO5dx2eOsDl1IYoHWCE17OykclYHTY0fXdGq2tWF3KuSXH76/5HAQa/wGRqzx679PdzVz8wvrae6IICkyGS47xVkuRud5WbO3jdIsNzVtYeKaxg8WjaM5GGX5zmZeXV9PMBIlFNexKzJnTS1mUkkmkZjKhtp26jsj7GkKYpdlppT40ZEoyXKT4baj6zrBmMqWug7CMY3t9R00h+KcMbmAqArnzSjh5bW17GgMcMM5k5lQnGH1xySkms4GeOlH0LQdWndBNAi6DKhGL+ZoAPQYIBstuLQoRiEYGTJLoaMRtNC+522gxQEN7D5jW6wTZAc43EYCF+6AUMO+MfblGLIL7B6ItBjnhLICasT49xm3wtFfseSjSUaJXtUzaZ01tWTQiZ/LlkaTNiKd0LgJcivhkgegeiVsfAF2fwiZ5VBxPLz0Y2jYCGNOhoJpEAtA626oXQNOv7Ff7mir38mwWdewjh1tO7ho7EW4D+p/2BZpY1vrNrw2L+3RdsozyinxljAiYwS1gVqW1ixlWv403Db3YUZPTZHt21Gbm3HPmIHW2Ul4/XqcEydiyxZ3qfoSi6hsX9mAbJMYNS0Pm924myzJEiVjswDQNZ3aHe3YnQp5ZenR8F5IH1keOzFVQ1IkKnK9XDSzlKdX7uGlNdX4nQqqptMRiRGP67y3pYHtDUFq24IU+J2cNKeUHY1BOsJxNtV1sL2hk6ZAlPFFGZRne5hWksmupiAxFVRd482NdWS47HgcCrVtYfL8dnY0hijNdvGlY4tZtquFYCTOL/+3jrim8cVjKhiVLyrqCkPA4QN/CVQtAzUOug6KAppmVFy3OSEWM5KwEXNg73Jju+KC9hrQ40Zi5y8xZm0F6iDUCrGQMTfZVwK6CuEmCHcCMePn2jIg3m78WwtDJAzYjdfI+5K/vAmQXW7Jx5KuxB2/Xky/4WXaIpopYx0/NocHvzrflLES1iOXw+aXzBlrwQ9g0Q3mjJXALn3hUtY3rQdAkRTuO+0+ZhbO5Ocf/JzntvW+wHle8Tw+rv0YTdfIdmZz96l3MyFnwnCGbamaG2+k9TGj+I+tsIB4axtEIkhOJ6V/+iP+RaIS3qHU7Wzn2T8tJx4z/q7ZXQqfu252l9YNkVCc//1lBQ27OwAYc1Q+p319CtIwV1kTd/wGRtzx658b/7eW+z/aZXUYh2WX4bUfnMioPJEACibZuxz+dZLVUfStcBp8632ro0gKoqqnyaJxzbSkD+C9LYO7a5jwNNW8pA9g8W3G1agUtqR6yf6kD0DVVX710a9Y1bDqkEkfwJKaJWi68d1sibRwx4o7hjzWRBHeuHF/0gcQr6uHiFH9To9EqPvdLVaFlhQ+/O/W/UkfQCyssvS5HV32Wf9+9f6kD2Db8gaqNrYMW4yCMJQSPekDiGnwh1c2WR2GkEqe+qrVEfRP3WqoW9/3fsKgicSvm1A0OUo+J4y4yaWnddVIJlPY9rae7S/aIm00BBt62fvQ6oJ1ZoWU8OL19YN6Pt11tvT8Pe1sCXd5HGjruU9v2wRBGDo1bSGrQxBSSTiJLt6Z2RpMOCSR+HWT6TG3cXHKf8AOj7nlgnPGgJLaS08vHHthj2qdZ4w6g/kl88lxHboKrFPpWvjm7NFnD0l8icgzdy62wkNX5cs455xhjCb5TDy2Z7Xiicd03TZ2diGSfGBap9Njo2KKaBsipIZck4/tQ+WKuWK9k2CiGZ+3OoL+kRSYcJbVUaQFscavF63BKDNuet2Usbb/9sz95dNTVrAZbpsBkTbjcelsY2Fww0Zj8bCsgCSBGj3oRQd/JrrxSz9iLlzxOLhSv6rZmoY13PjRjbSEWzhr9Fn8cPYPAdjVvov7191PTWcNkiTRHmlHlmSm5E3h4nEX879t/2NH2w5OGnESF4690OJ3MbyiVVU03XsvalMzmeecTXTXLoKfLsc9YwY5X/4SskP0nzsUXddZ8fpu1r23F0mWmLFwBFNOKOuxX9WmFta9vxe7Q2HGonJySoZ/rZFY4zcwYo1f/2iazjG/e4PajgPHIZsE8X6eAn12xOpt988O8Vo/x1JkULutKFGAn58zia8cO6p/gwhCfz33XVj+gNVRHJorG770EhSJdg79MdhjpEj8BEEQhIQhEr+BEcdHQRCE9CHaOQyBu97Zyu9MWmC985Y0uXVdvRKe/CK07DzyMYpmwBeeBm/q9z58Zccr3LzkZtqixl1Sh+xgQekCfjznxyyvX84dK+6gJlCDvu/6sk22YZNs2GU7Z44+kx/N/hEuM6fYJpHQmrU0/PWvxOvryDjnXHK//rX9lScjO3ZQ94c/El6xAgDXpInk/+AHuCenX8P7LcvqWPn6buIxDVmRUOM6uaVe2htDoMP0RSMYN6fI6jAFYdjc9uZm7nhrK1F14Be8bftu68U1HUUCpJ537bqT6P0OIRjLQHRAliXOnlrMHy+Zjl1J+cUhghUe/hxsec3qKA7vlJvg2O9ZHUVaEHf8uonHVSp/8Ypp4xX6HCz9xSmmjZeQYiH4QyVEOwc/Vvl8+Ip5n38iWtu4lstfvLzX50p9pezt3NvnGFdOvJKfHv1Ts0NLeFowyNaTF6K2tu7fVnTjjWRfdim6prHtjDOI7drd5TVKTg6Vb72J7EqfRLl+VztP3rLs0GedABJc9ONZFI3OHLa4+kPc8RsYccevfz7a1sjl/1pqdRiH9N2FlfzglPFWhyGkmnd+D+/81uoo+ufndWBPn+P0kRLtHEz29Iq+T7oHoq4z2vdOyW7vcnOSPoDdH6V8O4f3qw7dq6Y/SR/Ae1XvmRVOUgmtXt0l6QPofPddAKI7d/ZI+gDU5mbCa9YMR3gJY9fapsMnfQD6vv0EIQ089vEeq0M4rJdW11gdgpCKVj1mdQT9t/YpqyNICyLx62bBWHOr2CkpXtcFgNxKuhZrGQR/iVEIJoWNyRpzyOc8Ns+gx0hljlGjQOlaEdVZWQmAvagI2efr+SK7HUdFxTBElzj6W5TFiuItgmCFo8qzrQ7hsCaVpH5RM8EChVOsjqD/KhZYHUFaEIlfNyVZHirz+nfy3R8fXneyaWMlLH8hnP5bBp38yQ645EFTQkpki0Yu4rwx5/XYnmHP4LcLfss5ow/fmqDcX86PZ/94qMJLaPbCQgp/fj2yx/gd9cydS+7XvwaA7PFQ/OubkPz+/ftLHg9FP/85tvx8S+K1yujp+UxaUGK0Z5BA3ncFypPpQJKMaysTjilmzFEFFkcqCMPjqmNGMqU0MZOrAp+T688UFQ2FIXDhXeBIzO99F3kTIbvC6ijSgljjdwh1bSGuuucjtjSE+Gz9tleBqAoxINcNkbjRbzyuwWdtjiXAa4NL5ozkl+cl0ZUWM0SD0LAJogGjCXvmCNizFEbOA4cP9n5qNHwPt4HiAqcX2vca+3kLoHSG0fohTbRF2tjRugMdnWJfMbmuXOyK0WuqJdxCW6SNukAdcS3OjIIZNIebsck2in09e7KlGy0YRO3sxF7QM3HRolHU5maQZRS/H9nttiDCxBAOxACw2WUiwTjeLKexTQeXLzH7mok1fgMj1vgNTFVLkOrWEC67zI7GIDWtAbK9TipyvXSG4/jddnQdattChKMqiiJRmOFmYnEGcV1jW10nYwr82BSJ9dVt1HeEaeyIgC5RluNi9Z5WvA6FuWPyGVPgY0tdB8FIjD0tIdoCERqDcU6ZVMixY/L4dHcruX47lflJcGIuJLfqVbD5VWjabrTPyh9r3A384DYomATBRqMNl+KEQKNxW6hgCsg2yCiCpm3GdrsHdA2qlkHOaHBng91rtO/yF0HxFNi9xBgrowxCTcY5XjwC9Zsh2g5lc8DhhuoVxs+7+B7jZwj9Ito5DAFN05nw85eIDvKjOXlsLv/+6jxzgkoGDZvg/nMhUIuRAstGgyPFY0zPkxUoPQqKpkLdBmjcDLEgZJTC8T+Gcaem/DTPz6iaynPbnuOj6o84tvRYxmWN49FNj5LpzOQrU75CQ6iBT2o/ocRXQkOwgXx3PseXHY+qq7y15y0C0QALyxeS5cqy+q1YIrh8BeF16/DMPRrXuHFWh5PQ6ne1U7u9jeIxWeSXG3dDa7a2su6Dvfhz3cxYVI7TnTgFnkXiNzAi8eu/f7yzhdvf3Eo4ZlzOddkkvC4bhT4ntR0R2kIxdB1yvDb8TifheJxsj4MCv5MPtjQS1yHf52BknoedjUHcdgVFhkBUpSUQQ9V0FEXCqcgoko7X5cDvsrGzoZOIBg5FItNtIxzXUPc1/dN1UCSJBZV5/PTMiYzKE9OvBZNtfAUe/zzo8b73VRzdei6bTd73M8IHNk2+CC6+N23O/wZLJH5DoOK6F00ba0SWk/evW2TaeAlr52K4/8zBjXHUF+Hcv5kTT4L70itf4tO6T3t9zibZUHV1fyuHzxxfejytkVZWN64GIMeVw6NnPUqJr2TI400kjXfeScNfbzMeSBIlt95K5jlnWxtUglr11h4+eGLL/scnXDGeeFRl8VNb929zemxcceM8PBkOK0LsQSR+AyMSv/654u6P+HB7s9Vh9Om+L83hpAliCrZgkpWPwbPfsDqKvnkL4Mdb+t5PEFU9zbamqtXU8fa0RvreKRW8ZMKas+UPQkfd4MdJcBubNx4y6QOI6/EeSR/Ae3vf25/0ATSHm3ly85NDEmOi0qNRGu/+10EbdBrvvNO6gBLcspd29nj88Qs7umyLBONs/EhUFBRSWzIkfQB/e0uc/Aomeu47VkfQP4H6wfWBFvpNJH7dhKKq1SEkp7gZCa4+xFMMEkPUxPdo5ljJQAeId52uokfT6zMYCDWu9Xis9dK8uvt+giBYIyp+FwUz6Un0fTLlPFLoi0j8ujl6dK6p4/kdaTJn+ZRfDX6M8WdC1ojBj5PgpuZNZUzmodsxSIeojjo1byojM0buf+y2ublo7EWmx5fIZIeDrEsv7bIt5wtfsCiaxDf95BE9Hk87qazLNsUuM36eWFgvpLZxhb20eklAXztulNUhCKnkxJ9bHUH/2DyQP97qKNKCWOPXi85wjCk3vjbocXLcMstvOMOEiJLEplfgsStBj/V8TrKBJENWGRROhoYtRkVPLQ6uLDj2ezDnq2BLjHVGQy0YC/KvNf9iWe0yji46mnE543hi0xP4HX6+e9R3qemsYWntUrKd2bRH2in0FnLumHOJaTGe3fosgViAs0efTXlGudVvZdjpmkbHK68QXr8ez9x5+I4TvX8OZ/uKBmp3tFFcmcWoaUaf0g0f1bDxwxq8WQ7mnT+GjNzEqXwq1vgNjFjj13/f/M8nvLa+nn11VZAAuwxup41gJM6+mi/YZXDZFeKajtsu43LYqG41ilHYFYlsj522UBxFMnr1hlWd2EF30mUJJB3sdhmnItMWPjBLwSZLaNqBffV9+4/O93LTeVOYP8bcXsKCwKu/hI9uszqKQ8seC9d8AHaX1ZEkBVHcZQjVt3QQiUXpjMeRNR1VU3EoCg7FRmMggF2x4VQkIpqOW1FoCgbI9fkJRMKUZWeTm+Xv+4ekEk0DLWZUbIoGQbEbpYA1bV+1ps++a/v+q9ghHjUSQiVxqgoOF1VTkSUZVVeRkJAlGUmS0HQNCWn/Oj9Zknu8RkrT6le6piHJYqJCf+iabvTxO3ibrh/2u/PZ8cDK75dI/AZGJH4Do2k6mqYTDEdxOYzjjixLqKq27786drtCPK6hqhq6bjy22xUikTjRuIrbaUOSJGIxo92DLMuoqoaiKAcVJtRRVQ1JktB1HU0Dm00hEIrgdTuw2YzxFEVCUWR03YhDEIZEPA5qDOIho8K6JBttt2Q7RDqN9grxqPGcw2vsq8bAZjf2sznA5jSW44Q7QXYa522BRvBmYkwglI0K7rGo8V/JZlTv1DDO99QoqHFAM84THR6IhcCdZufKgzTYY2T6nW33w5f+/RHvbDZnIfhvzpvE5+en+NSNunXwnwugcxCFWSQbXLPE6C2T4qJqlKtevop1Tev6tf/ozNH8+thf88vFv2Rb2zYkJM6rPI9fH/vrIY40cYQ3b6bmZ9cTXrcO9+xZlP7+99hLS60OKyGFOqO8ef8Gdq1rIrvQw0lXTqBodCaLn9rKuvf3YncpzD13NJOP6/r5LXtpByte2w3AzFNHMvvMCguiF4ShUd8R5sv3fcK66narQzmkilwPj109n6JMcedDMEkkALeOAjXB188d/1M4+Xqro0gL4tJ5N22hmGlJH8DP/7fetLES1pNfHlzSB0Z/mcG2g0gSt3x8S7+TPoDtbdv5xuvfYFvbNgB0dJ7d+iwfVH0wVCEmnOqfXkd4nfGZhZZ9Ss0vb7A4osT14dPb2LW2CXRoqQ3y6r/WsuHDala9tYd4TCPUEeOdRzbRXBPY/5o965tZ+twOomGVaFhl6XPb2bMxOaogCkJ//Or59Qmd9AHsbAry/x5fYXUYQiq574zET/oA3vs9xMJ97ycMmkj8ulmyvdHqEJJLNAiNm8wZK9BgzjgJbkX9wA/snbHOHtve3/u+GeEkPC0aJbJhQ5dtodWrD7G3ULe9rcvjQFuUvZtbu+6kQ/3OAyfBdTu7vgagbkdinyQLwkAs39VidQj9snav+L0TTNSw0eoI+q9urdURpAWR+HWzYEy+1SEkF4fHKNZiBn+xOeMkuLlFcwf8mkxHZo9tC8sXmhFOwpMdDlzTpnXZ5pktloAdSsnYrC6P/Tkuyid3rVYsSVA05sB3qriy62sASnrZJgjJap7JFbuHylHlWVaHIKSSoulWR9B/xUkUaxITiV83XpeNi2aaV9r8ritnmjZWwvrcg5A1enBjKA746qvmxJPgfjjnh8wpnNPrcxISCkqXx1Nyp3DvafcyJXcKEhI2ycaVE6/k6OKjhytky5X+4VY8c+Ygud14Tzieol/daHVICWv+hZVUzi7A7lQoGOnn9G9MYdzRhcw+swKXz05GnouFX5pEVoFn/2tKx2Wz4HNj8WY68GY6WHDJ2B4JpCAks1+ePYm5o7KtDuOwJhVn8OdLZ1gdhpBKvvwCOJKglclpvzMKwAhDbkBVPSVJ8ui6HhzCeHolqpYJgiCkh2St6imOj4IgCMJQG5aqnpIkHQPcA/iAckmSpgPf0HX9miP9wYmsoSPMnN+8OehxFGDbLWcNPqBkULManrsWmrcfKBkMxp082QW2fV+1cCvoGiCDpBg9/yQFZn8JzvqzRcEPL1VT+cOyP7CkZgnFnmIaQg00hhqZXTibmBpjecNyCj2FeG1etrRuIabF0NFxKA7mFM7hNwt+gy8ZruAJQhpIt+NjstI0nb+/vYV/vbeDzkgcHaMHnyxLXXrwgdHfL8/noDMSJxLX0A5xfdypGK/Vum2XMKZT5/ucjMz10BSI0twZJRCNARKKbOwgIRGNqsT3vebUSfncdVX6zOQQhsmHd8BrCVwx05UD31oMmSVWR5IW+nXHT5KkpcDFwHO6rs/ct22trutThjg+YPivaFZc96JpYykSbPtdiid/1Svh7hM50KfvCE2/HC6404SAEttXXvkKn9R9csSvL/AU8ObnBn9hQhASUbLd8Uu342Oyuu6/q3jskyqrw+jTMWNyeOTr860OQ0gVyx+G55LhGpQEN7ZaHURSGOwxst9r/HRd39Ntk3qkPzSRfbDF3Kqe6iBzoaSw4iEGnfQBrHly8GMkOFVTWVY3uJO0+mA921q3mRSRIAiDlS7Hx2SlaTpPLEv8pA/gw22ijYpgojdvtDqCftJh/XNWB5EW+pv47dk3nUWXJMkuSdKPgA19vSgZ5XhFT/sBc5o07VBO/c9elmRkafA1lbx2rwnRCIJggrQ5PiYrSQKnLTlq2UlWByCkFkcSnSt4C6yOIC309y/hN4FvA6XAXmDGvscpZ1JJlqmlTksynSaOlqDmfB3MSEQW/WrwYyQ4SZK4ZNwlgxpjZsFMirzmVZ4VBGFQ0ub4mKwkSeInp0+wOox++fpxo6wOQUglF9xtdQT9Y/fCyHlWR5EWBlTV0ypWrGG45J+L+XhX66DG+OLcMn51QZr0JYl0wIe3w87FINuhfh2occgZBZ5csLuM2aD1G6CzFjw5kDnCaNjpzoaL/w2lR1n9LobNkuolvLzzZWYVzGJH+w42NW/i/MrzUTWV/275L7MKZ5HpzOTt3W8TUo1COV6bl7NGn8W5ledaHL0gDJ1kW+NnNbHGr//WV7fxu5c2sLWhk0A4Rp7fRYbbzq7GAMFonIgKsgRlWS5OHF/Ihpo26jsiRGJx4hrEVY3WsDGLN8MhM21EFlWtIUJRlbZQDFXTKfAbF3slSeL4cfmMyvNS1RKiviPMzqYANlnG41DQdHDZZJqDEfY2h3HYZf70uWkcN67Qyo9ISEVte+GfCyCcgNOIJRtMuxQu+IfVkSSN4arq+bdeNrcBy3Rd/9+R/vBE9uVjK/h418ojfr3HBtcuHGdeQIlOcULBFGjaAcEWGHUCjDwW1CjICmx+DTJGwEkXwLa3QFONip/OLJhyPlQtg/wJRkP4NDC9YDrheJiZhTOZFp5GTVEN84rnUdVRRVgNU9VRRamvlLtPvZv6YD06urjL142uqkR37ED2eok3NyMpCkgyit+Hruk4ykqJ7NiBLTsbJSvL6nATiq7rtNYF8WQ6cbqNw0BjVQdN1Z3kFHlx+Rz4c1wWR5kc0vH4mKxG5/k4pjKPmSOymD0ql/c317O7qZOjK8rw2BTW1rQzoyyL2o4wmq5x+dxyttZ1kumxoSCxoa6TScV+9raGkHWdD7Y2Mq8ih45oHF3TiMSgIMPB1LIsRuZ5iak6r6yppj0UJxCNMSrXg99ppy0UI8/noCOmctbUQj7e2Upxppv5o/Ot/oiEVOQvhsKpULsacsdBqBniAYhGIdIGSOAvMiqyyzLEApA/GUIN4C+B9mpjm80NsSDoEigy2H2QOwrCbca25u2ABooLHC4ItRmvkx2AAlrE6CkYDUC0E7JGQdl0OONWiz+g9NLfqp53AxOAz6pvXATsAHKB7bqu/7+hChCG/4rmqOteNKNUCQBzK7J4/JvHmjRagtr1Edx/5r42DYN06m/gmO8MfpwE9ty25/i/xf+H1u3zUiQFVe9aE0JGRttXLPz0itP53XG/w5YGayH7Etm6lT3f+CaxvXsPuY/s96N1dCDZ7eR/77vkfu1rwxhh4upsCfP87atorg6g2GWOPnsU6z7YS3tDuMt+Y47K55SvTkZRhndtVLLd8Uu342OyenbFHv7f46utDqNPf7x4GhfPHmF1GEKqWP0UPP1Vq6Po2/zvwmm/tjqKpDBcVT2nASfpun67ruu3A4swDnQXAKce6Q9PRBuqW01L+gCW7mw1cbQE9fTXzEn6AN64wZxxEtjNS27ukfQBPZI+YH/SB/DKzld4fdfrQxpbsqi79dbDJn0AWkcHAHosRv2f/0Ksuno4Qkt4H7+wg+bqAABqTGPJ/7b1SPoAti1vYOuy+uEOLxmlzfExmf3kqbVWh9AvP3t6jdUhCKnk6SS54PlRbxMnhKHQ38QvG6M57We8QI6u6yoQMT0qC721QZzoDFhHnXljaXHzxkpAcS1O6LPm9kdgV/suE6NJXtFdA/wcNI3o7u4V99NTW33X79/hrtm01gWHOJqUkDbHx2QWVU26ODnEYofqFi8IRySJvk+a6IIzHPqb+N0KrJQk6T5Jku4HVgB/kCTJC7wxVMFZ4eoTxlgdQvIZc7J5Y3lyzRsrAdlkGxUZFUf0WkVSOHHEiabGk6z8CxcNaH8lLw/3zBlDE0ySGTU9r8tjl8/e636S1HNfoVdpc3xMZqXZybFmNd+XBpXAheHjzLQ6gv6R7UY9CGHI9buqpyRJJcAXMPoT+YAqXdffG8LY9hvuNQw3PLOaB5aac3fgje8fR2VhhiljJaxIJzx6Oewc5NchowS+/i74U7uXS0uohW+/9W22tm7Fb/cT02JE1SgTcyeypWULbdE2ACQkZhbMxKE40HWdL0z6AieMOMHi6BODHo3SeOeddLz+Bmp7O2ooBKqK7HAgud3YCwtxjBpFdPt2bAUF5H3n27jGpVGxpcPQdZ2Vr+9h24p6MnJdHH3uaHasqueTF3cRi6goikROqY85Z1YwavrwF5tItjV+kF7Hx2TVHopx6l/eo7a957TmRJHtsbPkZwtx2sUJsGASNQ6/zgcS+I63bIf/txYyRAG7/hjsMbK/xV2+BnwPKANWAvOAj3RdN/FWz6GJA5sgCEJ6SLbETxwfBUEQhOEyLO0cMA5qc4Aluq6fJEnSBOC3R/pDE91Pn1zO45/WmDLWx9efTEGG25SxEtoHf4U3b4JeCpQcIHHo+eYyjD4RLrkfXEkyNWGQ7lt7H/etvY9ALECxr5iTyk7iyS1PEo6HyXZmMzJjJNPyp1EXrGNpzVLao+37i8Lke/K5bs51LBy50OJ3MTz0WIyme++l7ZVXidfWGnf3vF4cZWVkXnghWRde0GX/4IoVNP/7PvRYjOwvXInv2BSvrNtNR3OYZS/uoL0pzJijCphyfGmX59W4xvJXd7F3Uwv55X5mnzVqf1sHYcDS6viYzEJRlb+9uZl/L95JJH7kd0AOdyQ7Um67zK/Oncwlc8pNHllIe3eeALUrrY7i0Ow++NaHkDPS6kjSQn/v+H2i6/ocSZJWAnN1XY9IkrRO1/XJQx4hw3tFMxZXGfuLV0wdc+ctZ5k6XsLZ9SHcd4Y5Y5XNga+l/rKYxzc+zs1Lbx70OI+c+QhT86eaEFFiq7vl9zTff/8hny+59fdknms0to9W7WX7WWehR/bV1VAURj35BK5Jk4YhUuvpms4jv1rapTDLCZePY8oJZfsfv//4Zla/XbX/ccW0PM66ZtqwxnkoSXjHL22Oj8nuh0+s4r/Lq/re0UKv/+B4xhb4rQ5DSBWPXAabX7Y6ir7Z3XB9jbG4XDis4WrnUCVJUhbwLPC6JEn/A1KyvOC1j3xqdQjJ570/mjdW1SdGc88U9/z2500Z5/Xd6dHeof2Vw1+MaX/5wPOdb799IOkDUFXaX0+PzwmgcW9nj2qcWz+tP+zjnWsaiUVFRbUjlDbHx2T34prEb+ny7w92WB2CkEq2vWV1BP0TC0HjZqujSAv9Svx0Xb9A1/VWXddvBP4PuBc4fwjjssxpU8Ti0gErMPHCtsMHttSfGlvmK+t7p34o9Zb2vVMKsJce/n0e/Hxv+zr6eH0q8WY6kZWuV039ua7DPvZkOLDZhrdRe6pIp+NjsivL9lgdQp8mFKV4MThheLmS6PvkS+3CfoliwEd6Xdff1XX9OV3Xo0MRkNUuOMrc+fXlOQ5Tx0tIi34JDpOmppz5R5BT/wT0OzO/Q5Yzq8s2u9SzrL7HdugTlQnZEzi38lyzQ0tIhT/9CXJ2dq/POcaMIffrX9//2HfiCWSceWDqsffYY8k455whjzFReDIczDt/DLJsJH8Z+W7mnDWqyz4LPjcWl9f4vtmcCsdfNg5JFlNsBivVj4/J7sZzJuO0Je73vCjDyRfmiXVOgoku+Y/VEfTPzKvA3fsxXjBXv9s5WMmKNQw/ffwTHl8xuGbur3zvWCYUZ5kTUDJY/TRseQlKZkLzTuioAZvLeKyrxr9VFba/DaEWyCyBmV805p/nVcL0y9KmsAuAqql8UvcJVe1VTCuYxrjscXyw9wM2Nm3k7NFn0xBqYHzOeNoibezu2E19oJ6IGiGqRpmcO5nJ+cOyhChhaJEIkU2b0DWNWE0NzjGV6LEorokTkXq5WBDduRM9HsdZWWlBtNYLtkfpbAmTN8K/Pwk8WDym0ljVSXaRN6EKuyTbGj+riTV+AxOMxlm5u4UX19QQiWmsrW4jElPJdNvRNMj1Ocn22Mn3O6lpD7JqdyudkTgFfhcFfheTy7I4YXw+z62sorkzSmGmG5sksaWujdV725k2IhMZiaZADJddwe9SaA3GcdllFlTmkelx8OmuZrbWdRCOaXicCtPLsjhxQiEnjhd3PIQhoMbh+f8Ha54yzsH47LqUE2w2iAcACWQHoIM7F6KdEIuBNwOiIeOCvN0HihMCdca+0TZQfMZ4agzYt1xAcoIvHyIBiLYAirG/FjXGl+zGWj6bE0pnwrm3Q7YoatRfw1XVM+18sLV50GMs2daUPolf/Sb44C/QugO2vmVM/4yHINAAm140/thIktGvRVFAi0P1Stj5AfhLoHo5jJgHJdOtfifDojnczDt73iEUD+GUnTy/9XkuGHsBpb5SltQsYXPrZo4vO55QPMSq+lXUBGsYnz2e2UWzqeqoYmPzRgp9heS506fBtux04po4kcCSJdiyc7Dl5xH85BMku73XHn2OiorhDzKBuLw2GvfEWPP2HuJRDX+ei87mCLquk1PsRddA0zSa9nQQi2n4c1yMnJxLc02AzpYIZROycbjEIUJILc+t2stvXtxAR1hFBvxOCbfDTlsojqapbK7vwOe04bBBezhOLK7jtCtsqguwqS7A0p0tvL6uhtZQHJsM3roOdjSH0DXIciss3d6CruvIskyWS6ElFEOWZHK9dp7uMH7/WoMxWoIxdN2oDrqtPkAwqjG+0E9xVuovdRCGWbhlX9IX6vZEBOKfrYfXQdv378BBVe0DB/W9jLQd9Np9tRjU9p4/T49Ax8FFlFTQQl2f14FoGHa8A8sfgYXXDeQdCYMg7vj1ouK6F80bK8fJOz9ZZNp4CWnx7fD6L8wZ67gfwcL/M2esBPVxzcd8841vEtNih91vduFsdrbvpDHUuH/bCN8Iqjqr0NFxyA5uO/k2FpQuGOqQE4La3s6uz3+eyJatxgZZBs0oyZ77rW9S8L3vWRhdYomG4zz9x+U0VXUO6HWKXUKNGccEt9/OBT88iuwi71CEeEjijt/AiDt+/Xf2395nbXUvJ6oJ5J9XHsUZU4qtDkNIFdvfgweTYKmDJw9+ss3qKJLCcFX1TBvLdw3+Tt/BdjZH+t4p2b35a/PG+uCv5o2VoO5YeUefSR/AsrplXZI+gD2de9D3dZCKalFuX3H7kMSYiNqeeeZA0gf7kz6ApnvuJd7SYkFUiWnTktoBJ33A/qQPINQRY/mrojilkBpCUTXhkz6AX7+w3uoQhFTy6OetjqB/go3QUWd1FGlBJH7d7Ggc+MlS2tNMTG71uHljJajWSKtpY7V1mXqR2uKtrYd+MhZD6xS/u58JB/q+sNC/cVL/91FID5F4crQrCUSSI04hScSCfe+TKIJNVkeQFkTi181Fs8xdYJq49cNMNGaheWOVpv4MrwvHXtiv/TIcGUjdvkF2uWvlzwsqLzAtrkSXec45SE5nr8955s7FMWLEMEeUuMbOKcTmGPyf94nHiClnQmrI8jhw2RP/lOfiWenTekYYBgt+YHUE/Vc4yeoI0oJY49eLVbubOe8fH5ky1rbfnIGiJP7BZlB0HZ64CjY8Dxzp90mGyoVwxRNp0c7hxe0v8vimxwlEA0TUCHE9zollJ6Kj817Ve1RkVvDbBb9la+tWHtrwEDWdNUzOncznJ36eD6s/ZGPzRuaVzOOc0ecgSWlxeQGA8IYNtDzxBLLDgX3kSMKr1+CoqCD7yitRfMO7Fi3RNVZ1svKN3TTs7kBTNRxuO5FgDAnw57mRFQk1phEOxNB0ncw8NxOPKaZ+VwedLRHGzi6gfFLusMct1vgNjFjj13/BSJzjbn2LJpPuiJvJoUh8++RKvrewZ6EqQRiUhy6HrS9ZHcWhyXb4/nrwi6q2/THYY+SQJn6SJO0EOjBqvMZ1XZ8tSVIO8DhQAewELtF1/bCLc8SBTRAEIT2kU+JnxjFSHB8FQRDSRzK0czhJ1/WDK1RcB7yp6/otkiRdt+/xT4chjn6b+PMXCZk0zf6eLxzFoskpPl0q0Aj3nAIt2wc3jq8IfrAeZMWcuBKUruv8c9U/uW/tfYTVcJfnPpvaqXe7cyohddkmSzLT8qbx2+N+ywh/ekxxjNXVU/vrmwitXIVn5kwK/+8XRDZsoP6vt6G2tZL9uc+R+81v7r8DqsfjNPz1r7Q9/wK2wkIKf/wjPHPmWPwuhs+GD6tZ/upudF1n5inlTD6u5xQyNaax+L9b2fxxLdFwHF2DzAI351w7ncx8jwVRp6WkO0Ymo9ZglGNveYtANHHX0LntMs9ccywTijOsDkVIFcEWuLXC6ij6dsz34dQbrY4iLVgxp+484IF9/34AON+CGA6ptjVoWtIH8LX/LDdvsET1xFWDT/oAOmvh4UsGP06Ce3778/xz1T97JH1gJHzdk77Pth9M0zVWNqzkx+/8eMjiTDQ1P/sZnW+8idrYSMfrr7P3xz+m6jvXEtmwgXh1DQ23/Y32557bv3/zfx4yqn3W1RFevZo913wbtTNg4TsYPnU723nrwY201gVpqw/xzsObqN7a2mO/T17awZp3qogEjaQPoK0+xHO3rRzWeIUuEvoYmazOvv2DhE76AEIxjUvuNmeZiSAA8KcJVkfQPx/+xWg0Lwy5oU78dOA1SZI+lSTp6n3bCnVd/6w7ZC1QOMQxDMjXH/jE6hCSzx4TP7PdqX/QW1qz1LSx1jWvIxBLj2QmsGRJl8ehZZ+ix7qu1Ql8tOSg/bt+l7SODsJr1w5dgAlk76aeMwOrNvZvG0B7Y5iYqC44HJLuGJms9rZ0b16dmNpD4uRXMFEvF5gTVhqc/yWCoU78Fui6fhRwBvBtSZKOP/hJ3Vhg2OsiQ0mSrpYkaZkkScsaGhqGOMwDrj8rSa6OJJK8sSaOVWneWAlqYs5E08Ya4R+Bx5YeU/Jck7pW/HKOHQvdCtscvE/3/SW7Hec4E7+rCSx/hL/ntvL+bQNw+ezYnak95TpBHNEx0qrjYzLLdNv73ikBOG2pX9xMGE5J9H0qmWl1BGlhSL8Ruq7v3fffeuAZ4GigTpKkYoB9/60/xGvv1nV9tq7rs/Pz84cyzC7mV5p7cfWrx5rbHiIhXfIg2NyDH0dxwJcSuPKUSS4dfymnV5w+6HHy3fncctwtaVPVs/g3v8E51rgw4Bw3jtI/3Erh//0COSMDFIXM884l+7JL9++f97Wv4Vu0ECQJJSeH4t/+FltOjlXhD6sRk3KYdfpIbHYZxS4z85RyRk3L67Hf3HNHM2JS18/E7lI44xtThyvUtHakx0irjo/J7Olrjkn49koS8I/PH2V1GEIqufodqyPon4rjwOmzOoq0MGRVPSVJ8gKyrusd+/79OnATsBBoOmjheo6u6z853FhWVC1raQ9wxb1LaO0Io4YhrIEsgU2GmAoBwAN4nKBIEI1DaxxiwPhsOGN6Bf/v9MnDGrPlOhtg70qIBqB4GtjdEO0ET7ZxzXr3UvDmQ+5oCDWDYoNQJ4RaIGc05KRHkZLPhOIhIvEIkVgEl8OFXbaj6ioSEoqk0BhqRJZk3DY3fqefllALwViQLFcWsiTjd/jTJuk7mNrZieI7cIDQYzH0eBzZ3fvFBy0YRHI6kZT0u4OlxoyFe0of/cui4TiKIhEJxnFnOCz9XqVLVU+zjpGiqufAbK3rwG2XqWuPIMsaiiQjyRKRiEZnNIYsSbgdCtk+B3ZZYdWeZtx2iXgcpo7Ioj0SpzMSIx5X0XUZVdfJ9zlpj8Q5akQ2e1qCxDQdl12hIxilPRyjNRClJNuDTZZRZGgLxwhEVPxOhZiqI0lQmOFhdIE48RWGyJZ3oX4tRMPQUQ2ZIyAWAWRwuSESNpq9h5vAXwR162DEPIiHIXckeIth2QPGcw4HeAqNwjG+PLD5YOf7oEWNcz9UqF0P2WOMf7uyoW6tMZY7D4IN4PBC3jjw5sDMS1O+qJ+ZErmqZyHwzL4TCBvwiK7rr0iS9AnwhCRJXwV2AQlXzaMjGGHmb9/p+YSOUXR7n3agPdJzt00tsOmdndz13k42/PasIYoywax8FN77I7RVgRYDSQYk4w8BgKQY0/I01djOZzOYZGO7Nx/OvxMqT7LsLQy3xXsX8/imxxmdOZrvzPwOb+95m+rOagLRAI9vfpywGqbCX8HV066mLljHqztfpSXcwgj/CKYXTOeUkacwPme81W9j2Ck+H63PP0/b00/jmjCR/B/+4JBJH4DsSY+psL1prOpk9/omckt9jJqehyRJNO3tZMeqRjLyXVQeVYCsyDhcxqHAkykOvsMoaY+RyeqBxTu5+cV17LseckiKZByWnDaZSExD1Y+sQ+1nR7reeGyAJBOOa8jAcePyuP2KWficw1FsXUgrTdvg4XMH/rrNzw/8NesfH/hrVj8KXz6CnyUcEdHAvRcV171o6ng7b0nx5O+ln8DHd5kz1uWPw/jBT4NMdPesuYfblt+2/7FDdhD9LEnuJxmZvy/8O8eVHWd2eAmt7tY/0Pzvf+9/bB85kspXX7EwosS0+eNaXr9v/f4zz6knlDJqej4v/H0VmmZsHD0zP+GmdabLHT+ziDt+/fObF9bzrw92WB3GYXkdMst/eSpOm7gAI5gk1AK/r7A6ir75i+GHG62OIikM9hiZRKs+h8cjS3dZHULyWf5A3/v010vp0Z7gwXUPdnk80KQPQEPjwfUP9r1jiml9vOsVxdiuXYS3brMomsS14vXdXW43rHu/muWv7dqf9AFsX9FAW0PQgugEYXg98NFOq0PoUyCq8fZGUaxHMNEz11gdQf901EAsiSqQJjGR+HVjS8M1UwlFEl/JgZASvlzBMJHF59AnqUcRVGOz+JsnCAlD/DoKpkqmcyrx5R8WSfSNGB6XHG1uFc60+IBnf9W8sc78g3ljJbAvT/5yl8dOxTngMRQUvjj5i2aFlDSyP39Fl8eOUaNwjR5tUTSJ66jTRnLwdYEpx5dy1GkjkZUDGytnFZCRZ0JFXkFIcF9dMMrqEPrkd8qcNL7A6jCEVHL+HVZH0D8ZZWAb+HmQMHBijV8vQpE4E294ddDjZNlh5a9TfH3fZ9Y+De/8Hlp3gxo9UMzls+ahkh1k2XgOGWMOmgYoxnZfEVz0Lxg537r3MMze2/Mej256lDGZY/jW9G/xQfUHVHdWE4lH+M/6/xBWw4zJGsM3pn2D2kAtr+16jcZQIyMzRjI9fzqLRi5iTNYYq9+GJdpffZXWp57CNXkyed/5DrJNFEToTcPujv3FXUZOyUWSJFpqA0Zxlzw3o2fkISuJdXlKrPEbGLHGr/8e/2QXN/xvLeE+eqR/1krP41AIRVVUzThaDZTMoV+X6ZRRkQhFVWQJFk0s5E+XzsDjEH/LBJM174G/TeXIShQNgzGnwheetDqKpDHYY6RI/A4hHIly6p9eZ3e78diG8Uf8s5VYdqDAB4oOzQGIAz4HdEYh2wWVZZn852sLhjVmy7XsMZI4px/q14PihM4mkHXw5Bu9/sLNoMYhswxCTaB4oPoTKDsaCs1rbJ4MNF2jPlhPljOLlnALezv2MiV/ChE1QlyLE4qH8Dv8hONhVE0lokbwO/0EYgFyXDn4Hb03305VWjgMuo6uasgOO5LDYXVICS0aiqPYZZQ+GkKHAzFc3sRpbi0Sv4ERiV//6brOproOVu1qJt/nJBCN4Xc5iUsqTW1RijOdSLJCXNVYtauFuaOy2VDfSXmeh9bOGOOK/Wyp7SDDY8fntONz2Mj2OtjTHKCpI4wuyUwuzaCqJUSO10kspvLRtkYqC3yEVZ2yHDdOWWFbYwctgRgjst343Q52NXVSnuvl6FE9e20Kgim2vAHVq402C7488OVDyy7wFkI8BPGI0VLBnb+v3ZYdtDi018Lo44wK7eXzoG4NtNVB9XJAAXeGMZ1UjYPbZ7SIyK2EQIPx2pxRxmObAutfBj1u3CDIKId40DjvW/QL49xR6BeR+A2BKb98mc7okVzf62nRhFzu+dI8U8ZKWI1b4V8nQaR9kANJ8I13oXi6KWElso+qP+L/vf3/CMaPvLDG0UVHc8+p96TFGq36P/2JpgcehFgMdB3Z76fghz8g+7LLrA4t4cSiKm/ct57tKxtwum3Mv2AMk48r7bFfY1UHr92zjpbaINlFHk792hTyyqzvIyYSv4ERiV//vLe5gav+/bHVYfTpv9+az6yROVaHIaSKnR/B/UlQKb3yNLjyCaujSAqiqqfJ2kNR05I+gDc2Npk2VsJ68ioTkj4AHR653IRxEltci/Ojd340qKQP4OPaj/nv5v+aFFXi6ly8mKZ/3QPRKOy7UKV1dFB706+J7d1rcXSJZ9Ube9i+ogF0iATjvPvoZjqae1ZLe+vBjbTUGt/Bltogb/9nw3CHKgjD5lsPfWp1CP1y5T1LrQ5BSCUPnm11BP2z9VXjrqEw5ETi183HO9IgUTNb03bzxuqsNW+sBNUcbqY9ZkaiDB/XJf4V7MGKbDxEbx9NI7xp8/AGkwQaqzq6PNY1naa9nb3s13nYx4KQKuKqRiCqWh1Gv4T66i4vCAOhJVEyFWy0OoK0IBK/bo4bJypqDdiIOeaNVTjZvLESVIGngBJviSljnT0qSa7mDYJ3/vxeyzxLbjeeo2ZaEFFiGzGx6zQxm1OhaHRmL/tld308SUwvE1KTTZHJ9yXOOtbDyU2g9bZCCrB7rY6g//xFVkeQFkTi143TpnDy2FzTxrvnqjQ4Mb30ISicOvhxnFnwhWcHP04SuOuUuxiTNQZFUpC79dmR+/FrqaDwpUlf4vgRxw9ViAnDNWkSJbf+HkdlJUp2Nkp2Nq7p0xjxz3+gZGVZHV7CmbSghDlnjyIjz0XhqAzOumZar8VbTr5qImOOKsCb5aRyVgEnfyG9iisJ6eWpbx1LhiuxK2baFXjt+ydYHYaQSr6/3uoI+ueMP1odQdoQxV0EQRCEhCGKuwyMOD4KgiCkj8EeIxP78pdFXlq1h2seXW3KWFtuPgN7H+XUk14sBP+5EKo+2Tef/AgvJsy4Cs6/3dTQElVjsJHvvvVdNrRsQEam0FNIMB4kEAvgd/iZmj+VUCzErvZdBGIBfHYfRxUexcbmjbREWijxlnBS+Ul8fuLncdtSvwF3YNmn1N9yC2p7O44RI4y7flMmE6vaix4Jk3XJJbinmnDXOUXoms76xdVUbWyhpS5IOBClsCKThV+awNZlDWxbUU9rbRBdhzEz8ymoyGDTklqC7VFyS71MX1ieEBU+BcFMDy81+vjFE3QZ3dgCLy9/93hsqX7OIAyve06Hqo+sjuLwfrgZ/IVWR5EWxB2/bnRdZ9TPXjJ1zJ23pHgT99umQ8tOc8aa/VU4+8/mjJWgdF3nuMeOoy3aNuixThpxEn87+W8mRJW4wps2s+P88/dX9OyNZLdT8dRTuMaPG77AEthHz2xj+au7emx3+eyEO2N9vt7mVLj8/44mI2/4LyqIO34DI+749c/zK6u59rEVVofRpxHZbt7/6clWhyGkime/DSsfsjqK/rlx8OdE6UC0czDZr19IkvnQiSLSaV7SB7DqMfPGSlCbWjaZkvQBvLPnHVrDraaMlahan3rqsEkfgB6L0f7C88MUUeLb8FFNr9v7k/QBxCMqWz+tNzMkQbDUXe9vszqEftnTErI6BCGVrHzY6gj6r3GL1RGkBZH4dTO5OMPqEJKLzWnueA6PueMloCxnlmljuW1uXDaXaeMlIlt+fr/2U7JFVcrPuE2oYOhKkiqIgtAfuV6H1SEIwvBTkuj8wJVldQRpQSR+3Vw0e4Sp47lS/RNW7DDzKvPGOzf11/gVeYtYULLAlLG+M/M7KZ/4ZV92KUpeXs8nFGX/P51jx5J18UXDGFVim3/BGJRe1glVTMtDsffc3n1bQUUGY+eI9RZC6vjVuVOQe3aFSThfnFdudQhCKrk8SWZR2b3g699FXmFwxBq/Qzj+d6+xu61/06IO5WvzS/nFeTPMCSjR7f4E3v89yE6o3wgt20GSOXBtQTV+sTUN4kFjk7yvtpDdCyXT4aJ70uoX/6Pqj3hkwyNkOjM5uuhoOmIdrKpfxfT86YzLGUdMjbG5eTNt0TZ8Dh9njz6bt/e8TXO4mTGZY5iUO4kRGeZeqEhUejxO2wsvEK+vxzNvHmpjI57Zs4ls3YoeDuM5+mgkm6hVdbBge5Ta7W3INomaLa2MmVlAQUUGoY4o1VtbCXXGCLZFmDC/GJfHzt5NLURCcXw5LkrHZiFZdJYs1vgNjFjj13+haJzfvryBZz/dQ0dUxy5DjteOIss0B6LE4jo67E8QtX2nR9keBVlWkNEIRnUCURUNsMnsLxQjA5/VjHHbwGFTiKoaqmoMou/7/2L6gf2zPDbyfE6qW0NkeRz888qjmFrWtb+mIAxaoBn+MhXinVZH0rv534PTbrI6iqQhqnoOkfIc96ATv5MnpFEz+OKpMPcaWPIPKJoKmWXQuBmQQFYg2glZFeAvgM566KwFhx+iQdBUCLZAuCNtEr9gLEhNoIa5RXPJdedyXNlxPL/teUZnjqbQW0h1ZzVT86YyJmsMb+1+i0xHJmub1hKJR4ioEQq9hWmT9AFINhtZ55/fY7uSlU1o7VpiNTXosRjR3bux5ebimjwZSU712+2H58lwMGJSDns3tVBcmYXdrbBnYzOB1ghOj0J2kZeMXBcbP6wmElI56vRyXB4HWz6po2Z7GyWVWVa/BUEwlabpbK5tJxLXyfUqSJKMLIFNkcj3OQjEVGJxFQkJr9OGwybR3BnDZVdw2m2ML/KR43HyxoZaonGNUyfl88aGRtpDcWwKSJKEXZaIqxodYZVMtw2XW6ItpBKPa+R47UwdkUU4qrKqqhWbDI0dYVRNozTTzeh8v9UfkZCKJAm8eRDUIRY4+AkOXYVdAVRQPKAGDzf4YcboV3BQOmsQrxcGStzx60XFdS+aNpZPhrW/TfGqntUr4L6zuv1BOULTL4cL7hz8OAls8d7FfPvNb6Pq6qDGmZQziUfOegRFVvreOcXous7e7/+Ajlde6fV5R2UlIx98AFtO+q77q93exnO3rSQW6f/3TJIO1NEpGOnncz+bM0TRHS4GccdvIMQdv/55bW0tVz/0qdVh9Om2y2Zw3oxSq8MQUsXrN8HiP1kdRd+cWfCznpWohZ5EVU+TPbN8t6njdSZovyBTvXGjOUkfwKpHjemgKezGD28cdNIHsL55Pe9WvWtCRMknuGTJIZM+gOjWrTTf/8AwRpR4Fj+1ZUBJH3Qtnlq/q4MdqxpMjkoQrPG9xxO/lQPAj59cZXUIQipJhqQPINIK8YjVUaQFkfh188raWqtDSD5tVeaOFw+bO16CaY20mjZWVYfJn32SiFX33q6gyz41fe+TyjqaB38Qba4x6YKOIFgsHEuOC4pRNfFnYQnCkAi1WB1BWhCJXzd3XCHmGg/Y5AvNG0t2pnxLh+PKjjNlHBmZU0aeYspYycZ3wvFIrsNXM80444xhiiYxjRtkVU5JgknHlpgUjSBYa05Fckz7nlqaaXUIQiqxe62OoP/8RVZHkBZE4teNzaZw+WzzTnY+vf5k08ZKWCdeB6fePPh+MYobfrjenJgS2O+P/z3njD4Hj82DTbKRYc9gXNY4HLIDWZJxyA68di+TcicxJXcKLsWFU3HiUlxI+/5fvjuff536L4p9xVa/HUvY8vKoeORh3LNmoeTm4pw6FfesWdiKi3FNnUrpX/+K/+STrA7TUvPOH82csyrw5TjxZjrILfPhzXJgdyk4PDa82Q5sTtlYmy9BbpmXiQuKcfnsZBa4Ofu703H7Re8zITU8evU8Rma7rQ7jsEqznDxzzTFWhyGkkp9Xg2Jyv+Wh8NU3rY4gbYjiLoIgCELCEMVdBkYcHwVBENKHaOcwBC75x/t8vLvdlLHuumwKp80YacpYCUuNw/1nwp6lgxunYDJ89TVw+syJK4E9uvFR/rb8bwRiAfQjKIUsITGnaA73nnbvEESX2Jr/8xBtzz2HLS+PvG9+g46336bz3fdwVlZS8IPvYy827oJG9+yh/o9/JPjJMpBlvAsWUPijH2LrrRl8Ctq5ppHlr+2ioymMpulISDg9NiYeU8z0hSOo3tLKspd20lIXRJKgaHQm884bQ2Z+Yt8VEYQj0dgR4eQ/vk37AAseDaccj53F152M2yFOzQQT3VQIWoLXTvjOp5BXaXUUaUHc8esmrmpU/vxlU8fceUuKt3N47ErY+Lw5Y008Dy590JyxEtSm5k1c/PzFpox17phz+c2C35gyVjJoffZZaq772f7HktOJHjlQxMQ5aSKjn34aXdfZfuZZRHfs6PJ6z5w5jPxPan+/AJr2dvL4bz5B13r/+z7v/DF88uIO1G4FL7KLPFx+w1wkyZrm7SDu+A2UuOPXP3Nufp2GzqjVYfSpPNvNez9NgyUiwvC49zTYs8TqKPrnxjarI0gKop2Dye56d5vVISSfHe+YN9aml8wbK0E9sekJ08Z6d096tXPofPOtLo8PTvoAIus3EKutJbpjR4+kDyD4ySeonZ1DGmMi2LW26ZBJH8CWT2p7JH0ALbVB2upDQxmaIAy7uKolRdIHsKdF/P4JJkqWpE8YNiLx6+b0yYOrhJeW/CYWGMkqN2+sBDUtf5ppYxV706u4i2PUqMM+r2RmouTkYCsoRPL0rA5rKyxE7mV7qskqPPx7zC7uvdKb3angyRQFXYTUYlNklCQ523HakiRQITnYU3/pjDAw4i9MN2MKM0wdz5EOn/BF92LOV0mCi1N/zdp5lecxNW/qoMexy3b+etJfBx9QEsn96ldwzzJarkgOBzlf/QqOigoAZL+fol/diOxwoPi8FN/wSyT3gfVqckYGxb++CUlO/V/KUdPymHBMsVGxs5vCURkcf+k4pi8agXTQR2FzypxwxXgcLrG+SEg9f/zcdKtD6Jc7vyBaSgkm+tZiqyPonxlfsDqCtCHW+B3CM8t28P2nBtdaYMXPTybbnyaFEnQdNr0C294BLQ6RdohHQVMhUA+ebCifC5JiPL/hBfAVQsFEqFkF0y+HKReAkj4nnbvad7G3Yy/ZzmxWN6xmY/NGOmOdxNU4nxv3OSJ6hCxHFnva9/Dq7le59qhraYu0EY6F0SWdE0ecaPVbsEy0qgolIwMlIwNd14nt2mXczXN3/X3TAgFidfXo6DhKS5GdSVDW2kSBtgi6rhOPaNidCvGY1qV4S6gzSjyqosZ1vJlO7E7FwmgNYo3fwIg1fv0XjWvc+/5Wlm5vYnJJBp/sbEHTJUqznJTnerApNq6YW879H2xnW0MnDpuEy25nZK6HtVWtRONxdjaHmVGWyd7WCM2BMLIsc+zoHNbVtNLQGWdkjpudTSE0LU5cg0UTC9nZGKSqLUQ0pjG6wIfHIdEe1sh22YhqGpoOs0bmcfXxo5Fl69bXCinsf9+DFQ+DzQG+EgjUGedtigMcXujYDdhAcoIeNf6NBkRA8oAexLjAbwObE2z7ZpXY7RCLQDwCsgOibYAKDh948iDYbJwL6iro+5ZmuIsg1ArEoGQWfPFZcCZRv0GLDfYYKRK/Q6i47sVBj3HS2Ezu++oCE6JJAtvegf99G9qruj2hYPzx6PY9kxTw5kOoHdQgyHY46Rdw3P8blnATgaZrPL/teV7c/iINoQZkZDKdmRR4CnApLl7d9SoAM/Jm0BBuIKbGyHZlM8I/gkxnJqePOp0peVMsfhfWCG/YQMcbbxLZtQvX+HH4TzuN0LJPkVxO4rV1qC0teI49BmIxQqvXIPu8+I4/HmcfU0VTia7rVG1sobMlwsgpuXgyek7hVFWN5a/soqM5wlGnl5OV76F6ayutdUHKJ+Xgyx5kb84jIBK/gRGJX/89snQXN7+4nlBUO2wtZbtknBPrEjgUiSy3nZqOA2sEPTYJXYJQrO/zJ6cigaYT2berRI+jITYZxhb6uOWCaUwvzx7w+xKEw1r3Ijx5hdVRHFrhNPjW+1ZHkTRE4jcEzEj6PpPrsfHpL08zbbyE9Nov4MPbzRmrZBZc/Vbf+6WAy1+8nLWNawc1xndmfIdvTP+GSRElh+YHHqDud7cM/IWSROmf/kjGmWeaH1QCeu3edWz5pA4Ah0vhgh8dRV6Zf//zuq5z348/INQZ279t1Iw8dqxsBECxy5xz7XRKxw3viahI/AZGJH7985X7P+GtjfVWh9Gn314whSvmpngLKGH4vPVbeO/3VkfRN0mGG1qsjiIpiKqeJvvHW5tNHa8pGDd1vIS05E7zxqr+1OgLmOJWN6wedNIH8K81/yIcT/D+PCbSVZWGO/5xhC/Wafj7HeYGlKCaawL7kz6AaFhlxeu7u+yzYXF1l6QP2J/0AagxjU9f2TW0gQrCMEmGpA/gdy9vtDoEIZUkQ9IHoGvQsrvv/YRBE4lfN9VtopTygGmxvvcZCD1xG+yaJRQ353sWU2OoafB57adp6OEjT3S1UHr8fsejPb8T8UjX9g2RUN/fm3gCN7sWhP5KhplNn4mryROrIJgq0mF1BGlBJH7d3HyBuZW/0uIDHn+GeWN5C4yFwyluduFs8t35gx7n3Mpz8drTZ1G0ZLeTdcklR/z67CsuNzGaxFUwMoPCUQcqFEsSTDm+tMs+U08sRbF1LSSRW9r1uzTlxK6vEYRkJEkSY/KTo43LFXNHWB2CkEoqTTw/G2pFk62OIC2INX69WLq1jkvvMefn7bzlLFPGSWi6Dq/9Epb83bhdf6SKpsHV74BsfWXB4dAWaeNPn/yJd6reIRgPous6bpubDEcGUTVKfcioRumz+YjrcTRdw6k4yXJmUeAp4IxRZ3DRuIuwyelTCRVA1zTan3+e1qefIV5Xi2PUaPxnnUlkzVr0WJRYfQNaRzueuXMBidDKFcg+P5lnnoF/0SKrwx820XCc9R9U09kaoXJWAUWjMnvs09YY4v3HNhPsiDJj4QhGz8xn44c1tNQFGTUtj7IJOcMet1jjNzBijV//6LrOlfd8xOJtibmOyGmT+O7CsXz7pLFWhyKkmgfOhx1vWx3FYSjw0x3g7nmMEnoSxV0EQRCElCESv4ERx0dBEIT0MdhjZHrdKuin6Te8RFvEnIT42hNG8sMzUrzk/qZX4NHL6FmkeoCmXJwWDdxjWoyFTyykJXLkV54lJO5YeAfHlR1nYmTJoeH2v9P84INowSCo+9agOR2gajjHjsVWWEhwyRJsJSU4R40iuGQJSk4OBT/+ERmnnmpt8MNk2cs7WfXGHmRFYtYZFYw5Kp9n/rSctvoQsiIxY1E5br+d5a/uQlU11JiOGjtwt75wdAanf30qvuzUn3YtpIeYqnHO7R+wsTZx1xHZJHj3JydRmp0c01KFJBDphN8lwZT9kcfBl1+wOoq0kBZL0AaiqTNsWtIHcPu7aVAV7/HPM+ikD2DtU9CwafDjJLjvvfW9QSV9ADo61751rUkRJY/211+n8Y470Do6DiR9AJEoxONENmwg8M476OEwse3b6XzzTaOJ+5497P3hj4g3NFgX/DDZuaaRpf/bTjgQI9ge5f3HN/PcbStpqzcK22iqzvJXd7H4qa2EOmJEg2qXpA+gbns77zy8wYrwBWFI3PPe9oRO+gDiOpxz+wdWhyGkkttnWR1B/+x6H8KJ/fuZKkTi1819i3dYHUJyiUdBM7H9wvrnzBsrQa2oX2HKOKquEjfzs08CoU+XH/mLYzFCa9aYF0yCqt3W1mNba11wwOPU9DKOICSr19fX9b1TAmgOmlwlW0hvnbVWR9B/Kx+2OoK0IBK/br50zCirQ0guNgeYWVxkwtnmjZWgpuebUzlWkZS0K+zinjnzyF9st+OanOLTroGi0T0XyGcWuE0ZRxCS1ckTC6wOoV+yPXarQxBSiTc5vvcATE+PqttWE4lfN3l+Fz4Tz6W/Mr/MvMES1efuA6Q+d+vTxPOgcOLgx0lwty+8nSxn1qDH+cuJfxl8MEkm47RTyf3mN5A8HpAP+vNlt4Mk4Rg3Du9xC8Bux15ejvfEE5FcLmwlxZTe+nvshUl0EDxCFdPyOPqcUTjcNlw+Ows+N5ZzvzuTjDwXAJIsMeOUEcy/cAxOrw27S0bu1tYhf6SfEz8/wYrwBWFIXH38GMYW+KwO47AUCZ799rFWhyGkku8kSeGnsrmiqucwEVU9BUEQhIQhqnoOjDg+CoIgpA9R1XMIrN/bwpm3f2jKWGnRx09T4elvwtonuj2hAGpvr+jJ5oYvvwylg5jKl0TqAnV8+81vs6djD2OyxrCofBFPbn6SplATdsWOx+bBa/PSEeugKdyEpms4ZAcjfCOYnD+ZM0efyTElx1j9NoZVYMkSOt99D7WtlciWrdhLSij8xc+x5+cDEKutpfW//wUg68ILsRcXWxmupWq2trLyzT3UbGslEohhc9jIH+HDneGgcFQGWlwjElQZPTOP9R9UU7+7g4wcF9GIit2hMP3kEZSOz7b6bQiCqX7x7BoeXbobNUGvd589tYi/fz5JinEIyeP+c2Dne1ZHcRgS/F8jKCIlGQ7ijl8vKq570dTxUj75e+A82PGOOWNduxxyx5gzVoJSNZVZD81C1fuZFB/CDfNv4OJxF5sUVWJrfeZZan72sx7bJY+HcYs/QAsE2H7ueajNzQAo2dmMfu5/2PYlhelk+4oGXr5r8EVsFn15EuPnFpkQ0cCIO34DI+749c8X713Ku1sarQ6jTwsn5HPvl462OgwhVdxzGlQtsTqK/rlRFBTrj8EeI8Uav25ueDb1q/6ZKtJhXtIH8NbN5o2VoJ7e+vSgkz6ARzY+YkI0yaHloYd63a4Hg7S/9DLtL720P+kDUFtaaH/ppeEKL6GsfqfKlHHWmDSOICSC97cmftIH8ObG1G85IwyjZEn6AILNfe8jDJq4r9pNvt9ldQjJRVLMHc/hNXe8BOSzmVNgwKWkz3dVch36vcoeN3q8Z1sLyZk+n8/BbA5zrueZNY4gJAJJwpR2s4IgDJE0q1JuFXFk7+Y7C8daHUJycXhg5lXmjbfoRvPGSlBnjD4Dr21wCa4iKVw97WqTIkp8ed/8hlG5sxtbYQH+U04h46wzcYw60IrFMWoUGWen+BTrQzjq1JHISv+q7EqHOAJIssSs0yrMC0oQLHbZnHKrQ+iXry6osDoEIZVMv8LqCPrPlWF1BGlBrPHrhaZpjL7+5UGP4wI2pvr6vs+seQae/hron915sUFGEUTajOmgh7TvBDV/InzlZXBnDXGgiSGuxrl5yc18UvcJC0oXcFrFafx77b/Z07EHr81LhjODbGc2bZE21jetJ6JFyHHmMLNgJmNzxnLSiJMoz0iOExmzRPfsIbB4MSg2Qp8uw1ExityvfBnJ4QBAC4XoePMtAPwLT0Z2D7x3XaroaA6zaUkNVRubaa0P4clwMGJiLg63Qv7IDOJRlXBnjFHT89i+vIG9W1ooGpVJe1MIh8vGhPnFZORZ8/mJNX4DI9b49d9Lq6q54fl1NHZGAWPKU5wjvxEoA1ov222AzSahajo6oO7b6XA/RwH+etl0zpmRBi2ghOG19N/w8vetjuLQ/CXwww1WR5E0BnuMFInfISzeVMPn71s+qDE233QaDkea3LrWNPj4X7D+WRhzEsguaNoM7nzY+T548yCjBGpXG7fzR8wDLQJ16yCzHMrnGFembOnTvLYt0kZzuJnd7bvJdeVSnllOhsO44tUZ7eS1Ha/RGmlld8duZuTNoDyznGxXNttbt6PqKieWn4hDcVj8LoafrutEd+5E13X0cBi1vR3PjBnIB00HjVbtxZaTjezxEKuuRs7IRPGl/jTig8VjKoHWKBl5LiRJQtd1mvYGsNllXF47qqrhzXR2eU2wPYokg9tn3fdKJH4DIxK//tM0nf8s2UFLZ5Sa9jAeu8y6vW2UZXtxO2VkJDLcdjbXdtAUiOB12ijJclPXHiIU16nM9xGOasQ1lbr2CFkeGzsaQ0wry0CWJHY0Bcly2ynLdLG6uo1jKvORJWgPx4jEdLbWtVPdGqIk242kG4lgtseO3SaT7XVxw7lT+P/s3Xd4HNXVwOHfne276r24yL2DG2AwNr13MIQAgVBDCZ3QwhdIQqhJKAm9JxB67713DG7g3mXL6m1X2/d+f8y6SJYtyRppttw3Tx5bs7PHZ5fVzpyZe8+1aAasiasoHX33GHxyC9izwN+kD/cItejnYcKhn3tFIiBDQBgQYMsGGYVIgM2XSDSw5YDdCb6a+HYbWJwQbQOiYM8DTx5oNgj49JFhjavicTVw5YO/GQjpRd9JT0PpBDPelaSkCr8+YGRXz8G5dj696gDD4iWk1d/AYwcZE+vo+2Hir42JlcD+/v3feeKXJ9ptEwjO3flcAO6be1+34vxp2p84ftTxhueXqIIrVrDm9DOIVFe3f0AISv52Ixl77knleecT+PlnhNuNtaiQ8KrVCJeLoksvJe/U35iTeD9bOa+OD5/4haAvQk6xmxknjOCDx3/B3xrevJOA4VOK2P/0sQjgwycWsuT7aoQQjJtRxswTRyJE/5+EqsKvZ1Th1z0fL6zm9CcS/326dP/hXLz/KLPTUFKFvxFurTA7i645c+Dq1WZnkRRUV0+DfbvC2M5fqxtDhsZLSP8zsPB47ULjYiWon2p+2qroA5BI7pt7X7eLPoCbvr2JaKz3HUKTRfXNt2xd9AFIyYbrb6D2zrsI/PyzvqmtjfAq/UAi/X6qb72VcGfPTTHRaIyP/7uQoE8fdt1U3cb7j/7cvugDkLDshxqWfFvNstk1LPmuGiTImGTBp+tYu1B1WFNSx3lP9W4ET3+544NlZqegpJInjjE7g+4JNEHdUrOzSAuq8OvgpdnrzU4h+QRbjIsVC3e9T5Jb3rTcsFgRGaE1tL05lKkluGw7J0XhMMEli7f9eDRKaOUqw3NKNAFveKsiL9C2ddfTjRqrfDRU+TrZ3mZ4bopilkCks9l4ipLi6peYnUH3/fyy2RmkBVX4dfDHw0abnULyKRprXCx3gXGxEtQeZXtgFZ3P/bQLOzat+/Mcs+3Z5DhzDMos8WXuu+82H7MUFpJ58MHbfjwvD9fEnfsirYTiyXZQNDiz3bb8sm3Pb6zYKZ+KCQWb+iwBaJpg0Li8vkpRUfpdWXZyLO9iVXP8FCNNOtnsDLpvegI3oEkhqvDrIMttZ1pFtmHxXjl/N8NiJawz3wdnbu/juHLhvC96HyfBlWWUce/+9zI6dzSW+DqIAsGw7GE8eNCD/PfQ/5Jh63ytP7HF2Xm+I5/njniuX3JOFEV/uIKcE09EZGSA1aovzqVp2IYOpeLJ/5J/+ukUXHQhjlGjyNhvX/LOOAPHmDF49prJoIcfatcAJpUd/LsJjNilmLwyDxMPGMTRl09m5K7F2BwWbA6NjDwHxRVZHHDGWMpG5FIyNJsDzxxH8ZAsSodnc8h5E8gtSa9mOEpqe//Svch2JXazNU3AZ3/Yy+w0lFRy6O2QUWZ2Fl3b7by0au5npj5v7iKEsAA/AOuklIcLIYYAzwD5wGzgN1LK7U6EU5PXFUVR0kM6NXdRx0dFURSlJ3p7jOyPy18XAwuBjSsz3grcIaV8RghxP3Am0P1uFv3gxtfn8fCXaw2J9d01+1KUneLriflb4O/DIRrsXZy84XD+12BN/SUKVres5prPr2FZ4zIisQhCCCzCglWzEo6GCcVCSCQOi4PxBeNpDjazpmUNERlBIHDb3MwaMYvfT/59j4aGJqtoUxNrzjyLwJIlaJmZuHfbjWh9PYTDaNlZZB92ONlHHN7uOeH166l76CEiVRvIOuywrR5PZctm1/Dp/xYRCkRxeKzkFrkJh/TlHewuC+5sB7FIjKYaP8G2MBabxviZ5Uw/boTZqaebpDs+JrOLn/6RV+dWmZ3GNg0tcPPRFfuYnYaSav5cBLKX52d97cTnYLRB3eGV7erTO35CiAHAE8DfgMuAI4BaoERKGRFC7A7cIKXc7n/t/ryiKaVkyDVvGRpzVaov4v6XAuOaspTsBOd+bkysBBWOhpnxzAx8ka0bavTUSaNP4prdrjEgq8S2dO99iGzYsN19ym6/jewjjgBARiIsP/QwwmvWbPH47WlR/NWv9/HMX77doedOPngwux89zOCMeiZd7vgl4/ExmT346XJuenuR2Wl0aUJZFq9fNMPsNJRUcctQCNSbnUX33NBsdgZJIdGXc7gTuBLY2E4rH2iSUm5sMVcJlPdxDj1y3UvzzE4h+RjZiXND6r//c2rnGFL0Abyx4g1D4iSycHVNl0UfQPMbm98L/7z57Yo+gJY3Uv+9Apj7/o6vhbTk267fZ8Uwd5Jkx8dk9sBnxnVT7ksL1hvYJVtRkqXoA1jzndkZpIU+K/yEEIcDNVLK2Tv4/HOEED8IIX6ora01OLtt239scb/9W0on0mDYYpG7KCFjJSpLZgZoXX9V2YpLNv3dWlSkN37ZgrWkpONTUlJ28Y43ZXFlpv4w60SQrMfHZFaSlRyNnWwW1dVTSVO5FWZnkBb68o7fdOBIIcQq9Mnq+wJ3ATlCbOplPwBY19mTpZQPSimnSimnFhYW9mGa7e0zxtiTQ4uh0RLUiEOMi3XYP4yLlaAGZw3m4IptLzvQXVZh5ZpdU3+Yp+Z2k3fmmdvdxzZgAPnnnLPpZ/uAcv3nePFnGziQgnPO7tM8E8WkAwfhzup5AadZBPv8ZlQfZKR0IimPj8ns3lOmmJ1Ct9w2ayezU1BSyX5/NjuDbrJAZupfyE4Efd7VE0AIsTdwRbxr2fPAi1tMXp8npbx3e883Yw7DCfd+wXdrejfe+IbDRvHbGcMNyijBbVgAz5wM4RCIGNg8YHWCvwnsHvDX63/mj4TsAbD2G/DVgs0FkRAUjoLjH4eM1F/Hb6PFDYuZXT0bKSU2zUYoFmJ4znBWtayiJdTCutZ1TCmewriCccRkjM8rP8ehOWiLtFGSUcK+g/bFY0uflvuhykoa//c/3NOm4Ro7luCKFVjz84k2N+PaaSeEdeteVaHKdURqqrf5eCpb9mM1tWta9TX6JLizbVQuaqJwcCaxiMThttBQ1UbtmlY82Q7G7lmGxWr+Cj/pMsdvo2Q8PiaraExy+bM/8e7PG8h2CNoigpiMAQJvKEZxhhUpBPWtYSwa5HrsOCyC9c1BLALy3BZqfFE8dgjHBJGIJCJBAjYN7PErvaGovjSDzaL/PhVk2AlFJC3BEEJojCpys3BDK754v9Ysu2CnQXncf8oUMpypP+pF6WfeBrhrJwi3mp1J52ZeC/teZXYWSSMZunp2dBXwjBDiRuAn4BETcujS0prej7OvbDBmHldSyCrXh2mG68CeDRY7NK3Ri7pQqz4P0F8PzRvAmQGaHYQFWuId1hpXQ3Nl2hR+4ViYL9d9yfza+bhtbmr9tRww+ADWtK5hSf0Svq3+lnxHPlXeKv638H+UZZSRZc8iGAmy3reehkADRc4iditPg3Ui4+wDBpB/9tn4584ltL6Ktu9/wDVlMhnTprXbzz9/ATGfF/fUqdgHlGMfkH7TpEL+COFAFKfHhrchQPmoPNxZdrIL218oyC3JYNikIqLRGIu+qWL94ibyyjLYaZ8B2BxpMV4h0STF8TFZNXgDfL6sjkBEEo5KfRlQQAqJTYMmf4RQVC/kNMAiJJVNIWJATEKNN0oMaAkCSGxAaZadJn+YaFSiaYKCDBdNbUEa/VGCUX36prchgMMC0RhIGeXHNa2bJnYCtIQkq+u81HuDqvBTjBcJQNTAXgxG64cbUMpm/XLHr7f6+4pmxdVvGhbLCixL9a6ei9+Fp08wJtakU+GofxkTK0HV+es45MVDCEQDvY61Z9me3HdAenR7937+BZUXXogMtH/fPNOnM+iRh5FSsu7iS2h97z0A7MOGMfjJ/2LNzTUjXdNUr2zh5X/+SDS8+dRSswgOOns8QyduPSywrSXEU9d/Tcgf3bRNaILjr5lK4cDMfsl5S+l2x6+31B2/7nnu+zVc+eJ8s9Po0hUHjuD3+440Ow0lVXz7ELx9hdlZdM2eCddWmp1FUkj0rp5J56mvVxgaL9L1Lsnvud8YF+un/0As1vV+SeyBOQ8YUvQBfLH+C0PiJIOaf/xjq6IPwPfllwRXraLtu+83FX0AoeXLaXz66f5MMSF88+rydkUfQCwq+fLFZZ3uP/udVe2KPgAZk3z2zJI+y1FR+ts1LyV+0Qfwz/eXmp2CkkqSoegDfWRYIt+VTCGq8Ovgm+UNZqeQfIxczqEv4iWYqjZjFxCOxqJd75QCovXbbksdra0j2rD149G6JGplbZC2llCn2/2tnW/3NnW+sG9gG/srSjKKJv7gJkAfUqooaSlizAVxZftU4dfB3ScnR+evhDLKwKGsniKwOoyLl4DOGH+GYbFcFhcWLT3mYmUffXSn27WMDFxTJuOZMQNLfv7mBywWso88on+SSyBjp5d1un30tNJOt++8z4BOt4/fq/PtipKMpg7OMTuFbhlVnGF2CkoqKRpndgbd5+j/qQXpSBV+HQghuGTfIYbFW/yX3rftT3gnPgkDDJiSkzUALkmO4Ti9Mbl4MrfueStZ9ixE/H8aGhm2DAqcBQg6X8fJItoXePnOfD791af9kXJCKLz0Ekqu/xOZBx2Ec6cJWIqLce8ylSGvvYrQNCwZGVQ8/T9yTz6Z7KOOZPDjj+GaONHstPvdzvsNZO+TR5Fb6saVaaNgQAbTjx/Onsd33mG4bEQuh/xuPBl5DjSLwJlhZfqs4ey838B+zlxR+s4L501nWEFid0EeUeTh3Uv3MjsNJZWc/xV4kmAN22s6XblG6QOquYuiKIqSMFRzl55Rx0dFUZT0kYzLOSS8cf/3Jj6Dppn987gxHLvLUGOCJarVX8OTx0G4l8tX2Nxw4WzI6nyoWiq56KOL+GTtJ0g2X3gRiHY/FzgLqAvUdfp8i7CwS8ku/HG3P1KRXdHH2SaehiefovHpp4m2tBBrbgYknj1nUH7HP9Ec+lDh+scep+m557BkZVFw0YVkTJ9ubtL9aP4nlcz/dB02u8aQnQtZObeWxg1tCE0wdOcCJh00mM+fXULVsmY0i2DsnmUMGJPLD2+uIuSPMHbPMibuP8jsl6Eohlnb4GPGbZ+YncZ2WTXBT/93AJkutaSDYpBwEP6WBAuj734pHHSD2VmkBXXHr4OqRh+73/qJoTFXpfpyDjeWQMRvTCxPCfxhsTGxEtS9c+7lvrnGLMEwNHsorxz1CkJ0Pjw0FbV+9DGV55/f6WM5J/6K0htuoOWtt1h32eWbtgu7neEffoC1cOvlDFLNqvl1vHnPvO3u48q04W9tf3VLaCC3aAZ68DnjGTa5/08Y1B2/nlF3/Lpn2DVvJkWDl0ynlfk3HGR2GkqquKkcQl6zs+ie62pSvseDEdRyDgY7+aHvzE4huTSsMq7oA/BtgHBqd3b6aM1HhsVa0byCKp+xXUITne+LbS9h4f1En/Po/eLLdttlKITvu/T43V67sOvOxB2LPmhf9AGs+Tn9OqIqqSsZij6A1kBaLAKl9JdkKfoAlrxjdgZpQRV+HVx6wAizU0gu2QP0WwVGsTrB5jQuXgIakzfGsFh5zjwKXal/F2tLjtGjtv3YKP0xZyf7OEdt+3mpJL+8666AFlvXv7P5A1SHNUXpb1YtfUZvKP0hiU7zB6XPdAwzJdEnon8cMcnYFubDClO7iMFihYNuMi7eSS8YFytB/XHaHyl2F3e537a6e26U48jhxuk3YrOk13yQnGOOIfuoI0HTYIshrtbSEkr/8md9nxNPJPOQg0HTEG43RX/4A47hnXe1TDWjp5UweloJQhNYbRqDxuVhsW/+qs8tcbPfaWNwZmz+3BQPzWKXwyqwOiwIASOmFjFuz9Sfa6ukj9tn7WR2Ct3y9Nm7mZ2CkkrO/tjsDLonZwhkFJidRVpQc/y2YfbKWo57YMeHhrmBn28+NH3mXkXDsG4uLHlbX4uvaa2+JotmhWgQ7BlQPBosLqiaDf4WfT/NAtEAFI+HoXvpJ/NpYn3repqCTbisLuwWOx6bh6ZAE4saFjFjwAw8dg/LG5eDAJfVBYBN2KgP1FPkKSLLnoVVS9/+TNHWVoTVSszvJxYIYC/bulCJtrQg7HY0Z4pfgOlE0B9BswhsdguRcJRwIIqU4M6yAyBjEm9TEKtNw5Wpb4uEokQjMRxu8y4mqDl+PaPm+HWflJL/fLWSRq+fUAQKs12EIlE2tPgIhCQDc10Eo5LxA7KZv6YZl9NKbYsffzBCptNKQaYDsKBpEpfdgsNmoak1yJoGP+PKMvllfSsVBW6CEYkvHCYaA6dVY3x5Dj+vb0EiqWryM7YkixgCbzBCQaaNmIQMh50jJpab/RYpqerLu+GbR8HuAYcbsgZC/TKIRiAjDyJhCPvB5gJi4G2AjEL93M27DtDA3wi2TIhFINgEVjc4s8CdB4EWCDSB5oSoD4RTbx/pLoBAK0RC4K+HsklQsxBcuRD2Qv5QOPG/4FDrV3aX6urZB7xtwV4VfQBtwJBr3kr9xi4bffBn+O5BiIaAHbmYIGDGFbDfdUZnlpCu/+p63lz+JtFYFIfVQZG7iDJPGQhY713PTd/eREzGsFvsRGQEi7AwKGsQFmGhwFXA7mW7c8iQQ9Km8IsFg7S++y7BNWsJrViOsNooOO9chM1G6wcfYCspxVZUhLDq70eksZHWd95BOJxkHZyejRIcrs2fDavNQiQYY/lPNWgWwfApRWgWwbrFjSz7sYa25hAISdnwXAaPy6Ou0kfJsGxKh2Wb+AoUxVjPfbeGv721kFDU7EzWd7p1SXUrlx80up9zUVLes2fAwhfbb1u/xTnutqaFtyzbftwg4AO2Nx28cWn7n1d9oP/ZFl+3r2UVPH44nPWBPoJM6XPqjl8nKq5+09B4KV/8PbwfVBr032f0YXDi/4yJlaAOf+lwVreu7nWcMXljeOqwp7BpqT3UU0ajrDrpJAJzO3SqFAIsFojozRAy9tmHgffdS3jDBlbOOp5onb4UhmPECCpeeH7TMg/pyNcc5LmbvtcLPCCn2IXdaaVmdet2n7fn8SP6fSF3dcevZ9Qdv+656c1fePDzlWan0aUDxhTx0Gm7mJ2GkioeORTWftn1fmbT7PCnWrOzSAqqq6fBrn5hjtkpJB+jij6ARcYW3YkmEosYUvQBLGxYyJfrkuALvZd8X3+zddEHIOWmog/A+/HHBJYsoemFFzcVfQDBpUvxfmRcJ9VktOjrqk1FH0BTtb/Log9g9jur+jArRek/D3+R+EUfwPsLa8xOQUklyVD0AcRCsH6O2VmkBVX4dRCMmD4GRFG6LSrT4PMa68FrjMX0/3cgo1tvSycytmMjOzou8aAoySrxxzYpSpqLqaVM+oMq/Dq448QpZqeQfIrGGRdryN7GxUpAVs1KiafEkFhDs4cyo3yGIbESmWf33Tct07AVi2XzfnvsjnP0aLKPPRYte/PcNNvgQWTuu09fp5nQRk0rbdfFMzPfQV6Zp8vnTTygf4d5Kkpf+fUuyfFZ3nN4vtkpKKmkZGezM+geYYEBaoR/f1Bz/DqxttbLjH98akislJ/ft9FL58D8F6A3d6B2PgWOuce4nBLY7z/8PV9UfkGUKHZhJ9eZS6G7ECEENb4aWsOtyJjEqlmJEUMTGiXuEiwWC/nOfKaXT+eY4ceQYU+PTlhRr4+WN14nuGw5oVWrEDYbBRdcgOZ00PLuu9hKy8g6/DA0u96dMrxhAy1vvIFwusg+8ggsWVkmvwLz+ZqCLP5uAxarxqjdStAsgkVfb2Dp7Gr8LUGEEJQMy2HQ2Fwa1rdROjybQWP7/yRUzfHrGTXHr/v+9eES7nh/KYl6I/tXU8q59fiJZqehpJoHD4T135qdxbblVMAF36b8Gs5G6e0xUhV+2xAKhTnqjvdY0ghRwAnkO6AlCAKIAW4NNo4gC6N38rQBA3Nhj2HF3DArzc5dVn0Hdctg0C7gcOlLNsRi0LhGb/fryNBbBxPTl3+I+KF4LIR9EA5D8UizX0G/qvfXk2nNpM5fR4Yzg+ZgMw7NgdPipCXcQp4zD1/Ih9PqxB/xE4vpXT5dNhcum8vs9E0hpSTm86E5HMhIBM21+X2INDZizc3V/97UhCU7O32WU+lCwBvCmWEnGokRi8XQLBoWi0Y4FMVmt3QdoB+pwq9nVOHXMwtW11PvD+NyWGj2hXHYwY6Fep+fCQMLaQkEqWn243JYiUShLRjGatWwW63ke6zIKNQHQhR4HNS1BojEJPkZDhp9QRxWaA1EcTssNPvD2KSFmIgRDkvysp0MK8pkRXULkZjEG4xQnuumwRvCZgGP08GkwXlmvz1Kqlr5Faz9AcKR+Pq3MQi1Qu5oqJkDzhywOvQ7byIGzfX64w43ZA2Athp97H/OMPCt05dpiAT1c7rm9aBJyB0Kbc1gt0FGEdSvBFeO3u3dUwBVP+tLdmWVQ7gVMkvB4YRJJ7Vbk1fZPrWcQx/orKtnAFgXbL/N28llwwiwpBGW/FDN4z+8ydE7F3Lnr3ftkzwTxhd3wQd/MibW0Q/AxBONiZWg1rSs4djXjiUYDXa98zYMzxnOffvfZ9iw0WTg++ZbKi+6iFhLy6Zt9hEjyD7qSOru/hcyFAK7HSEEMhhE2GwUX389ubOOMzFrc62cW8u7D/9MNBxDaJvn7AkNnG4bfm+YosGZHHDGOHKK3eYmqyh96Lnv13Dli/PNTqNLdxw/gWOmDDI7DSVVrJ0Dj+xldhbb99r5UDAafp/AdyVTiJrj18HP65oMjffK3DRoT2tU0Qfwyu+Mi5Wgznj3jF4VfQDLmpZx87c3G5RR4pPhMJUXX9yu6AMILV1K7T/+qRd9AKEQMhjc9JwN119PLNi79zqZvfeoXvRB+0YtMgZ+bxiAmtWtfPLUIjPSU5R+kwxFH8ClzydHnkqSSPSib6O6RRD0mZ1FWlCFXwf/eGeh2Skkl74YKhz0Gh8zgdT7t7faaffNr0ufE4RwdTWx5ubOH9zeZzAaJbxuXd8kleCi0RiRYPdmM3VnaQdFURRF6TOLXjc7g7SgCr8ObpqVJB2QEoXh47I1fS5gCivPKDckzu5luxsSJxnYysqwFhV1/qC27a8x4XBgH5Sew6YsFg2Hu3uj+ctH5fZxNoqiKEr/S6LT/AknmJ1BWkiiT0T/KMl2Y+t6t2677ZixBkZLUL9+xrhYp71hXKwE9dRhT5Hn7N0k/j3L9+TKXa40KKPEJzSNgQ8+gK2iQi/0LBaEw4Fn5gzK/vkPLLm5IARaXh6W/Hz979nZlN/zb4Q1facyH3HRRFyZ+jeazWHB5tDQLAKHx0peqQeHx8rQiYXsc8pokzNVlL71/Dm7mZ1Ct7x+Qfpc0FP6weVLzM6ge0Ydsd2LuIpxVFdPRVEUJWGorp49o46PiqIo6UN19ewDz36/kqte/MWQWGmxjl/QC3eMg0BT7+JMPg0OvzMtrvp8Xvk5d/14F4sbF3f6uAULQ3OG4gv5qA/Wt2sG47F6eOLgJxiVv41FzVOU77vvaHnjTbTMTEASbWwCqxUhY2QecAAZM2du9Zyo10fj0/8jtHo1mfvvT+bee/d32qZa9mM1nz+7FH9raFMnz1hMEvJH0ayCrHwn0Ygkt8SNK8OG3W2luSZAS52f8lG57Hr4EJweI8dAKIo5pJQcdOenLKlO3AYSEwdk8crvZ5idhpJqHj4QKhO8Y+alCyG7zOws0oK649eJzpZz6I2UL/7+UgCxsDGxxh4NJzxhTKwE9eGaD7nk40t6HWfub+aipUGRDOD9/AvWnnPOdhu5lP3972Qf3v53bfVpv6Xt280HvLJbbyH7qKP6LM9EsnpBHW/8e16vYuSVeTjx/3bt1/UQ1R2/nlF3/Lpnj5s/YH1z4nf43a0ih2fPnW52GkqqeHIWLHvf7Cy654ZtNHBT2untMTI9zhp74IInvzc7heTSVm9c0Qfwy2vGxUpQLyx5wZA4j/78qCFxkkHTCy902UG26fnn2/0cWrOmXdEH0Nhhn1Q2+53VvY7RsN6nOn4qKSEZij6Ab1c1mZ2CkkqSpegDWPGJ2RmkBVX4dTC6JMvsFJKLxWlsPKvD2HgJKNOeaUicco8x3UGTgSWr699LS1b791XzeMBiab9PZvr8fhs1RNPhUjMCFEVRklMSneZ7is3OIC0k0Seif1y4f3rNm+o1hwdyhxgXb78bjIuVoM6ecDYOrXcFrtvi5pChhxiUUeLLO+N0LHnb7oSqZWSQ/7tz222z5ueTf/pvN+/j8VBw3rmki+nHDUdovRuiOXr3EnKK3QZlpCjmOXRCidkpdMvlB4w0OwUllRzwF7Mz6B5hheIxZmeRFtQcv20wYp7fmCIbb192oAHZJIHP74KP/wqxyOZtmhWkAIsVZEwfEioBooAAVwGEWvXn5I+A4x+H4vRoK98aauXlpS/zzop3WNCwAIChmUNx29xsaNvAgMwBHD/qeJY2LmVty1qWNy+nyluFEIJZI2dx5a7ps5TDRlGvD9+XX2ItKgQJkdpaLHl5ROtq8ey+O5acnE6fF/jlF0KrV+OeNg1rbnqtVxcKRPj21RXUrGrGYrdQNiwHf1uYxvVenJl2KnbKp2aVl6ETCwh4I2TkOfA2Bald3UrF+HxKh+f0e85qjl/PqDl+3ffBzxu4/Pk5NAeiAGS7LMgY+ILRjUclOjsjsmsQirXfJgCHVWDV9GdFYpJApJMnb7G/rUMci4Bo/B90WTWe/d1u7DSwd0v9KMpW1s+HB2cCsS53NcXoI+DEJ83OImmorp595PhJpTz/U1WvYvx91hSDskkCMy6GxlXQsgayBup/9zdAwyooGKkXgcEm/ajaUqXfKYxKcORAsBWEBbKS44qsETLtmZw67lTKM8r5svJLyjPLaQ22srBxIdPKppHrzKUp0MQBgw/g5/qfGV8wnsklk5lXO49cZy6/1P/CsJxhOCypPzR2I0uGh6yD2l9ICa9fTyw/D4Qg8MsvOEaObLduX6S2FixWMg8+uF8blCQCKSUtdX6mHFKBM8NG3dpWQsEoBWUZODNs+JqD1KxqYdzMUurX+igdnkNmnpNoOEZ2vovsIpfZL0FRDLXzoBwKPHasWphdKnLxOK20BCKsqPGyttGPx2YhP9PBukY/dquG0ypobotQkGnHZbPQ6A9jt2hkOCxEY5IogvJsB0uqfUigJMvK3iMLeWPeepr9EexWQUmGnagmsFug0RfGYbXSFopg1TSKsp20toVAaOw6NI/RJdlmv0VKKiqbAINmwJpPt7GDDTQbxNr6NS0AcobCYf/s/383jak7fp0wsqtnhg0W/DXFu3pu+AXuN2jR2WkXwsE3GhMrgbWGWtn/uf1pi+74F222I5u797mbycWTDcwseVRdfwNNzz2nN33RNIjFsJaVMujBB3EMH07tv++h7r77IBrFMXo0gx5+CGtBgdlp9wtvY5DX/zWHhvU+hACb00rIr9+OEJpgwOgc1v7SuNXzhk4qpGpZE/7WMDanhf1/O5ahEwv7NXd1x69n1B2/7vnr6z/zyJerzE6jS/efPJmDJ5SanYaSKupXwr8mmp1F16b9Hg7+m9lZJAXV1dNgL/+wxtB4XgMbXiasxw2ca/bNv4yLlcD+/v3fe1X0ATQHm7nlu1sMyii5tP3wA03PPru502dMH8ISWV9FzT/vILR2LXX33ANRfUhXcNEi6h9+xKx0+93sd1bRsF5fr0xKNhV9ADImOy36AFb8VIu/Vf/SCgeifPb0YmQs8S8OKkpXkqHoA7jkuTlmp6Ckkgf3NjuD7vnm3xBJjs67yU4Vfh28NGed2Skkn6Bq995TS5qWGBKn0ltpSJxkE1q77dcdXruW8Lp1Wy3/EF6XPu9VS53fkDi+lhCRSILOC1GUbkqGkU0bBcLq900xUDCJ1sYLJFGuSUwVfh08ctouZqeQfIbua1ysXna7TBa/HftbQ+IcODhNmgd1kDFjTzR3590mMw86CNekSVgL2w9RzDzwoP5ILSEMm1y0/R22Md1Rs7R/YPC4fGx2S+c7K0qSEEJgTZIpvqOKM8xOQUkl444zO4Pu0eyQ0cVxSzGEau7Sgd1mZfqQXL5c2flQqJ768JI9DYmT0H7zAtw9GRqW9zKQBn8w5k5YojtoyEH80vALjy14DNlpHzmdVbMSiXdK1dCIEUNDI9+Vz9HDj+acnc7pr5QTirWggEGPP0b9Qw8RbWoCmx0ZCpKx117kn3EGwmJh0BOPU3fvfURqasg+6kiyjzjc7LT7zdjpZcSikqXfV5OR68CT62D57BrCoSjlI3IZN7OM795YRX1lKzKm3xHJynex/+ljWDG3jnWLGikclMkuhxu4VIuimOjra/Zj15s+3M63rflKsx28ffFMs9NQUsnxj8DKT6CtzuxMtkPARbPNTiJtqOYuiqIoSsJQzV16Rh0fFUVR0odazqEPnHDvZ3y3xph5a59eMYPBBVmGxEpo9SvgoX0g0LTjMSwuuGo52D2GpZWobv/+dp5f/Dz+aOdzseyaHYkkHNu6O1CmLZMTR5/IuTufi91i7+tUE4KMxai9737qH3gAQiF9o9tN7nHHUXzN1Qht86j1lnfepeb22wlvqIJofL6MzUbm/vtT+pc/Y8nMNOEV9K91ixv59rUVNNW04XDbEBbwNQRxeGy4Mm001/hxuK0M2bmA+nU+LDaNyQcOpmxEjtmpK0qfqGsJMu2WD4kkcLOiqYNz+d9Zu2G3qeHVikFiMfhrMciQ2Zls38G3wbTfmZ1FWlBz/DoIBCOGFX0Ae/39c8NiJbQHZvau6AOI+uGOCYakk8genf8o//nlP9ss+gBCsVCnRR9Aa7iVh+Y/xD9++EdfpZhwGh57jPp//Wtz0QfQ1kbjf/9L3X33b9rk+/Y71l1yid7cJbpFk4RwmNa332b9H1J/4fvmWj+v3v0TVcub8beGaapuo3F9G6FAlNb6ADWrWgm2RWipCzD3w0oqFzWyen49r909h9aGgNnpK0qf2P3WxC76AH5Y3chvH//e7DSUVPKvKYlf9AG8cyWE1fGnP6jCr4NznlRfuj1WvxxCBhXL/npj4iSw11e8bkicD1Z/YEicZND63vvbfKz5tdc27/fB9t8T76efImOp3TVv9YI6ZLTnz4uGY6xekPq/f0p6CkcTu+jb6IfVxvQXUBQAGleYnUH3fXa72RmkBVX4dXDcpHKzU0g+qhNTjwzKHGRInIFZAw2Jkwxsg7b9ntkHD97894Hbf0+sxcXthoWmoqwC1w4/N7twx5+rKErv5bhsZqegpBItiWZ0Dd/f7AzSQmqfAe2AoyYbc1K+UW46rE7gyIQ9LzMm1mF3GRMngV037TqybL2b95lrz+XKXVJ/2OJGhRdfhJabu9V2LSuLkj/9adPPOcfPwjVlSqcxhM1G6d9u7LMcE8XgcfmMnlbSrX3tzvhcIgFjppcyYPTW77GipIJTpxl7bO8LQsA/T5hodhpKKjnxabMz6B5rBgze3ews0oLq6rkNf351Lo993bsFn7++ai9Kc9NoTR5fHXx0Myz7AHIGQ0sleOvAogF2sDsgtwKa1kDIB65c8NVCTMKQPeD4x8DmNPtV9AspJd9WfUtzsJl1ret4f/X7TCudhkWzMDpvNDnOHKIySoO/gcUNixmQMQB/1I/b6mZswViG5w7HpqXXlWEZi9E2bx6+r77GPqQCa3YOnmm7dXoHL7hyJYFly4jW14MQ2MrL8UydiuZMj88XQGtDAF9TAIfbhifHwboljeSVeXC4bNStbcWdZSevLIOmmjYsVo3MvMR4b1RXz55RXT27r8kX5JJnfuLn9c0UZjio9YbIclhoDETwOCzYNIHHbmFdUwBfKIrdClbNQobDypiybNY2eKlpDmC3aUSiYLcI/OEYw4ozsQtBY1uIdc0BnFawWiwMyfdQnO2irjVIWziC22ahyR+mzhvEahGEwzEGF2QwKN/NxEG5zJo8EJtVXY9XDBaLwSOHwrqv228X7vj8v0gnT9KALadFWICNcwjEFn9q23h+d1nglBdh+D69iJFeVFfPPtLbog/g9Me+5Z3L9jMgmyTw7UPwwV8g7AVi0LwG/UtBQtQG+EC6YMM8CHqBCPgb2PRFsvJz+OU12PkEs15Bv1rnXcezi5+l2ldNrjOXLEcWn6/7HAQsblxMZWslxe5iDh92OF9v+Jq2YBu+iI/dSnejxl/Dj9U/cvCQg8l35Zv9UvpFqLIS/48/YhswEMfAgdhKSok2NtLy9tuE6+qINTeTddBBhKuqICbJ2HM6tvJyNtx0M8ElS7CWlSJbW8k65BCzX0q/0SyC6lWthANRhkwsYNCYfOZ9vJa21hCjp5VSt85LKBClZGg2i7+tYsOKFsbPLCe/PI0uVilp5cNFNXy+rJ6ohFqffrJa7wsjgYa29ievAghGAaI0+qOsbapBA2wWQdQfIcbm0+KGVU2bniOBZvTnrWsOAVvP2bNr+o4hCetbG/lmZSML1rVy9MRybGoglmK02oWw7rutt8u27Typ41z4LSeOyy3+7O2c+Si8dYVax68fqTt+nai4+k1D46265TBD4yWc+/aE6vnGxBp+AJzygjGxEtRHqz/i4k8u7nUcu8XOIwc+wsSiib1PKoG1vPMO6y6/AqLd71hiGzaM8Jo1EG7fGdW9224MfuJxgzNMPOuWNPLaXXOIbdHQwmrXiIS2Pki7Mm34Wze/TzNPHMmEvQf0S56dUXf8ekbd8eueUx/9hs+WJH7zojn/dwA5nvRYpkfpBz88Dm/0/nyjX9zQbHYGSaG3x0h1aamDv702z+wUkktbvXFFH8Cy9/VhCSnslu9vMSROKBri/nn3d71jkqu9864eFX0A4eXLtyr6ANq+/ZZQ5TqjUktY37+5sl3RB3Ra9AHtij6Ab19Poi5witJNyVD0AVz54lyzU1BSyVt/MDuD7lvyntkZpAVV+HWwpNZndgrJJdgH79eO9KJPIv7wttfv6ylfKPU/r1Gv19B4MZ+x8RJRyL/jv0OxSOKPAlGUVFXvS4I115TkEevN/Lt+1tT7KVZK11Th18ETZ6quQj2SOwhsBs4JyiwBS2o3Lfn1mF8bFmvWyFmGxUpUuSfswLxPt7vTzdbCQpyjRvUyo8Q3bkZZt/fVNNHu52GTC41OR1FMV+hJjuPKn48cb3YKSiqZeJLZGXTfrmeYnUFaUM1dOnHzMWO55uVfDIm18uZDDYmT0K5YDA/sDQ1LexenaDyc+5khKSWy8yeeT6Ytk/vn3Y8/4kcTGlJKovE7nVZhJRKLYLfYKc8oZ3XLaiIygkTisrioyKog25nNqWNPZcaAGSa/mr5XcOHvsQ+poO277xEOBzIURMvOQQYDROvqCVWth3AEz57TiQWDCAQ5JxxPpKaG9ddcS7S+HuF04pk2jZK//sXsl9Mvxs0ox53tYN5HawkHo4yYWkTJ0Gy+fGk5YX+EAWNyCQdjZOU7GTa5kC+eX0ZTTRvDpxSx2xFDzU5fUQz3/f8dyMxbP2JNo3EjLowkgHtOnsT48myzU1FSydH3gL8ZFr9udibbd14nzWeUPqGauyiKoigJQzV36Rl1fFQURUkfajmHPjDlz29T7zemwcjpewzg+iN3NiRWwqqaBw/tBzED5iac+wWUTOh9nAQmpeSSjy/ho7Uf7XAMu7BzyNBDuHa3a3HbOh/WmEpq772XxqefxuL2UHDRhWQf1r5Tbv2jj1Fz990QCLR/ohAgJcLtpuT6P5Fz1FH9mLV5WhsCvHT7bLyNQUB/GxxuK1LCwLF5NNe0Ub9Onx/qybbT2hDcKobFqrHfb8cwYmpxv+auKH1hRa2XA/75KdEEvtZ9wpQB3HZ8ip8vKP0r5IObuj/03zSF4+GCL83OIi2oOX4d1LcGDCv6AB77Kg0mqz5xhDFFH8BD+xsTJ4E9tfCpXhV9ACEZ4tXlr3LPnHsMyipxtbz9NnV3/4tobR2h1atZ/4crCa1evelx7+efU3PbbVsXfQDxEQ2yrY2qa64l2tk+KeiNf8/dVPSB/jYEfBGCbRGW/VBD7RovsagkFpWdFn0A0UiM9x7+mbYW1WxCSX5H/vuLhC76AJ6bXcnb86vMTkNJJf8YY3YG3VO7AHwNZmeRFlTh18HdHy4xO4XkE2gyLlY09U/MP177sWGxvt/wvWGxElXb9x1eYyxG2w+bF3tt+66b70Es1v19k1zDeuO6vW5YodZWUpKfN5gc3aK/WZEcy04oSSKYRN/fH1xvdgZpQRV+HZw1UzU26DG7x7hYIjk6r/XGriW7GhZrQkFqD4sFcI7f+jU6J2zufOfcqZvvgRC4J6bHMKqsAqdhsQoHZRoWS1HM4rIlx+nOzgNzzE5BSSVWl9kZdN+el5udQVpIjm/CfjQwL8PQN2W3iiwDoyWoXz9jXKzfvGxcrAR11oSzmFg4sddxZg6YyUWTL+p9Qgku++ijyD3lFITdjiU7m+L/uw7nyJGbHs/cf3/yzz5Ln8i2LVYrhVdcjiUrDX4fgcMu2Am7u/0UbotNAwHlo3LIyHNs2m53WToPImDGiSPIzDOuiFQUszx55m5mp9ClmSMKOHpiudlpKKnkojlmZ9A97mLIrzA7i7Sgunpux7XPfsWSqkasQCACWU6oaQKPB3Kd4I1ArhUawxAMg02CNwR5Hpg2spTfHzK533M2VaAZ2prB5oKIH4QGUSDUChZN/9mVC8EWiEX1NftCbRBoAVcOZKbX+mHhaBh/xA8xsFgt2C12wrEwDs1Ba6gVAE1oRKIRXDYXFmEhHAvjsrmIyig2LfXvjm5JRiKgaQit80szMhpFxmLEvF6subnE/H6E04n0+9G2sa5fqguHooBEs2homiAWk1gs+vsXjepzmTf+3OYNYLNasVg1wpEodocVsb1iuo+orp49o7p69kxTW5BAOIrTasEbDCNjMYLhKBEpicWiNLWFcVs0bHYNpEZ+totQKEoEKMtys67Jhz8cwWWzEAjHsFs12kIxnHYNmwUsWGgJBMh0ufCHgkQiMTQE4WgUl8NKMAIWCzR5gzjtFvI8LuxWC8XZLqwWdS1e6SMtG6BuOTSt1yd9ZxZDSw3klkLtUsgbBkE/RIIQDULTKsgbAo4MsLlBhsGRCQGffk5ndenndMEW/fG2enDkQfNaKKiAsE+fd+/ygN0NMp6DKxNqlkHOQBAS3HkwOvV7OxgpYbt6CiGcwGeAI/7vvCClvF4IMQR4BsgHZgO/kVImVPeAT39Zz2n/+WnbO3i7CNACX1RV8fdP32TVLYd1sXMKiEbgf7+ClZ9CLLzjcUYcAicbePcwwTUGGrnuy+v4uf5ncuw51PprCcTnOEo6vyDjsrgYnTeaMyecyV4D9+rPdE0XCwRpef01Ig0NWPLziVRtwD1lMhkzZxJatYrmN9/EkptL9pF6587mN9+k+aWXcYwcSfFVV6K5kmjIiwH8rSEWfbOB1no/QhPkl2dgscKcDyoJ+sJYbBr55ZmUjchmzYJ6bE4ro/cooXa1F5vDwqhpJTiTZNHrZJTMx8hk9dmSGs547HsiCXi92yLgzD2HcO1hY81ORUk1z54BC180O4vt+78G/YqI0uf67I6f0C8Ve6SUXiGEDfgCuBi4DHhJSvmMEOJ+YK6U8r7txervK5oVV79paLyUL/5uHwG+GmNiFY6BC74xJlYC84a87PXsXoR60Q31+t2vZ9bIWQZmlbhkNMrK448n+MvCrR7LPeUUml54ARnv2OkYMwbXLrvQ9J//bNrHVlbG8I8+7Ld8zRb0R3jmr9/i3UbHzu7ILnJx4nW7YrX378E4Xe74GXWMVHf8umdZTSv7//Mzs9Po0n5jinjktF3MTkNJFY8fAasS/3MPwA1J1IjGRL09RvbZuAKp23hvzBb/vwT2BV6Ib38COLqvctgR+9z6gdkpJBdfnXFFH0Dt1if2qej5Jc/3qugDeGj+QwZlk/javvuu06IPoOn55zcVfQDBhQtpfu65dvuE16/Hv3BRn+aYSJb/WNOrog+gucbPynl1BmWkdJSsx8hkde5/Z3e9UwL4aJGBx1NFSZaiD/TpQkqf69MB5UIIixBiDlADvA8sB5qklJH4LpVApzOZhRDnCCF+EEL8UFtb25dptuPs56vbSU+oOQk7wmFxdL1TFywijT6r2xsC0tmcv07mpmm2PhvZnnA0izFz8yxqzlGf2tFjpFnHx2Rmtfb/fNUdkRxZKkpfSKNzGhP16VFdShmVUk4EBgC7AqN78NwHpZRTpZRTCwv7r+nH25fu02//Vkpw50FOhXHxBk4zLlYCO2bEMbitvWs4ctGk1O/ouZF7l11wT+18ZEPe6b9F26Jbp2vqFPLOOqvdPvZhw3AMH96nOSaSYZOKyC3p3eerYGAGgyfkG5SR0pkdPUaadXxMZo8myfDJoyeprp6KgcYcbXYG3efMMDuDtNBvXT2FEH8C/MBVQImUMiKE2B24QUp50Pae299zGOqa2ph6S+8X2bYCy1J9ft9Gb1wO856DUAC0GMQiXT+nHQHTL4YD/twn6SUib8jLrd/fyndV31HmKWN1y2oag41oaMRkjI3/E/H/SSSFrkJ2KtyJMyecyfiC8V3/IylEhkK0fvghkcZGbKWlhFavxj1lCq4JE4jU1tLy/vtYc3LI3H9/hN1O6+ef0/TsszjHjSf/d+egbaMbaKoKB6Ms/7EGX7M+5DOv1IPdaeXH91YT8Iax2i0UDspgwKhclv9Ui8NtY/S0EjasbMHmsDBsUmG/z++D9Jnj19GOHiPVHL/uW1nr5ah/f0FLAi7m7rFr/PHQsZw0bbDZqSip5tO/w8d/NTuLbbNlwx/XmJ1F0ujtMbIvm7sUAmEpZZMQwgW8B9wKnAa8uMXE9XlSynu3F8uMA9uHv6zhzP/M3+HnO4DF6VL0bbT0A1jxKZTsBOt+hNXfwaBdINIGOUMguxy81Xq74LKJ0FYDlT9C7ggoHw8V081+Bf1qQe0CFjcspthTTKYtk3AsTGlGKaB3/CxwF1DXVocmNJoCTURiEcIyTLG7mEJ3IfmufKxa+gxfjLa2EmltJVxZib28HEtWFjIWQwaDaFlZtH7yCc6RI3FUVBBatw7N7UYIgebxoDl6P7Q2Wfm9IWx2C0ITBHxhYjGJjEmsVg1vcxCb3YIzw4aMSdpaQuSXZ5iyjMNG6VL4GXWMVIVfz3yxZANvzd1Akz/E1CF5OK0WGtrCrGrwkuuykety8PXyWpr8IQbmeshyWfFHJHkuO1luKwsqm5g5spDyPA/fr6yHmGB+dRMei5UhRR6sgNthw223Mn99I4FQBJfNSoMvRFGWi0ynFY/DRkWBi9mrGwkEo1R7A+w6KI+LDhpj9tujpKpP/gFf3QshH3gK9THFQgJ2fTmtcDNEIuDM0ufa2TPAagF/qz6lx1OoL/PQWgcyCOEIlE8Eb50eJ9gKRaP15R+iEfBWQbBN/zNrIGQWgb8J/C3QtA48ORCNgjsffvMM5Kg73d2VyIXfTugT0y3oQ0qfk1L+RQgxFL1VdR7wE3CKlHK7XQiSuavnxAEZvPL7FG+7X/0z3LeHAYEEnP+N/uWRwhoCDez33H5EZE/viraXacvktr1uY8/yPQ3KLDHJWIwNf/0rTc88q68/1ENaRgbF11xNznHH9UF2iSsUiPDewz+zekE9FpuGEBAJxbp8nsWmcfjvd2LAqLx+yHJraVT4GXKMVIVf99R7g0y5MfGbtz30m8kcMK7U7DSUVLFuLjw00+wsumbPgmvXmp1FUkjkrp7zpJSTpJQ7SSnHSyn/Et++Qkq5q5RyuJTy+K6Kvv722k/GfvDmVHa16F8KeOxQgwJJ+O8xBsVKXOd/cH6viz6A1nAr//fl/xHuzdqJSaD1gw9oevqZHSr6AGJeLxtu+DOR+nqDM0tscz5Yy+oF+muOhmPdKvo27vvewz/3ZWoKyXuMTFaz7vvK7BS65ez//mh2CkoqeShJ+laEWqB+pdlZpIX0mvTSDQ9+tsLsFJJPsMW4WL7U71C3ttW4iwt1/jqaAk2GxUtEwSVLex1DhsOEVq3qfTJJpGHdjl908ntT+2KCkn7WNfvNTkFRTJB481m3aeFrZmeQFlTh18GDSdL5K6HkDjUuVulOxsVKUHuUGTEsVjcqdxSF7tTu6pcxY89Ol2foCUtuLs5x4wzKKDkMGr/jHTnzSjwGZqIo5ttzWIHZKXSLw6ClWBQFAEeu2Rl0326/MzuDtKAKvw7KctzYDIz35JmTDYyWoC74DhxZXe/XlawBcJpx8ysT1W0zb2NY1rBexdDQmFY6jTv2ucOgrBKXa+edKbvtVqylpe0KQJGRoS/jkJnZfnt2NthsYLOhZWfjnjaNgQ8+iOZ0mpG+acbsUcq0o4eSW+KmqCKT4qFZ2J16kxehta+lhYVN2/PLPBx16STzEleUPvDwabtQ4DHy6N43vrx6P7NTUFLJlcvMzqB7xs8CW3odo83Sb8s59IaavK4oipIe0qW5i1HU8VFRFCV99PYYmT694HvgoU+X8re3lxgSa951+5GVkeJXMfxN8NhhULOgd3F2OhGOfcCQlBLdA3Mf4MWlL+IL+wAIRoJEY1FsVhsZtgwmFk3k7PFn8+dv/szSxqWEYqF2z7dg4dAhh3LTzJvMSN90kcZGGh59jMDixYQqKwmvXau3orZaseTmIv3x+TxOJ7K5GSwWMvbdl9I//xlLRnoMY1zzSz1fvbiMUCDKqN1K2PXwIbQ2Bnjxttm0tYRwuK0cet4EvnppOXVrvWgWQTQcJRYDu9PChL0GMPngwdid6jChJL9YTHLMvV8wt9LAOekGK8t28sVV+6JparinYqB7d4eaX8zOYvtOexOGpHaH8kSh7vh1IKVkyDVvGRpzVaqv53fHBGg2aPHNXc6Cw/5hTKwEdf/c+7lnzj1d7rdx0fbtOW74cdww/QaDMkseq351Iv65c3v8PNfUKVQ8+WQfZJRYala38PzN7b8zd95/APM/Xkcs2v3v/IoJ+Rx2wc5Gp7dd6o5fz6g7ft1zysPf8MWyxO/sW5rt4Otr9jc7DSVVPHoIrEmOjrbc0Gx2BkkhYZdzSFZXvdDzk8m0FvYbV/QBzH3GuFgJ6qWlL3Vrv66KPoC3Vhp7kSIZhFat2qGiD8D/w2wijY0GZ5R4Fn29Yattv3yxvkdFH8Cq+fUEfKrDp5L8vkyCog+gqlmt3qEYaM3XZmfQfT88ZnYGaUEVfh3sOsScRYuTlsUBGDgsxZltXKwEles0rstWhj3DsFjJQsvORth2sEmDzYbmdhubUALy5Nq32ubO3HpbV+wuCza7xYiUFMVUDmtyDJ9MjiyVpGFJ/IZGm5SMNzuDtKAKvw5mTR1kdgrJRdNg17ONi3fM/cbFSlDXTbsOq+h63lR5RnmX+/xtz78ZkVJSsebmUnDBBTu0xEPR1VehORx9kFViGT+jnIzcza9TaLD3KaMpGpzZbj+rc/uHgN2PGY7Fpg4TSvK78egJZqfQLefMGGJ2CkoqOfTvZmfQPZoNBqjl1PqDmuO3DTP/9hZrWnv33py6awl/OXaKQRkluA3z4fXLoXqBfkIeiYAM6I85ciDkAxkGBNg8EAmClPq+dhcMmQlH35sWd/wA2sJtvLz0ZexWOy3BFizCwrKmZUwqnERTqIl9Bu3D0Oyh/LDhBz5c8yH+iJ+1LWvJceYQiATIc+Zx1a5XpeUdv41Ca9YQWrMWzeOm+c23iNTVYisuxrPnDALz5iJsdmzDh+P/7luEZiHvN6dgKy01O+1+I2OS5XNq8DWHGL1bCQ63fuV31bw65n5cyZjdSxm5azG1la3M/7iSsuHZNFa30VDVxuBxeQweX0BmXv83plJz/HpGzfHrvupmPyc9/C0ra33EAIsAm4BAbPM+LisEI7DFJjLsGuFojFCUrQbgC7be1lFn+2jxbQJw2gUFHidPnD6VIUUGLI2kKFtqrYJHDoKm1WZn0rlpF8LBN5qdRdJQXT37SMiAgnhEcU7vE0kWEgi36X/XrDB0V6hZCEXjoG6Jvi3YArGoPi/Q7gFnDgRaIBrUt6XRIJemYBMrmlaQ5chiedNyljctZ0LhBGLE+H7D98ypmUMoEqI2UMuUoikcNPggPlz9IXPq5pDnzOPIYUemXdEX3rCBppdfwZLhIWfWLOyDBiGsVrxffoVj8CBsA8rJPfZYLFlZuMaPo/mtt4lUVZFzzDE4R40yO/1+11zrJxyIIqOSdUubcGZYWfFTLQFvhANOH0NDVRsN670EvGGmHTUMd5Y+FDQWjbFhRTPRcKyLf0FRkktTW4i19XrR57LAyJJMFle3Yotfg5SAy27BaZN4gzE2/gr4QvpfMmzgcdmRMYlVCDZ4Q3Rn2qwGRON/2iwwosjNuuYQVgGNbRFCYYnHaSHXk+IdwBVzuPKhucbsLLZBg/I0WO86gag7fp2ouNq4RcQz7BoL/nKIYfES0otnw/znjIl1yoswPLU7mt0/537umdt1V8+uTCqcxH8O/Y8BGSW++kcfo+a22zZvsFjIOfFXND31v/Y7CkHub0+j8fEn9DvKcRn77cuAf/0LoaXHsMXPnl3C/I8ru72/ZhXsd+oYykbk8PI/f6KlVl8OY+d9B7LnCSP6Ks1OqTt+PaPu+HXPOU98x3sLa81Oo0v/PH4njp0y0Ow0lFSx9nt4JAnOqTLK4IqFZmeRFFRXT4M9+91KQ+N5Q2lw1dyoog/g+dONi5WgHphnzFqFP9X+xIK6Xq6dmARiPh81d9zRfmM0unXRByDlVkUfgPfDj/B98UUfZpk46td7e1T0AcQiki+eX8qP767ZVPQBzP1oLY0bfEanqCj9LhmKPoCrX5pvdgpKKnnkQLMz6B7vegi2mp1FWlCFXwefLqkzO4X0Fkr9k8yojBoWq7KlZyf4ySja2grhHiwpsI1RDJGaRB3qYqy2ptAOPS/gDeNtDGy13de8Y/EURem5cA+XXFGU7Uuimw9tqb/UUiJQhV8H/z4pTZqxGMme2fU+3TXmKONiJahBmcZ0jtXQ2HfwvobESmS2khKc48Zttd1SkN/p/taioq22aW43GXvvbXRqCalsRA6enJ4v3TB0UiGjp7VvfpOZ56R0eHo0XFJSmzVJznamDM4xOwUllQxJonOEXNVVvz8kyVdh/9E0jVN2KTMs3oLrk+Q2e29csVSfPNxbFTPguId6HyfBvXr0q4zPH48FC6JDQxttG7+SHoun3c8FzgKePfxZ7Jaen+Ano0GPPkLmwQcj3G60rCzyfncOQ159lexjjkYrKEA4nWhZWWTPmsWw994l54Tj0XJz0bKy8MycyeCnn8ZaUGD2y+gXFpvGsVdMYeQuxTgzbNicFjw5djILHAhNX9oht8xNxYR8ykbmMHBMLrscVsF+p41l6KRCDvndBIZOLGT8XuUcffkkLBZ1mFCS38K/HJLw7cOGF7p54bzpZqehpJLTXgZbEly8u3CO2RmkDdXcRVEURUkYqrlLz6jjo6IoSvpQyzn0gT1veo/Klh7MKdqOF3+3G1OGpPidBinhtqHgb+hdnOzB8PvvwZb6C2wvqlvESW+fRDjW/c+ZRVgQUmC32sl2ZLNH2R5cNvUysuypve5TzOdj7bnn0TZ7NsS2mK/gcGArKiLnuGOxDRjIhhtuIObzIVwuZDQKwaC+n9VKxl57UfJ/12ErKTHnRSQ4KSWz31nNj++sJhyKYnNYmHHCCMbsYdzoB0UxU4M3yOQbPzA7je3y2DW+/+MBuB3q1EwxSCQIN5VDD841THH4nTA19Zv7JQI1hqeDQChiWNEHcNwD3xoWK2E9cnDviz6A5tXw9Im9j5MEfv3Wr3tU9IHeFCZChLZIG1W+Kl5c+iJ//fqvfZRh4lh74UW0ff99+6IPIBgkvHYttXfexforriDm9YKUyLa2zUUfQCSC98MPWXfJpf2beBJZ8Ok6vn11BeGgvkJ1OBDlo/8swtcc7PrJipIEdvlbYhd9oK8XeNi/Pjc7DSWV/GNM4hd9AG9cAtGI2VmkBVX4dfCnV1K/Pb7h1n1vXKzVXxoXK0HVttUSkcZ8wX1a+akhcRKZ/8cfjYkzZw7R5mZDYqWa1QvqO92+8Kuqfs5EUfpGsjTLXFXXZnYKSirxd/7dnpBqfjY7g7SgCr8OTt1ddRXqMbcBjV02yi43LlaCynHmGBZreM5ww2IlKqOGZ1pLStAyMgyJlWrySj2dbi8fmdO/iShKmnPbLWanoKQSLYmGDecMNjuDtKAKvw7GD8wzNN6w/NSfr8aZ7xoUSIMTnjQoVuKyaTbOmXBOr+OUZ5Rz3bTrDMgosZX98x/gcm3zcdfUKWQedNB2Y2hZmZTeeCPCok6qOjP54MEUD2k/V3TIxAJKh+WYk5CiGOxvR481O4Vu+e+Zu5mdgpJKTnrJ7Ay6p2A0uHLMziItqK6e2/D5wnX85ok5vYqx4qZD0LQ0qq1/fApWfQHD9oaqBdBWD8Xj9MnF7nxY8zWs/BKyiqF8CuSUQ90KsNph2D4w+hCzX0G/CkVCvLzsZUrcJaxtWcvY/LF8vu5zXDYXMwfOxBfy4bK6qG2rxWqxMrFwIitbVjI4czCt4VZKPCVoIj0+X1JKAj//Ak4H4cpKLBmZOIYOQYbD2IqLAYg0NBBYtgznsGFYcnNpeuNNLPl5OAcNwlZSgrDZTH4Vic/XFKSlvo2sAjeebHMuWqmunj2junr2zMX/+4GalhAzRxayrslHkz/KoHwXlXU+QpEoMcDjsDO+PIvX564nx2mhsinAHsMKaGgLsb45QKbTSr0viEUKst12gpEoCNhjWAHvzq9CSkluhp1ct52QlHj9URxWGFmcTWmOizX1rSytbmVFbRt5bisFWW4OnVDKCbuqOx5KH/n0HzD7CYiGwZkL3irAAp58vUFf8yqwZ0FmKQSawZ4BLevA4gKLgEgYHG4ItELeELB7oGUDNK8BZw6EvfqyEYEmyBkAgUYomwwNyyESgnAQEGDRwOYCbzV4CiF/GMx6BNxJsOREgujtMVIVfp2IxSRDr32r13HswJJbDut9Qsmgah58eRf8/DrIHWkIocHUM+DwfxieWiKKyRjPLnqWF5e8iMPqYGz+WGyajUUNi7AIC8NyhlHdVk1ToAm3zc3ihsW0RdoocBZgtVixaTbOnnA2+1fsb/ZL6VexYBDvhx/iX/AzwuEgUl2NsNvIO/VUYi0t+L79juDqVRCJYh84ECljBObNR7ic5J18Mp5p08x+Cf0iHIqy4qdapJSUDMli3seVxKKSyQcNIqvADUDd2lbmfLiG5ho/nhwH42aUs/zHGgB2PWII7ixV+CUDVfh136KqZk555Dua2kJEYl3v39/+eOhozp45zOw0lFTz3Bnwy4tmZ7EdVvhTLaTTjZJeUIVfH6i4+k1D461K9eLvh8f0jkxGyB0CF88xJlYC+81bv2FO7Zxexzlx9In8cbc/9j6hJCBDIVb9+iQCP+/4BPD8s8+m6PLLDMwq8YQCEV645QcaN2zdJEIIOO6qqbTUtvHeI79sM4ZmEZzy193JzHP2ZaqdUoVfz6jCr3sWVDZx+L8Tv3nYETsV86+T1MdfMcg9e0BtkjRNuUE1X+uO3h4jVXndwZfLas1OIfl8eqtxsRpXpnxL35XNKw0p+gCeW/xcj5eFSFatn3zSq6IPoP7xx4l6fQZllJiWza7ptOgDfUTPN68s5+tXVmw3Riwq+fqlZX2RnqKY4swnkqM4fn1etdkpKKkkWYo+gG8fMjuDtKAKvw68gZDZKSSfiNFrfSX+XejeCEWN+4xJKUmGu/ZGkCEDCtxoFGLR3sdJYLEuxrBFwjGi3RjnFknEsXCKsoPCHdcBVRQlsfiSaOmJJKYKvw4OGp/6ywkYbtr5xsVy5oIltZtwjMobxeBMYybx7ztoX+wWuyGxEl3mvvtgGzCgVzGyjzoSS1ZW1zsmseFTinFnb/szscthFUw6sIvPn4BdDx9qcGaKYp7bZ+1kdgrdMmWQanKhGMhVYHYG3bfv1WZnkBbUHL9ONLS0Mfmmjw2JlfLz+zZa+AZ8dFPvhhWUToJzPtYnIqU4f8TPbd/dxodrPsSqWRmcNRirZmVNyxo0oVHqKaUx0EhbpA0hBHVtdURkBIfmwKpZsVvszBo5i/Mnno9Ig/dro0hjI03PP49/zlywaETr6vXGLaeeimxro/XzLwitXAFSYistRUaiBJctQ9jt5J1yMjnHHZcWSzr4moMs+roKGZPkD8xgwSfriEUluxxWQdmIXACW/VjDnPdX420M4sq0M3xqMZWLGkDCtKOHUVxhToGs5vj1jJrj133Pfb+aP77yM+EEXc19n5EFPHaGWs5BMdjto8FXZXYW23fhPMhXXW27QzV36UNrKitZX1WFw+FEs2hEYzEEAptFA82CjMUQQkNogqDPB5pACgtWq8aAklLy841dEzDhRSL6JCIRb/1rsYKMgWbRh9dF40PshAaa0LcLEd9Hf0/TTSQaISZj2Cw2orEokWgEu1W/WyOEQAhBOBpGExoCvcCTUiKESK+lQrYQi8X0YldKhKZtej86avfdFt833Wzrvdn4Hm7vfTPrgoIq/HpGFX49E41GiUSi6FMKNKxWjVAoTDQaRdOsRKIhbFYrWvy7BSAakwg0pIxhsQg0zUIkEkXTQB9BKhGCTd/L+tMkkUgEm81OMBQiJiUOmw0hBNFoDE3b/LsWiURxu11Y0uCilGKSUAAiUX1phUhEP9/yt4HHDTYneL3g8eg9FjQrCPTzuXBYf47TA1YrBANgs+of/JgEu13/VQoF9MeJn9sh9fO6QECPFYufG9ps+jmfxQatTeDJArfbzHcm6fT2GGk1MplUMeaaN/H3uh5eBcCl+w7l4gPH9DZYYvvxSXjtgt7HcefDRXPAmdpD8QBu//52/vPLf3oVY1DGIF4/5vW0KQBjfj8rZ80itHxzYxJhtyOjUaxFRRRfdRVZBx9E/WOPU/uvfyH9be2mi9oGDqT0r3/FMy31r6jP+WANP7y1ilhUstO+A5h2lN4iPhqJ8eSfvsbboM/LzS5ycdIN09A0vch7/d9zWLOgAYDS4Tkcc9kkhJY+d5SV1DW/sokj//1lws8gn3f9gWS5Unu6g9KPNvwM9+9hdhZdG7QHnPG22VmkhfQ4Y+yB+taAAUXfZnd8tP3ueUkvGjWm6AN9wfcXzjAmVgJb07Km10UfwBrvGm793sCOqglu/VVXtyv6QF/igWiUSFUV66+8ktZPP6Xm1luRbW1b9QgKr13LuksvJRZK7QZOG1Y28+ULywi2RQgHo8x+ezUr5ujdit9/9OdNRR9Ac42fz55eDMD8Tyo3FX0AVcua+O71FP/+UtLGrx74OuGLPoB9/m7MNBNFAZKj6ANY85Vq7tJPVOHXwSNfrjI7heRSt9jYeJXfGxsvAX281rgD+3cbvjMsVqLz/7xgu4/LUAjvR9t/b6ONjYTXrDEyrYRTvaJl620r9fWRqpZvvU5S5aJGAFYv2PqgW7m4ydjkFMUE0ZikLZwcXT3rfemxPI+ibGXha2ZnkBZU4dfBuTOGmJ1CcikyeBhrxQxj4yWgAwYfYFisGeWp/35t5J44abuPC6eTzIMP2u4+lsIC7IMGGZlWwikdvnVXwNLhOQAMGJW71WODJ+QDMHTi1t3fBo/PNzY5RTGBRRNkOpJj/lxJRnp0aVb6SxKd5o87xuwM0kISfSL6R5bHQY7DuHg3HT3WuGCJSAg4/gljYmUNgGMfMCZWAivLKOO8nc7rdZyROSO5bOplBmSUHEpvuRnHuHHttgmXC+FyYR86lPI77yBj990pueEGLLm5+sRy0D+jFguOUaMYcPfdCHtqn1gVDc5i75NHkZHrwJVpY9rRQ6mYoBd1+502hpxi16Z98wd42PP4EQCM3bOc4VOL9Ka6AgaPz2PqoRUmvAJFMd5L50/HkgTTVT/4w95mp6Ckkot+MjuD7hlxCLhyzM4iLaiunoqiKErCUF09e0YdHxVFUdKH6urZB5asb+bAu78wJFbarOP32R3w0Q29izH6KDix901PEl1Mxrj5m5t5bslzxNDnnViFvjZfmaeM6rZqApEABa4CNKHRHGwmEA0QkZF2cU4fezoXTr4QW4oveL8t3k8/pfWTT4g0NhFctYpYfR2a24Nz9Cik0IhUVoIQZOyzN/mnn47mcnUZM5XEojEWfb2B2rWtDBydx9BJhQR8Yb56cRmVixuJhKIgwGrTyCpwE43EaFjvJRKK4c6ys8esEYyYUmT2y1AUwxx7z5f8uLbJ7DS2aUJ5Fq/9fs+0WptV6Qd3TYbG5WZnsX0XfA+FI83OIi2oO36dqLj6TUPjpXzxN+dpeOVcY2KNPQZOeNyYWAnq2s+u5fWVrxsSa2b5TO7Z/x5DYiWTxmefY8P113d7f/duuzH4icf7LqEE9OF/FrLoq82L9u5x3DDmfVSJtzG4nWe1t99pYxi9e2lfpLdN6o5fz6g7ft1zyJ2fsnCD1+w0ulSW7eCra/Y3Ow0lVdy3F1TPMTuL7rlh6+ZjytZ6e4xUc/w6ePwr1b68x965xrhYv7xiXKwEFJMxw4o+gM/WfUZjoNGweMmi8emne7R/27ffElq1qm+SSUDhYJQl32xot23OB2t7VPQB/PjuaiPTUhTTJEPRB7C+uWe/o4qyXclS9AF894jZGaQFVfh1UJblNDuF5GMzcAidSO2PpCY0LBjXXU4TGjYt/YZ6ah5Pz54gBMLl7ptkEpCmCSy29r9LdmfPP3d2l5oNoCiKovSDrHKzM0gLqX2WvQMOHF9mdgrJ51f/NS7WfjcYFytBXTH1CsNinTb2NDLsGYbFSxYF55+HsHW/4M359a+xFafPfDWLTWvXkVPTBLsfM5yyETk9irP70cOMTUxRTHL8lOQ4qZwxXC2hohho6tlmZ9B9ow82O4O0oOb4bYMR8/xG5Dt4/w9pMla/qRIePRha1nbyoNBb6ksrEAbinzmrG2QMokFwZMKvn4WKPfoxafPMrZnLFZ9eQUOggRx7DtmObDLtmUwrm8bc2rms865jj9I9CMVCrGldgzfkZU3rGtrCbcSIUeYp4+Y9b2ZyyWSzX4ppwlVV+L7+BmG3458/n0htLcJhJ3OvvYg0NBKprUUG/GTsuy+eXXYxO11T1K5tpW6tl/KROWQVuJBSsuzHGlbPqyMUjGKxCjSLoHRYDgFvmPXLm/E2BCgalMXuxwzDY+TaNt2k5vj1jJrj132vz6nkomfmkohnPW6bxnWHjeGkaRVmp6Kkmrkvw8u/NTuLbcuugEvnmp1F0lBdPfvIJXsP5s5Peje/5fGzphmUTRJwZsGYI6FhOWSUwoqPwF0IrnwQEkrGgbBCNASrvgCbUx/W6SmE0p0h1Arl6VPE7Fy0M08d+hTvrXqPLEcWJZ4SGoONaFLDYXEwtWgqX1Z9SUVWBcOzh9MUamJ03mhynbnYLXbGF4w3+yWYIub3E16/HgBrYSE5x+oLvmYfrjdQinp9RGqqyRg4kPDq1dgGDCDa2Ei4uiat7vhtlF3oonGDj6AvTIsAi1WjaHAWSCiqyCK7wEUsGqOp2k9GnoOhE4vIKnBitSfHYteK0hP7jS5mtyG5LN3QQiAcRQooy7JT3RohFovhtAksFiu5bhvZDo1fqtsoz7FT2RjApmmMKc3AYbXQ5I/S1BYiy20lGpUEwhH84Sj13gh2KwzO99AWilLnDTAo183K+jZcdo0clwNfMEJDWxiHBnkZToSI4QvGOHB8CbOmDjL7LVJS0c7HQN0veiO+WFTf5quDjDIIN+vX4mNRiPgACe4ycLrA3wixCASbACdYhH7OJqMQCkLYBwjQbODOgmgUfNVgsUNMggzq8TQnSAvYnSDDkDUYmtfqz3XnwMnPm/O+pCl1x68TRnb1zHVp/HT9IYbFS0if/xM+/LMxsQ67E3Y53ZhYCay3nT3LPGW8dsxrOCz9f0fGLK0ffMC6q65G+nwACLudoiuuIO/U3wDQ/OqrVP35L8i2NrBY9IOQzQbhMAhB9tFHU/q3GxFaeoxwX/BZJZ/+b8l29ykanImvOYivKQQCkOBwW9n/t2Op2KmgfxLtQN3x6xl1x697/vTyPP7zbWcjUhLLnb/amaMnDTA7DSVVrP0eHkmCkWc5FXCJuuvXHaqrp8GWVjUZGq/RHzM0XsKJRowr+gDeusy4WAmqLdTW686e633r+deP/zIoo8QnIxGqrr9hU9EHIEMhqm+7jUhtLTGfjw0biz7Qiz7Qiz4AKWl++WW8n3zaz5mbIxqJ8fmzS7vcr2Z1q170waYR2MG2CJ88tYhYLPEvCipKdyVD0QdQMqbIAAEAAElEQVRwxfPzzE5BSSVPzTI7g+5pWgWxFD9fThCq8OvgpZ8qzU4huQRbjI0nYyn/y7/et96QOEsat383J5VEW1uJ1tdv/UAkQqiykkhdHbGNRd92pMuSDsG2CLHojhduvuYQkWDUwIwURemOiLrgohgp2Gp2Bt3Xln5LU5lBFX4dXHnIOLNTSC7uPLBnGhfPmQcpPhRveO5wrKL302tnjUySK3kGsObm4poyZevtJSW4xo/HNmgQjhEjughiJWPvvfoow8TizrL3qjFL+agctZSDklI0YXYG3VOclT7D95V+ULaz2Rl0X4bqaNsfUvsMewcIIRhbZNy6dE+fmQZTVc79Emw9XFetM44cuGh27+MkgccPfpwMW8+XYdDQyLRlcv7O53NgxYF9kFniGnDnHWQdewzWkhKsRUVkHngggx59BGGzIYRg4P33kXXkETjHjcM1ZTKOsWPxTJ+Oa8pkPHvszsD778cxdKjZL6PfzLpyCjklboQAzSLIyHNQMCADu8uCEOD0WNn/9DFMPmgQBQMzyC/3kF/uYez0Ug48Mz2bBymp69tr9zU7hS557BY+vHxvs9NQUslZH4G72OwsunbCk2ZnkDZUcxdFURQlYajmLj2jjo+KoijpQy3n0AeufnY2z/y0wZBYP1+/Px5Xig/diMXgob2hqpcdmawOuGA25A40JK1EVuWt4qz3zmJN6xoABIKKrAoOrDgQX9jHJ2s/wRfWG5n4I34isQhCCKyalSFZQ7hu2nVMKJxg4iswV2DxEtZfeSXhDRtwTZiAvaKC4NKleHafRv6ZZxJpbKTq+utp+/prEBqZBx9E2V/+0qNF35PZuqWNfPSfRXgbAzhcVkbsWkx9pZfGqjYy8p3sdsQQBo7JY97HlaycW0dusZuph1XgyU7x7yolbbX6w+x+84d4Q4k7d3V4oZsPLt/H7DSUVHPnJGhaYXYW2/fr52FUeo1iMou649dBNBpj2B/fNjTmqlsOMzRewnn0YFjztTGxhBWu76SJRwqJyRgzn5lJc6h5h2PYNBtvHfsWJZ4SAzNLDrFAgCXTdkcGAp0+nnfaqXi//IrQsmXttmcdcQTlt9/WHymaytcc5IlrvkJur0mEgJ32HsC8jzc3syoYmMGv/rhrP2S4feqOX8+oO37ds9MN79ISiJidRpf2H13Iw781//dQSRHPnwE/v2h2Ft1zw46fE6UTtZyDwR78bFnXOyntrf3OuFgy8Q/MvbW0cWmvij6AcCzMZ5WfGZRRcmn7YfY2iz6A5tff2KroA/B+/HFfppUwVs+v337RByBh2eyadpvq1nppqum6M6qiJKNkKPoAPl5Ua3YKSir55RWzM+i+X14zO4O0oAq/DnYboroK9ZjNbXYGSaXQXWhInPKMckPiJBtbeVkXj5eDdetR7Jb89Pjdzixwdms/d7a93c9Wm4Y7076NvRVF6Q8ZDovZKSipxGFg1/W+VpK+01f6kyr8OphcYezJ4bBunoQlteOfMC7WqMONi5Wg8px5nDb2tE4f81g92LWuT773GbgPu5ftbnRqScExZAhZh7f/nGycu2fJyaHkj9dSdPVV7Z9ksVD6txv7K0VTDRiVy4DRue22adb2vezLRuaw76ljyMh1bHp8j+OGqyUclJR17szk6Oj7xJm7mZ2CkkrO+sDsDLpHc0LeELOzSAtqjt82nPv417yzqKFXMT65fAYVhVkGZZTgIiH44HoQFtgwH3z1erMWmxMcWeDMhaY1EGgCISDYDFYnaDaw2PS7hkfcCYUjzX4l/abaV80TPz9BZWslBw85mAGZAxiVN4pQNMTihsXEZAwE+MN+qrxVlHpK8Ya9jM0fy5Ac9QUZXLmStjlzyNx/f4SUhFaswDFmDJpDL2Yi9fV4P/8chCDr4IM3bU8XdZWtrF/WRH55BqVDs2mpD9C0oY3MAif5ZfpSItFojLo1XrIKnLgS5G6fmuPXM2qOX/fVtAS44H+zWVXTii8YJSoh12OhuS2KP97zxWOFcAxCMXBZIRyBGOC06X3MYjHIdtsoy7JR2RyiLRAhFNPXCZRAnttKc1uEYPzUymMXFGbYCYSi1HgjxNCvuNsExAQQA5tNY+bIAu47ZSpCJMmCg0rykBL+O0vvxSAjoDkgHNA/tLEgoOnbYmGwuiDiRf80oxdksTAQBYS+ryMTZAxCbUAkvl3EnyP1vwur/mfZZKhbCsGNvRviFxdtLgjHF5ef9SSMP6Jf3opUkLBdPYUQA4H/AMXon4QHpZR3CSHygGeBCmAVcIKUsrGv8thRH/Wy6AO4/tX5PHHWdAOySQJWO9gy4Ku7IBoEhL6wuz0r/l1hhUAjhIN6IRhuBYsbLJq+CPzIgyErfYYuNgYaue7L62gONnPV1KtojbTy6dpP+deP/8KiWTh2+LG8s+odpJRMKJyAJjScVidLm5Yyu3o2ew3ciz3L98SipdewoEhjI82vv0Hbd9+hedxgteJfsAAhwZKbS/1//ovmdJDzq1/h3nlnco4+mkhjI95PP8UxbBiOYcPMfgn9pmBAJgUD9GE+/tYQ9ZVehBA01/jJzHNid1qxWDSKh+gXpxrW+2is9lE+MhenJz26n5ol2Y+PyeqLpXX8vK6ZtvDmC94bWtt3+fRtMRXQv8Xf28Kb/17rC1Pr22IDEI2HrPG1n0voC0l8DcF222KgF4bx54TDMZZsaKW61U9Jlpo6oRispQqqF0BE7xSun6OhfxA3/iXm1/8aaW3/3NiW8+klEIVgU4d/YIsP88afZfz3Y903HfaN/36Et/h3bIlx0TFd9NkdPyFEKVAqpfxRCJEJzAaOBn4LNEgpbxFCXA3kSimv2nak/r+iWXH1m4bGS/munlLCzQMh1Nr1vtujWeH8b6FguDF5Jaifqn/i1HdO7XWcETkjePLQJ3GnyRzLtu+/Z/UZZ0I43PXOQM6JJ5J95BGsPetsYm1605LCSy6h4Nzf9WWaCadycSNv/nsukfCmozzODBvHXD6ZvFIPAD+8tZJvX1sJgM1h4YiLJlI6LNuUfNPhjl8yHx+T1dH//oI5lYnfNfCRU6ey39gkWHBbSQ6/vAHPnWx2Fl0bcTCc/KzZWSSFhO3qKaWsklL+GP97K7AQKAeOAjZOCnsC/WCXMG56Y4HZKSSfuc/0vugDiEXgne2e46SEKz+70pA4S5uW8vZKY5ceSWQ1d/+r20UfQNNzz1Fzxx2bij6AuvvuI+r19kV6Ceu711a0K/oAAt4wP767GoBgW5gf3lq96bFwMMr3b67s1xzTTbIeH5NZMhR9AJc/P8fsFJRU8vLZZmfQPUvf0cdRK32uX5q7CCEqgEnAt0CxlLIq/tAG9KEunT3nHCHED0KIH2pr+6+98fz1Lf32b6WMlvXGxWrr/RDbRLdxYXYjNG015CJ1RRt7OOItFiPa1NRukwwG2xWC6SDg67xY3rg9HIwRjWxdGCr9I5mOj0rf84cTd4F5JQlFQ2Zn0H1Sffb7Q58XfkKIDOBF4BIpZbuqSurjTDsdayqlfFBKOVVKObWw0Jj2993x9Dl79Nu/lTJ2Pce4WNMvMi5WgjptXOcdPXvKbrFz8JCDDYmVDHJPOL5H+ztGjCD3Vye22+aZOQNbUZGRaSW8MXt0vvzF2Pj2jFwHg8bmtX9semmf56Uk3/ExmblsydHE/KRdB5udgpJKdjqx630SgSNHb/Sn9Lk+7d0thLChH9SeklK+FN9cLYQolVJWxec51Gw7gjmuPXQEN7211JBYC68/0JA4Cc2ZCed8Ao8eAhH/jsXwFMOBf4FxxxiaWiL63c6/ozXYylOLniImY4zKG0Whq5D5dfNpCbWgCY08Zx5NgSYkkhxHDlmOLArdhaxpWYMv7GN8/ngum3pZWq3ll3fqqWjZ2dTdex/hKv2miNi4Xp/NhhBCX9jdYiFzn30o/fMNaB4P1vw8vJ98gn3YcPJOSYK5DgabdOAg3Nl2Vs2rI+AL486yM3K3EgaP27x0zUHnjGf+J5U0VrVRsVMBw6ekV3FshmQ9PiaredcfyLSbPqS+LXHvZs+aXM71R44zOw0llRx9D7TVw5IEnhZiy4IrFpudRdroy+YuAn2OQoOU8pIttt8O1G8xeT1PSrndSU9q8rqiKEp6SJPmLur4qCiKovRYwi7nAEwHfgPMF0LMiW+7FrgFeE4IcSawGjihD3PYIeP/702MmuJy+9HjOH5ahTHBEtWab/S7ffRyYq4jB87/CrJT/y5WS6iFG7++kY/WfkRMxhiZO5Ijhh7BU4ueYr13PdEtxrprQtPX9NtCriOXl456iQJXQX+n3u+ira1suOHPtH7wATIaRfN4QAg8u+5KyZ/+D2uB/h74f/6ZmptvIbR6NZ6990YGg/i+/grniJEUX/dHHEOTYwHn3opGY3z94nKWza4mM9/F9FnDKa7I4tvXVzD/40oi4RiZeU72PGEEpcNz+PzZJaz9pQGbw0I4GCUSioIQDByTx8wTR+LOUq22+0DSHh+TVXVLgL1u/5hAOLEbSHx4+V4MK8wwOw0lVYQDcMugzUs4JKpzv4aSsWZnkRbUAu4d+AIRxt3wrqExU3o5BynhrwV6R04j5AyES1K/s+q1n1/L6yte71WMiqwKXj+mdzGSwfpr/0jzSy91+ljGXnsx8IH7keEwy/Y/gEh1daf72YcNY9ibb/Rlmgljy6UZQF+6Yeohg/ni+WXt9tMsgqGTCln2w7ZHE1bsVMBh5+/UZ7l2Jh3u+BlJ3fHrnr1u+4jVDTs4FaEfWQQsvzmFzxmU/vXvXaEuSYZR3pAcnXfNlrDLOSSr/3t1ntkpJJeW9cYVfQBNa42LlcC+rfq21zFWt6zueqcU4Pvm6+08pi8OG1y5cptFH0Bo+XLC1ekxXapyUfvupwFvmBVz6rbaLxaVVC7cfqfUysVq7XAlNSRD0QebF4JXFEMkS9Gn9BtV+HVw2QEjzU4huWQUA8K4eM4c42IlsNH5o3sdI9eZa0Amic85dtvDP5xjxgBgHzgQLTNzm/tZi4ux5udt8/FUUjCo/ftgtWuUDMvaekcB+QM8241VOFANOVNSQ56rT3vZKUpiyigxOwMlwajCr4MBecae6Eyv6OSEK5VYrHD4ncbEEhqc/KIxsRLcNbtew5i8MZt+znXkcsLIE3BYHN16vlVYeeTAR/oqvYRScu21OLYs/iwWABwjR1J6418B0Fwuym69FWt8qQbXlCk4d9KHKNrKyym77bbNHUBT3C6HVjB4fD4IcGXZ2e+0sUw9dAhDJ26eD2q1acw4YST7nTaW4iH6d5TNoSEEiPh1nPwBGexzSu8vUChKInjsjN2MvETZZx48ZbLZKSip5OyPzc6ge4681+wM0oaa47cNLa1t7Pq3jwmgV8cSsAER9BYmLsAONAOFDmgIwsZ2HBZg8kA3z1+wT7/mbKpYDKrmQaAZ7Jlgs4EjEwJecGaDMws2LACrWy8WfTWQWQINq8DmhLyhkD/E7FfR77whLwKBy+ZCExrhWJhAJICUkmA0iMPqwGFx0OhvxGPz0BxsRiIZmDXQ7NT7XdTrRUqwZHiI+XxYMra+SCNjMWJtfiwZnvhzfGgeN0IkwymfsUKBCFa7BU3b/NrDwSixWAyr3YLFsvm6X8gfwea0EAnH0CyCaCiG3aQ7JGqOX8+oOX49s6y6lXlr6vGFYgQjEVbUtWKRErfdii8kmTIsj9U1PoozHNT6Q4iIxGoTrG8KkO+2UZznpjTTRVskSkWemye+WcOIfCdCaISjMTKddnzhMP5giFyPG7dNw2qx0hwI4QtGcFghw2GDmKA1FKGlLUiDL8ABO5Wx16jO19xUlF6rXgTrF0DzGsgeALEAWF3gyocN86BqCQzbEzQBLVVQsxQyCiEjFzylICP6dlcOtDWBRYO8wfr0nFAQ3NnQXKWf7wE4cyEjD1prwe4Giyv+b5dC3XII+qBuEex8Akz6lZnvTNLp7TFSFX6d8AcijDGgwUuBy8IP16fJAttSwqd/h6/uhJBX3yasesEnNIhGINi0eX9h1Qu+WBTsHtjtdzDjCtDS4yZ0nb+OV5a9wlfrviIUDVHsKSbbkU2xu5iZA2by4pIXqfRWcvKYk5kxYAbhWJgH5jzAK8tfwW1zc+mkS9lncBpdWIgLV9fQ8tZbaC4XWYcfvqnAA4i2tFD34IO0ffsdMhrBMXo0GXvtRXjFCpzjx5MxY4aJmfevWDTG8p9qaapu03+lhGDYpCIyC5ws/7GG6pX6WuHFQ7IYNrmoXRFoNlX49Ywq/Lrvs6U1nPX4D4QSdCLdUTuVctdJ6o6fYrDvHoa3rkC/hZGAdj4ZjlF3/LpLFX59oOLqNw2LlWGHBX9Jgw5dT54Ay3pZLA/dB059xZB0EllNWw2zXptFY7B7jTOu3uVqXln+CosaFrXb/oepf+DUcaf2RYoJKVRZycrjZhFr1jt/2YcPY8iLL6I5HES9PpYfdBDR+vptPr/g/PMovOii/krXVO88uIDlP7ZvZmOxahRVZFK1rH3ntCE7F3Doef3buXN7VOHXM6rw654PF1Zz5hOJ/z7tMjiH58+bbnYaSqr4+Fb49Cazs+jawGlwprEd9VOV6uppsJdmVxoazxsyNFxiCrT0vugDWPEx+LbuPphqXl32areLPoAH5j2wVdEH8PD8h41MK+E1Pf/CpqIPILRsOd5PPgWg9b33tlv0AdQ//gQyYmAH2gTVUuffqugDiEZiWxV9ACvn1tFU3dYfqSmKaf74ynyzU+iW71c3mZ2Ckko+v93sDLpn7TdmZ5A2VOHXgSX9pgIpSvLa+Pva3Tl8aTjXT1EUEEnR2kVRFKVvqcKvg6MmDzA0XqY9DQ42ziwYcUjv4wzbDzwFXe+X5I4afhR5ju4vLXDezue16wC60dk7nW1kWgkv5/jjsWRnb/rZMWIEGXvvDUDmAQdgKdj+Zyf/t79FxDuCprKsAhfDpxZttd1i0ygbmbPV9qETC8kpdvdDZopinpuOGW92Ct2y6+Acs1NQUsnMK83OoHsGqeHN/UXN8etEIBBhtAHNXUozrHx93UEGZJQEpIQv74LP/g6hVn2bsOkdoITQm7sEGtk0uVjYwOaGWFhv7rL7BTD94rRp7lLvr+fV5a/yzfpvCEaClHhKyHJkbW7usvRF1rau5eQxJzO9fDrhWJiH5z/My0tfxm1zc9nky5g5cKbZL6PfhWtqaH37bYTbTfahh6J5tmju0tpK/UMP4/tOb+7iHDWajH32JrR0Gc4J48mYnj4HllhMsuKnWppq2tDiwxiGTSokM8/J8p9qqVmlN3cpqshi2KRCNNXcJWmpOX7d9+WyWs58/HsCkcQ87zl2Uhn//NUks9NQUs0PT8AbF5OwzV0mnw5H3ml2FklDNXfpI15/iMufmc2iDU0EAjE8Lg2Xy0WGNYY/LAlFI/iDUTx2jarmKBlOcFgFG5okmS6YMaaE246f0q85my7Yqs/Rs2dAsAVceRBogqwBUPk9WJ16ARgLgT1LX48tsxjql0HeML11cJrxhrw4rU6sWuet85uDzWQ7sjt9LN3E/H7QNDSHAykl4XXrsOTmIqxWNIe+/qGUkmhTE8JiwZK1eQ3NaEsLWkYGIk0uLGxPsC2M3WlFaAIZk4QCERxu2zb36W+q8OsZVfj1zJINLTS2Blje4KM408GCtc2MH5hDhsPKkg0tWCxQ4HHhclpx2jSikSjzKlvZZ1QBi6u9DCvOZFWNj3WNPuxWjYmDclla18rkgflsaAqwodnP8GIPNd4gkXAMbyBClsfOwBw3q+t9ZLqseINhAlGJQwiaAmEG5rrJzXQypiTF1/1VzFOzGKrmQ2YZaBKiIahZpl+YLx0P4TZAA1e2fi5mz4Q134MrF3wbwOIERwbULdPP4Tz5IDWQMfDH5443rwZPMQgJLev1v2cU6Bf6Wyshe7Aey9cANhdklelxhu6VNhf9jdDbY2R6rGjcQxP//C5N/g5NIIIxaPJ1sre+el9jGDZeTfG2wXOzN/Dc7Dc5Z88Krj18XJ/ma7qgF/53Aqz+sndxnDlw5ntQOMqQtBKZN+Tl6s+v5rPKz8hx5PCHXf7AEcOO2PT40sal/OHTP7C8eTlDsodw+8zbGZWX+u9LZ2QsRvWNN9L4/AsIi4WM/faj9f33IBTWd7DZyD/rTDL33Y/K3/+eSHU1APaRIym94Xqqb72VwNx5WMtKKbv5Fjy77WriqzGPtzHIuw/NZ8OKFjJyHey07wDmf7yO1oYAxUOyOOjs8WgWwbsPLaBqWTMZuQ72OWU0g8blm526ovTa4g0tHHr350RjO/b8m95ZbGxC2/DIaVPYb0xJv/xbShqIhOBvJSCjXe9rpkP/AbueZXYWaUHd8etgZZ2Xff7+qaExV92S4ss5fPQ3+Ow2Y2KVT4GzPzImVgK768e72nXltGk2Pjj+A/Kc+ty/k986mXm18zY9PiZvDM8d8Vy/55kIWt56i3WXXd7lftayMiLr17ffVlREpGZzh0trcTHDP/owLeb6dfTewwtY+sPm90IIfYT2RkMnFWK1ayz5tnrTNlemjdNumo7F1n9XY9Udv55Rd/y6Z+qN71OXBG22nTaNRX81YM68ogA8dmjvL8r3lz81qjt/3aCWczDYm3PXd72T0t6GeV3v013VvxgXK4EtbFjY7udwLMzypuWbfl5U3375hsWN/XO1OREFFi7seifYqugDiHRY4iFSXU20ocGQvJJN7Vpvu587XvOrW9tKXYd9/K1hvE3Bvk5NUfpcoy/xiz6AQHgHb0kqSmeq5pqdQfc1rzU7g7SgCr8OTtm9wuwUks/QvY2LNSQ9GpbsXrp7u5+z7FmMy988JHha2bR2j08rbf9zOvHsvnvXOwmBY+zWnU/tgwe3+9kxYgTWwvSbSwowcHRuu581a/v5ewPG5DFwdPtus9mFLrLynX2em6L0tcH5ydG5NrfDfFtF6ZUxR3S9T0LQIHdw17spvaYKvw5y3HZmjsjtesdueuas3QyLlbB2PQd2Oxe0Xh6wyibD0fcZk1OCO2XMKZw5/kxKPaVMLJzIv/f7N27b5hOTP+/xZw6qOIgiVxEHDD6AG6ffaGK25vLssQcl1/8Je0UFjpEjKbrqSqxlZfpYRYsF28CBlN1+OwPvuQf37rsj7HaEw0Hm4Ycx6LFHyZ51HNbiYjwzZlB+911mvxzT7H7scMbOKMOT42Dg2DwOPW8nBo3Lw5PjYMwepUw/bji7HT2UcTPL8eQ4GDA6l0POm2BKgxdFMdqrF0wnL8GLKo9d44Vz9zA7DSWVHHM/uLde3iexCPjt62YnkTbUHD9FURQlYag5fj2jjo+KoijpQ83xUxRFURRFURRFUbZLFX6KoiiKoiiKoigpThV+iqIoiqIoiqIoKU4VfoqiKIqiKIqiKClOFX6KoiiKoiiKoigpThV+iqIoiqIoiqIoKU4VfoqiKIqiKIqiKClOFX6KoiiKoiiKoigpThV+iqIoiqIoiqIoKU4VfoqiKIqiKIqiKClOFX6KoiiKoiiKoigpThV+iqIoiqIoiqIoKU4VfoqiKIqiKIqiKClOFX6KoiiKoiiKoigpThV+iqIoiqIoiqIoKU4VfoqiKIqiKIqiKClOFX6KoiiKoiiKoigpThV+iqIoiqIoiqIoKU4VfoqiKIqiKIqiKClOFX6KoiiKoiiKoigpTkgpzc6hS0KIWmC12Xl0ogCoMzuJJKLer55R71fPqPerZxL1/RospSw0O4lkkcDHx3SQqL9DitLX1GffPL06RiZF4ZeohBA/SCmnmp1HslDvV8+o96tn1PvVM+r9UpTeUb9DSrpSn/3kpYZ6KoqiKIqiKIqipDhV+CmKoiiKoiiKoqQ4Vfj1zoNmJ5Bk1PvVM+r96hn1fvWMer8UpXfU75CSrtRnP0mpOX6KoiiKoiiKoigpTt3xUxRFURRFURRFSXGq8FMURVEURVEURUlxqvBTFAUhhNjyz1SRaq9HURRFURRlR6nCr4+oE87uE0LkmZ1DOhNCCLl5sm+5qckYbOPrEkKUCSHU952iKIqiKGlLnQgZpGOht8UJpyoAOxBCOLf4+9HAJfG/q/fKBFt8Vs8GXhNCOFLpv4UQ4jTgZsBmdi7pLJU+U4rSFfV5V1Ldlp9xdWE1eVjNTiAVbHnHRAhxPJAHrABmSykbTE0uwQghxgFXCCFuklIuBUqB+vjDFiBiWnJpTAhxMHAycKSUMhj/Ek/6lr9CiDOAycBNUsqg2fmksy2+I38N7AL8DMyXUn5namKKYrAO5wTHAG5gDfCjlNJnanKKYoAOn/HzgRIhhAP4q5TSa252yvaoCt0AW3z4LwPOB1zAjcCBZuaViKSUPwMO4I9CiAFACeCLP6aKvn7S4UqdBSgDpgL7A0gpY8l4xbqTuYp7ov9ObnxcXewykRDiHOAaYBEwBThTCHGIuVkpirG2OCe4HLgIGAzcAhxgZl6KYrT4xdUT0Nf1uxD4nbkZKV1RhV8vbXGimQfsLKXcB/1OSSPwvBDCKYRI+yFmQqcBSClPQi/2LgUygV2EECcKIX4jhDhGCDHVzFxTXYcrdQPR/xs8DlwAnCCEOBz0k5dkKv46zFUcBCClPAO4F3hdCGGXUkZU8WeO+Ps+CjhHSvkgcBMwB9hDCGFNps+aonRm43z1+PGuFJgUPycIA83o30MuNSxOSVZCiIlCiNHx8wM7sBNwHnAI8Blwl/p8Jzb1H2cHCSEKYdPJ8U7xIZ0xIcTr6Ff1DpdSRoFZwAgTUzXdxhPy+F2kk4UQh0opLwDswHHoQzx3Rr/jtA+ghsf2kQ5F35XAPcAL6F/cnwL/A84SQhwHm69cJ4MtXtfvgXuEEHcIIc6XUv4e+BL4TgjhUHeW+0cn854j6NMLLosX4ZXA18CugDuZPmuKsqUtCr3ZQogD45/lQPyx54C9gKPi5wRHAUPMy1ZRdky80DsUvbgbI6UMoU/VuQ04DDgi/j3/f/E7gUoCUoXfjttXCPGKEOJ3wE1CiGzgGyAfuC1+Z+E09GFNaT3eeYsT8ouBi9HnOiClvBB4FX1e3/1SyouBS6WUK8zKNdVt8d/iMGA/KeWR6J/PPaSUq4DXgTfQ7/xlJNtdGCHEkejDTn6NfiVyIoCU8nRgIXpxqxov9IMt5zgJIc4RQuSi331dAfwpvtvA+J/qWKQkrfiFzSr0KR53CyH2l1I2AnOBCuAGKWVYCHE6cB3xolBRkkm80HsC+BD9vHcg8DkwAfgH+s2PWcAxwFemJapsl1AXWXtGCDEeWCelbBRC/ACMA0ZKKdcKIXYCDgeOAJajn3T+Kj6vLa0JIUqAh4EzpZTV8Tsvwfhj/wNa0YcaRtWVf+PFh8/+Nn73a2PDgQL0RkT7oF+NDgohhgBrAY+Ustm0hHeQEOJkIIo+z/bX6HfeQ0KICinlKiFEafwETekjHe4qn4Y+x2k9+pXhZ4EQcCr6cFw3+tDPuSalqyi9svEi0haf+d8C/wecjv5dejr6fP/5wB7ACeqcQEkmHaZRIIQoRp/LtzNwDvrn+0QgBuQAF0opF5iQqtINqvDrgfgX/F/Rr1o3AWcD+6GfQM+QUkbjjTIGA1lArZRynUnpmqqTLwo3+t2k26WU72yxfaiUcoUQolhKWW1GrukgfmXuKeAHKeVlQojp6M0GvOhFX0gIcSkwEzgx2TpgCiG0+FDiGcBjQLWUcnr8sQuBkeh3k9Uwzz7UoejLAs4AnpFSbhBCXI9+oeFl9DuvBUBYStlkVr6K0hsdPu/5QFP8POA09OLvN1LKr4UQu6BfjFoppVxrYsqK0iMdPuMTgTqgGn3Y/lXAePQGag3o3+8xKWWdOdkq3aEKvx0ghNgV/SreDfG7V88DQ6SUU+NDzWxSyhfNzdI8Hb4osgEtfof0OvSmLu9LKRcIva37LOB0KWWLiSmnrA7/LQ4BbgeelVL+VQhxB/r8yp8AJ/o8v18nw9Xo+Hya6nix92v0OTMfALPRC1oNfThKIfodp9PUFci+tbH4jv/9D+i/28XAA1LKm+Pb/wSMBu6TUn5uWrKKYiChd++cAniAP0kp58ZHH/wf+gWnt01NUFF6KX4B9WTgC2AAcBp6I8Or0OewXiClXGxehkp3qcKvG7Y8oYn/7Ea/q9ACXC2lrBdCvAqUozcs+ZWUcqE52ZqrQ6FxGTADfTjXXegn5X9E7+xXjb6W16xkKDSSXfxEfDr6/Mq9gNfQ51mdiT5c2Q7cI6X8xbQkuyl+9/IP6AcgN3A5+l2kc4DfoA+v2h19nkEdcIeUcr452aYfIcSewJXAZejzLP8E3C2lfDT++FXAE1LKDeZlqSjGEEKciz6v+ADgB/T5e9dLKd+LN7i4EP2716+mMSjJQgiRG5+nunF96kvQO3f+CTgW/Th7UHz3C4Gn4w27lASnCr8uCCFcUkp//O8HABEp5cdCX6LhIfTGJH+I39GaCSxP1+GdWxJCnId+MDwcvUg+Dr0gfkEIsTP6/J65Uso1JqaZFoTeYvw14GQp5ep44fQk8K6U8qb4PjYpZdjMPLtLCOECzkVfA3II+p33X+IHp+uAa6WUb4r4sg1qeGffEkKMBXaVUj4e//td6AX3SVJKGf/evBl4VEp5r5m5KopRNl7kjI9k+S/6MW5v9CZvp6Pf6XtDCJGlRrQoyUQIcSD6cjvXxi9gTAaqgCPRP+dHAO+gr8m8r5RSNStKIqqT2nYIIUYDTwghMoUQJwF3AjcLIW5HP+E8GxDAffE5ap+la9EnhJgghHh1i26JfvTJvr9Dn/B7CPA/IcTpUsq5UsrXVdHXNzrpWCnQh2S44z+vA54BrhBC/DW+LeGLIyFEjhCiKH4h5iNgA/pQwlnxZkHPA38BHhBCHC6ljKiir2/FP2t56OuTDY3fMf4P+nymg4UQbinl+8D1wK+FENmdfD4VJSl0+Ox6AKSUN6J/xx4ipTwyfjHNCxwd//yrok9JNqPQ5+5dIYQ4Qkr5I/oorcnATfEeAF+g97ooMi1LZYeohYy3QQgxDDgafU7aY4BFSjlOCFGAPqb5TPQuleeiF4TpXkSvRO+m+BxwfPzq/0DgYODs+J2m94AbhRAvAq1q2IvxOpmIvTQ+FPk14BkhxCFSyvVCCD/65/a/kDTr9U1CX+w7F/1K4w3ov5+jgeOEEM9LKV8UQoSBhB+ymuy2GAL/hdDXNb1eCDFfSvl3IYQT+JW+m/g0fgf2Yyllm7lZK8qO2+K79XfATCHE91LKO9HvcAeFEGejL9S+HPir+rwrSeppYCjxrrTxCxjPxi987CWE2AN9+PKvpJS1Ziaq9Fy6FyvbYwP2Rb+r8AawpxBiZLxb0T3o793FwGAp5QUyTVvECyEK4mPBveh3+EJCiJfiBcha9LtLuwohzkdfv2sXKWVLkhQaSaVD0Xc++ry3/8QnZT+E3tXzSyHE3cCfgaeklCtNS7ibhBADhBA56HeOp6Iv0/CWlLIe/QC1Ir79VCGEVUr5mlRrQfa5LRq5HIF+EfEFYLAQ4mIp5UPAZ+gXyKbH91cnwUpSEkJoW/x9BnAW+vfpKfGGRRnod7r3Ba5Fn+O32oxcFWVHCCF2EvqSZKB36AwBY4H7gJOFEPugD/+0oS/jcKkq+pKTmuPXgdDXMWuQUjbHP+gvAL9Hv/U9Dn0+36r4HcHT0ZsW1JiXsXmEEIei33VZhX5n6Y9CiAzgfsAtpTxWCHEmerezGehzflSTjT4mhDgWvdHA9ejrRu0BNAK3oQ/V8ABrpZTLTUuym4QQRwHXoK8Dl4u+3MTf0LuQPiulnB2/CnkV+vDCf6ihVX0rPt+jQkr5ktCXr/kIOBS9qcVB6PN6F0op/yWEOBX4QEq53ryMFcUY8cZFWUCWlPIZIcQI4G7034H/AjVAbvyilKIkBaEvRVKLfqH+UmA1erfvu9D7A+Sid/S8Pz56wyKljJqVr9I7qvDbghBiJPoCw4uBS6S+9tTp6F0QH0UvXsYDf5T62nPWdJ1DJIQ4GL2Rxu3oXxKXoy/E7BdC2IHH0RvhnBrfP1sm4YLgySbeyOUT9KUODohvOxT9SrQf+LdMkvUS4xdeHkC/w7cKyERvSvMj+tDioehNQ4qACuAzKWWDGbmmi/idj1+hz2++S0r5qhDiG+DY+BBiO/pn7STgaynlfSamqyi90mEUxVno6/jOQZ/jf5yU8mchxFD076U3NjbLUpRkI4TYF31JpBuBMDAGvRCcK6V8Mn4ufDD63W6vGrWVvFThtwWhdwF8HL3Q+wi9CMxEv939I3qr5j8A2egnPtF0/PDHi4s69APfy0Jf1/BV9KGFFinl7+IngC+hL2h7ypYHUMU4nb2v8f8e/wMekZvXTzsKfTjknclyNVoI8UegWUr5byGEU0oZEEIMAp5HX5biU/S14iqAvaWUq0xLNg1s/KzFh90eDJyCPv95F/S7yxYpZVt8vt8k9BOGpLjIoCjbI4Q4CDgKfY3QBvRRQLuhXwT+RQhRgX4+oBZnV5KWEGI/9Jsck9GPrSehz/M7A31ePVLKVtMSVAyhCj8gfjLplFIuiTdvuRB9Dl8lMAL9Tt9y9A+/Lb5vWo9tFkIchn5l6LfA34Gv0JvdvACslFKeKITwANlqmFff6HA1+tfo80xWS7398iT0sfmvSClvie/jkVL6zMu4e7YoMO5Dv3N5Q3w4pyaljAohxgP/RJ9jmwtsUHP6+laHz1ox+pC2XwEXoM/hewW9u2cd0IZ+91+1+FaS0hbfQRr6Mf859EWrz0G/CFyMfuw7AH3h6kVm5aooRoqPELoV2F1K6RVCDEmGXgBK96V9V894cfJ/gF0I8bKU8hUhxAr0+SrvAWXot7xPRL97dT6Q9lc84uO8o+jjwK/dorjYD3hVCJEfv7OU8IVGEtOAqBDi9+jj7/8JvCGEOEfqXVXPBZ4VQoSklP9MhqIP2nUYfQG4WggxJT6XTwp9/cwmoAWolFIuNCvPdBAvuLfsZngJcAz6nL630RvutKLffX0U/TOZo4o+JVmJzd1qAQqllNVCiBOAe9G/Z9fGp4E8gd4Aw2tWropiNCnlW/Gv/e+FENM3Fn1q1FbqSPvCT0rpE0L8H/q8lH8LIUqBZejLNCyLn3CegX6l72kTU004Usp34kNg/i2EuF9K2QQcj95kI2RqcilMCLGblPLb+N2viegn4huH3s0F/iT0RYPvFkLMInkvVHwDfAn8Kn7Q+QGICb2VdD7q+6s/uDZ244zP8TgRfbkWX3zI57vo80EuQ7/T/xp6O3tFSUpbdKu9ADgsfiF4CfpIoP8AfxBC/ENKWSWEuEs1uVBSTbz4swEfCCGm6ptU0Zcq1FDPLcS71d0KvI8+fCkbOFNKubzDVUBlC0KIQ9CbvNzL/7N31+FxXNfDx793lrVilmVmZojjJA4zp2nD0GDhbZtCmnLK+Cu3adOmKSRpkjYNNNQwObEdmZktg5hx+b5/zFrSSitbvNrV+TxPn2juzM6cVeWdOXvvPdd8MPyk1nprbKNKXEqp54ExWut54e08YCnwBa316UqpazDn+H1Mm4uaxy2lVCHmZPIzgQ8wv1D4CHCt1npTLGNLdEqpi4FPAlcBXsxhnYcxiwTNwZzn/CfMntklwGqZ4yTilVIqX2tdFv75Wswve2/EnNdnDU9fSMf8AngD8HV5JhCJTCmVrM2lukQCkXX8OtBar8dcoqEac37facCl4XH+kiF3Q2v9EnAf5oLgn5Ckb3CE/w7RWl8M7AtXUyRcQCMVs6cazOTon5jFiOKa1voo5jIUXwcCmIUVrpCkb3CFe/K/gVkMqDX8gHsI82H4c5iVfL+EWeAioLX+lyR9Il6F56w/Fy5MBOYQ5i8BF2FWDb4h3J6EOarld5L0iUQnSV9ikh6/KMJd3E7g/zDXBdsV45DiglIqScsizYOim+qdzwK5WuvlSqlZmAsHuzDXnLxECp6IvlBKrcSs1nm71voNZa5t+imt9RfD1QtLtdZepdQ5mOXtr9Bal8YwZCH6TJlLE30N+L7W+uVw28WYoybWaq3PDrfdgfnZep8eocs4CSHinyR+QgxznSoq3oNZPONb4e3/YlZOPS1cnfZU4EOt9e7YRSzilTIXZP8B5jplH8ecS/kY8KTW+lfhY2zhfXcBN2utt8QoXCH6pcPSRFeGC7tNxhxd8DnMHu+ZmEs3nAN8ArhOa70tRuEKIUS/SeInRJwIV++8Brih45p1Sql/AnO01rNjFZtIHOGH4W8AduB04A9a69902O8EpgMN0qss4l14mOd3MZdn+AXmQuy/CM/n+wJmVe8Q8G1J+oQQ8U4SPyGGKaXUSZhr6fwiXFb/r5gl8w9hfgO9ArMn5oVw8vdVWW9H9MexIlbh5O9ezATvC1rrfeH9dwAfBS7UWvtjGKoQAyY83PNFwksTdRploQCLDO8UQiQCSfyEGKaUUsswk70/aK1/pZT6LjAXs8DAm5gLZhta68/HLkqRaJRSlvBSIZnANzF7O36D+UXDJzALOG2OZYxCDLTwnNXfAMu01vVKKbvWWpYlEkIkFEn8hBjGlFJLgAcwq8g9rJRaBBwNLyB8FebaUpdhDruTf8yiX8K9Gyrc6+fGXKPvB5jD3SYCV2mtt8cyRiEGS3hpol9ijrSoiXE4Qggx4CTxE2KYC/f8/R74q9b6N0opK+ayI/dgLqYt805Er3UazmYFgh22T8b8mzs7fPgngX9qrffEJFghhohS6jLgW4AsXC2ESDiS+AkxjB17OA/3/P0WeCSc/H0CeEOWGhF90Snp+xzmEOIWzKGdDcCrwM+01i90Pl6IRCcLVwshEpUkfkIMA50exI8V2Dg212o84AUKgSeA72it/xbDcEWCUEqdAXwPs6rhBZgLsp8FoLVuDg/9RJI+IYQQIv4ZsQ5AiJGuU9J3NXBFOPkLKqVOB/4DZGitizArKr4Ts2BFwlBKXQp8FnhQa/2y1vqzwGrgFcB97DhJ+oQQQojEIImfEDHWIen7NPA1YHO4xy8JuAr4/rGCGlrrdbJkg+iLY713HRQDqcBJSqk0AK3154CtwONKKbk/CCGEEAlEhnoKEWPhB/IC4CHgTq314fBDtwZStNYNx4Z9xjRQEbc69SovA8q01sVKqQnAg5i9fH/SWteFj8nTWpfHLGAhhBBCDDhrrAMQYiTq+CAeLt5SCTQBk5VSpccWC1ZKTVJKbZP1pER/dEj6voC5/MdBpdQRzHXL7sSs4OlSSv1Sa90gSZ8QQgiReGQojxBDrFPvS6ZSKkVr7cccercYs/cPpdQ1wJcwF2wXoteUUhlKKUv458uB87TWp2Euyn4O8GXAA3wGmI98GSiEEEIkLBnqKcQQ6pT0fQY4DygH/oc53O43gB0IAHOA67TWW2IUrohjSqnJmMWAfq619oTX5isFLsTs9fsa8FPgKPBV4OixnmYhhBBCJB75dleIIdJxnp5S6g7Mh/KPAj8Cfg18S2t9g1JqHjAeuE9rfShW8Yr4pZRK11rvVUr9CpiplEoF3gkXDZoH3K213q+U2oHZ49cqSZ8QQgiR2CTxE2IIKKXOAW5VSu0GtgEHMXtdbgTSgEuBfyql0rTWPwY2xSpWEd/CBVs+p5R6VWv9vFLqo0A2EATeDR/2pFLqz5jr9l2hta6IUbhCCCGEGCIyx0+IQaaUOg/4IeYaaQ3ALZhfuhybZ/UZrfUaYC1wrVIqK0rpfSF6qhmoAE4JD+/8KnAAuF4ptVRrfSfwIrAEuFlrXRy7UIUQQggxVKTHT4hBpJSaCjwFfERr/bJSKguYjFmwxYuZCE5RSl2A+cB+jta6OmYBi7inta4IV4ldBswCvgv8APg6cItSyqm1/qZSyhYuKiSEEEKIEUB6/IQYRFrr3cBzwCeVUq5wUpcO5GitW4DNmPP87gJ+rbWujFmwIiEope4EbgceBnzAdcDJwPcxv2i4Ivy3KEmfEEIIMYJIVU8hBkmnYi7/AHKAHZg9fldrrT3hfS7AorVuilmwIiEopRyYlWGfC8/vKwQ+AcwAfoY53DhLa10VwzCFEEIIEQPS4yfEINFaB4+toaa1vhHYD9wA3BIur+8M72uVpE/0hVIq4jNca+0FDgNXK6VytdZHgT8Ds4FLAKckfUIIIcTIJImfEIMonPzZwj9/EvgP8FelVNaxHj8h+iK8JmQo/PO5Sqnrw39rj2MWd7lZKZUNTAf2YA4lbo1dxEIIIYSIJRnqKcQAUUoZxx7EO7RZwsnfEmCy1vqfSqlnMCt6XqXlH6DopXDCpzts3wncA+wDcoGrgWnABZgFXqzAbVrrLTEIVwghhBDDhCR+QgwwpdSZwFGgSWt9VCl1Gmahjbu01q+FjxmltS6JZZwiPoV7i6vDP58CfAG4VWtdp5T6BWYP3ye11geUUmMx/w5rYhiyEEIIIYYBGeopRD91XHNPKXUr8HfM0vnfUErNATzA57XWrymlrACS9Im+UEqNAh5RSl0abroMs1jQOQBa63uAbcBTSqnxWutDkvQJIYQQAiTxE6Lfjg27U0pdC0wAFgD3A7uBLwHNWutnw4U4grGKUySEZsx5oreFF2f/Znh7oVLqdACt9RcxF2iX4RxCCCGEaCNDPYXop2NzrpRSm4F0rfXYcPs04GJgBfAdrfXGGIYpEoRSKg24AnP9x+8DWzGHe9qAN7TWr8YwPCGEEEIMU9LjJ0QfdBzeifnAjdZ6LlCplHoyvL0Ls+flDcwqi0L02bG/Oa11PfA08CTwNcylGn4G2IEVSqmkmAUphBBCiGFLevyE6KWOVRWVUrcD44FSrfXvwm0fAvu01teEt21aa3+s4hXxq9PfWr7WuqxDD3MmZo/yR4D/A9ZjrtNXGcOQhRBCCDFMSY+fEL3U4UH8k8AtwH+BHyqlfqaUStJaLwEWK6X+Gj5ekj7RJx3+1u4Gfhr++9JKqaXAKcALmL3KnwICkvQJIYQQojuS+AnRQ0qpU5RS+eGfC4GzgMuBxcAGYCbwG6WUQ2s9Gfh2rGIViSO8ZMOVwGe01i1KqYXAM4AnvKzDY8Adsji7EEIIIY5HEj8hem4hYA33uhwFPg5MBT6itV4JfA64Dvh/4eF4B2IXqohXnZYHyQGuBcYB88LN+cC1WutXALTWDeF5f0IIIYQQ3bLGOgAhhjullKG1Dmmtf62UmgG8q5Q6Q2t9MLxEA0opJ+Z6av8Fnjg2RE+I3ug0p8+lta5USn0T8ANnKqXKtdYvhvcbmKNB5W9NCCGEECckxV2EOI5OD+LZWusqpdTPgFMxy+lXAj8E5gJ5wJVa650xC1gkBKXU5zGHEI8CvgscwexhbgFe0FoXxTA8IYQQQsQhSfyE6AGl1Bcw5/B9TmvdqJT6Me1z/Moxh4GWaa2LYxelSARKqZuAG4CLMIu31Gutr1ZKzQPuxEwCf6619sYwTCGEEELEGUn8hDgBpdQdwI2Yc/kqji3PoJT6KnAbcIbW+lBsoxSJQil1G7AOOAc4E7gMCABJQDbQorWWdSGFEEII0Ssyx0+ITpRSeVrr8g5Nk4C/A6OVUjcAZyml1mqtv62UcgCWmAQq4l7HocQdpGFW6tygtb4gfNxngInAF7TWwSEOUwghhBAJQBI/ITpQSk0HtiulfgXs1Fr/EdgCXADcCvwNeBJYEl624Vuxi1bEuw7zR28HnMAe4JfAhYBXKTUm/POdwNWS9AkhhBCir2Q5ByEiNQHvA2XAVUqpP2AOs/u+1nqF1vpBoB44GbNnRohe67Rkw9nAPUAG5pcLnwbOx/x8/gbmlw4f1VrviEGoQgghhEgQ0uMnRAda6yNKqbWYxVouxKzceQ3wKaXUp4Gzw9s3yjwr0RedKsVOB8YDt2qt1yqllgJfxJx/fUv4mCStdUus4hVCCCFEYpAePyHCOvTC3AdozEIaJZgLZ28HvgdcD9ymtd4WkyBFXOuU9H0Wc+jw/cBFSikrUAT8FDhHKfW18MtaYxGrEEIIIRKLVPUUooNw8mfDHGI3EVgE3Ke1fkYpNQGztH5NLGMU8U8pdTnmkg3XYfYsfwr4A/B0+JD5mMuDlMQiPiGEEEIkHhnqKUQH4d4Yn1LqEeBt4Hda62fC+w7EMjYRvzpWilVKpWIOIZ6ptfYBz4Srw34Cs8DLP7XW62MXrRBCCCESkQz1FCIKrfUuzCGfFqVUUqzjEfErPI+vVCn1C6XU7VrrBsxhw1uUUr8D0Fo/gblkyDWAO3bRCiGEECJRSeInRPdWYxZ5EaI/OlaK/ZhS6mFgKvA7oEEp9UsArfXfgeu01o2xClQIIYQQiUsSPyG6obXeCVwjFRVFf2itjwDHKsVeALwK3Aj8CNgPnKaU+kr48KaYBCmEEEKIhCeJnxDHIUmf6I/jVIpdCKwHLgWagaegfUF3IYQQQoiBJsVdhBBikGitdYfkbw/wf5iVYu+RSrFCCCGEGEqynIMQQgwBpdQ02ivFfjfW8QghhBBiZJGhnkIIMQSkUqwQQgghYkkSPyGEGDpSKVYIIYQQMSFDPYUQYggppZKkaJAQQgghhpokfkIIIYQQQgiR4GSopxBCCCGEEEIkOEn8hBBCCCGEECLBSeInhBBCCCGEEAlOEj8hhBBCCCGESHCS+AkhhBBCCCFEgpPETwghhBBCCCESnCR+QgghhBBCCJHgJPETQgghhBBCiAQniZ8QQgghhBBCJDhJ/IQQQgghhBAiwUniJ4QQQgghhBAJThI/IYQQQgghhEhwkvgJIYQQQgghRIKTxE8IIYQQQgghEpwkfkIIIYQQQgiR4CTxE0IIIYQQQogEJ4mfEEIIIYQQQiQ4a6wD6Ins7Gw9fvz4WIchhBBikK1bt65Ka50T6zjihdwfhRBi5OjvPTIuEr/x48dTVFQU6zCEEEIMMqVUcaxjiCdyfxRCiJGjv/dIGeophBBCCCGEEAlOEj8hhBBCCCGESHCS+AkhhBBCCCFEgpPETwghhBBCCCESnCR+QgghhBBCCJHgJPETQgghhBBCiAQniZ8QQgghhBBCJDhJ/IQQQgghhBAiwUniJ4QQQgghhBAJThI/IYQQQgghhEhwkvgJIYQQQgghRIKTxE8IIYQQQgghEpwkfkIIIYQQQgiR4CTxE0IIIYQQQogEJ4mfEEIIIYQQQiQ4SfyEEEIIIYQQIsFJ4ieEEEIIIYQQCU4SPyGEEEIIIYRIcNbBPLlS6rPAHYAC/qS1/qVSKhN4AhgPHAQ+qrWu7cn5QqEQ/seeh6PlsHQOjjNOinqcbm4Gux1lsw3E24grOhTE56nG7spBKTXo1/MHWgiGfDjt6f07T9CDJ9BMiiNrYAI7gXp/M1ZlwW11Dsn1hIhGBzXBVrAmD/6/VTG8DPT9UfRMXYsPi6HYdLieqblugoDWUNnoZUK2m5pmH06bhbxUB+UNXnJSHNS3+mls9dPg8WMoRU6KAw04bRbSXDZqmn04rAaBoEYZ0OTx4w9qRqW72F/RRFBrjta2cOrUHDz+EBZDYbMY1Lf62Xiohvw0FxNykkl1jrxnFjFMtNSAYQVnani7FhpKIH/W8V8X9ENzJaSOam/z1ENTBaSNBpvLbGsohaQssNrNffZksCcNznsRxzVoiZ9SajbmTW0p4ANeVko9D9wJvK61/pFS6j7gPuDLJzqf9/X3oWhbe8PaLXjXbsG46XJsBTkAaK+PwH+fI7T/ANhsWE47FeuiRQP+3oar+qpN7Fj9Dbwt5biSxzDz5B+SnD5l0K63cc/DbNrzMMGQj/H5p3Pagm9jtTh6fZ41R/7DS3t+gzfYwuTMpVw35we4bCmDEDEEQkG+u+sJXq3YhFUZXDdmJXdPOH9QriXE8TTtC1L+so9gKzhyFaMus2NLk0EYI8FA3x/FifmDIe7992ae3nC0R8c7rAbeQKjtv9EoBYXpLo7UtmIxFKGQRvfg3BZDoUOazme9dcV4vnnxzCH50lYIAIIBeO7/webHzcRv2d3QUg0bHzX3O1Lg9tcgZ3rX1+55DZ75BDRXQO4s+Ngj8P6vYd1fAQ2GDc74Gux4Fko2gCsDUguhfKuZ+J3zbVhy+1C+W8HgDvWcAazRWrdorQPA28CVwGXA38LH/A24vEdn65j0dRD6xzNtPweLPjSTPgC/n+Abb6Lr6/sSe1za9eH38LaUA9DadJg96386aNeqadjD+l1/IBjyApqDZW+yq/jpXp+nwVvJc7t+hjfYAsDemrW8Xfz3AY623YvlRbxSsRGNxq+D/O3QG2ypLx606wkRjQ7qtqQPwFuhqXw7ENugxFAa2PujOKGn1x/tcdIHtCV73SV9YPYUHqk1/xEHe5j0HTs22lkfXnWQd/ZU9ThGIfpt679h02OgQxD0mYnbsaQPwNsI/7q16+uC/vakD6BiGzx9J6x7GI79Swj54fVvm0kfQGutmfQB+JrgxXvNXkUxpAYz8dsKnKqUylJKJQEXAmOAPK11afiYMiAv2ouVUncqpYqUUkWVlZXdX6XDJ62uqu60TxPq3JagQkE/rY2HItpa6vcP2vVqG7ueO1rbiVQ2FxPSwYi28qbBi3t/c3nXtpayQbueENEEmnVb0neMr6r7B0yRcIbm/ija7C5vjHUIPbK7LD7iFAmiYseJj6k/3LWtpaY96Tumel+UFx/n6xAdhKrdJ76+GFCDlvhprXcAPwZeAV4GNgLBTsdouvmr0Fo/qLVerLVenJOT0/2FnPa2H42JEyL32e0Yowv7En7cMSw20nOXRLRlFiwftOsVZC3GYkQO6xyd2/vrjUmbhcuWGtE2NWvw4l6eGTlcwaosLBnE4bBCRGNLNbBnRQ7nck+wxCgaMdSG7P4o2pw+LTfWIZyQUnDaVPn/UwyhKedEbisL5rTjDsZEqaeRkgf5cyLbJp3Z9bXHm/7jTIfRS7rfLwaFMu8tQ3AhpX4AHAE+C5yutS5VShUAb2mtpx3vtYsXL9bvv/wK+qGnuuyz33t7xHj4wJo1hLZuA7cb66mnYBSOjMQPwNdazb5Nv6KxZhtpOQuZNO8zWO2DM1cOoKTqQzbs/jM+fxPTxl7OzAlX9+k8h+u388q+B2jwVjA//3xOH3/LoM5xeK50Df8++j5Oi51bx57F8qwoY9eFGGS+uhCVb/nxVWvcEw2yT7VhWGVuj1JqndZ6cazjGEr9vT8WFRUNRZhx74kPD/HQu/vZX9VCIKRRgM2iCIQ0WoM1/FW4zWowKSeFRo8ft8NKWb2HmhYfxx6XrIbCYTXIT3Myf0w6W482EAiFCGmzsEuDJ4BGk2S3Ut/ib8vebRZFYZoTp92K1prdFU1t58x02/jBFXM4f3bBUP9axEi38TFY/QBYHXDqF8DXDC9+CXyNMHop3PAfsEUphFdbDK98Dcq3mwnk2ffD7lfg5fvMeYKZE+HSX8OO52DXS5A9BdLHw743ILUAzvwmjB45dTgGSn/vkYOa+CmlcrXWFUqpsZjfbJ4EfA2o7jB5PVNrfe/xziM3NiGEGBlGSuIn90chhBC91d975KAu5wA8pZTKAvzAp7TWdUqpHwFPKqVuA4qBjw5yDEIIIcRwI/dHIYQQQ2pQEz+t9alR2qqBswbzukIIIcRwJvdHIYQQQ00WjRJCCCGEEEKIBCeJnxBCCCGEEEIkOEn8hBBCCCGEECLBSeInhBBCCCGEEAkurhK/kNeH//0NBD7YgG7xxDocIYQQQowANc0+3t1TSV2Lr8u+vRWN/O39g2w8VBuDyIQQoucGezmHARM8eITAky9xbCXU4DtFWC47C+v0ibENTAghhBAJ6+WtpXzm8Y34AiGcNoPfX7+QM6fnAfC1p7fw6JpDbceeMjmLv318GRZDxSpcIYToVtz0+AX+915b0ndM8JX3YhOMEEIIIUaE7z6/A18gBIDHH+J7L+wAYG9FU0TSB/De3mre3l0x5DEKIURPxE3ih6fr8ApavWitu7YLIYQQQvST1prKRm9EW0WDuV3RGH3KSXmDN2q7EELEWtwkfkaUIZ1q+iSUkuEUQgghhBh4Sikumz8qou3yBeb24nGZ5KU6IvY5rQZnz8gbsviEEKI34maOn/XcFQQsBqEtuwFQMydjO2t5jKMSQgghRCL73hWzGZ/tZsOhOpaMz+Djp0wAwG41+M8nV/Dd/25n05E6Jma7+eYls8hJcZzgjEIIERtxk/gppbCdfTKcfXKsQxFCCCHECOGwWvjUGZOj7itMd/GHGxcNcURCCNE3cZP4AehQiOD7Gwjt3I9KS8GycglGblaswxJCCCFEHNl4uI6f/W8XFY0eLl9QyCdWytQRIUTii6vEL/jhFoKr1gOgq+sIVVRjv/salMUS48iEEEIIEQ+avQFu/sta6lv9APzk5V2ku+xct2xsjCMTQojBFTfFXQBC+w9HNjS1oMurYxOMEEIIIeLO+kO1bUnfMW/ukiUYhBCJL64SP5WdEdlgtaAyUmMTjBBCCCHizuTc5C4LrE/LS4lRNEIIMXTiKvGzrliIGh0uk+ywYz33FJTLGdughBBCCBE3CtJcfOuSmbjt5jSRUyZnc+fKrktGCSFEoomrOX4qyYX9+kvRTS3gsKNscRW+EEIIIYaBm5aP5+pFY2j0+slNkS+QhRAjQ1xlTqGqWnTxUVRuFsaYgliHI4QQQog45bJbcNlPXBwuGNK8vqOc8kYv58zIIz9NEkUhRHyKm8QvuHM/gefeAK0BsCyfj/W0JTGOSgghhBCJ7K5/FPHaDrP4y49e3MGTdy9n1qi0GEclhBC9Fzdz/IIfbGxL+sBc2kH7A7ELSAghhBAJbVtJfVvSB9DsC/LQewdiGJEQQvRd3CR+BIOR26GQ+T8hhBBCiEHgD+oetQkhRDyIm8TPsnhOxLYxdxrKYY9RNEIIIYRIdPNGp7FoXPtSUjaL4saTxsUwIiGE6Lu4meNnmT8dlZFC6MBRVG4mxoxJsQ5JCCGEEAlMKcU/blvKU+uPUtHg4aK5BUzPl/WDhRDxKW4SPwBjXCHGuEJCwSBKqRO/QCSUkA5iqBNXYBNCCCG6EwppDKPnzxBJdmuPe/lCIY1SdHlGCYZ0l0XjhRBiqMVV4hfcW0zguTfB7weLBctZy7EumBHrsMQg21m3kQd3/YDS1kPMyzyJT06/n1R7eqzDEkIIEUceX3uIn/5vF43eANcsGcO3Lpk1oMnYz/63i7+sOoDVUHzqjMnctXISh2tauOeJjRQV1zK7MJX/u3o+0/JTBuyaQgjRG3Ezx0/7AwSefd1M+gCCQYKvvIduaIptYGJQBUMBfrX965S0FqPRbKz5gMf2/ybWYQkhhIgjB6qa+crTW6hu9uELhPj7B8U8WXR4wM7/6vZyfvvmXlp8QRo8AX740k7WFdfw1ae3UFRcC8DWow18/smNA3ZNIYTorfhJ/GrqIBDs0h4qrRz6YMSQqfZWUOuL/P94b8O2GEUjhBAiHm06XNdxRSgANh6qG7Dzbzxc26Vtw6G6LtfYVtKAPygVyYUQsRE3iZ/KSgdbp5GpSmGMyo1JPGJoZDvzyHYURLRNT18Qo2iEEELEo0XjMroM61w6IXPAzr90QlaUtswu11gwNh2bJW4evYQQCSZuPn2U1Yr16vMhyWk2OGxYLzkDleKObWBiUBnKwhdm/4jJKbNwWZI4Ofdcrpv4qViHJYQQIo6MyUzilx+bz/isJDLddj59xmSuXFg4YOdfOTWHr144ndwUB4XpLn5wxRzmjk7nh1fO4czpubjtFpZPzOKXH5s/YNcUQojeUrrz2IdhaPHixbqoqCjWYQghhBhkSql1WuvFsY4jXsj9UQghRo7+3iPjqqqn97X3YV14fpehsNx0Oda87NgGJYQQQoi4sPVoPU+tP0Kay8YNJ40jO9nRtq/oYA3/3VRCfpqL65aNJc1l6/Y8h2taePCd/WwtqWdKbjJ3njaRyblmtU5vIMjf3j/IS1vKsFsN8lIdjM5I4tqlYxmTmRRxnkPVzdz/3DZKGzxcuaCQ20+dKMtVifhWvh02Pgq2JFj8cUgtOPFrxJCJmx6/VT/5LXy4pcs++723y4ekEEIkCOnx6x3p8eu5zUfq+MgDH+ALF1cZl5XEK/echsNq4Z3dldzy8FpC4UeiOYVpPPfpFVGfLyobvZz987eobw20tblsFl787KlMyHbz6cfW8/zm0i6vy3TbeeWe09qSzaomL6f86A08gfZiLzcvH8e3L5s9kG9biKFTsRMePB0CreZ2yij49FpwyBImA6W/98i4meNH0daozYF35YYnhBBCiON74sPDbUkfQHF1C+/urgLgsTWH2pI+gC1H69l0pD7qeV7cUhqR9AG0+oM8vf4Itc0+XoiS9AHUNPt4aUv7vhc3l0YkfQBPDOASE0IMuY2Ptid9AI0lsOvl2MUjuoifxK+7KlipUtxFCCGEEMeX7Ow6u+VYm9sRZZ/DEvU80Y49di671cBm7f7RqmMMKa6u53Haol9TiLjgSI3SJr19w0ncJH7qgpVR223zZw5xJEIIIYSINzcvH09eavucvtOm5rAsvNzCXSsnRszpu2JBYducvc4umlPAjILIfWMzk7h60RjcDiufOn1y1NfNLkzlgtnt850umF3AqHRnxDFfPm96796UEMPJopshfWz79tiTYfLZsYtHdBE3c/yKiooIVNYQ/Ofz4PHB6Dzs114s8/uEECKByBy/3pE5fr3T5A3w5s4K0pNsrJiUjdFhbb+6Fh9v764kP9XJsold1+XryB8M8fqOCrYerWdqfjLnzsyP6K3berSel7aWke6ykuF2kO6ysXJaTpc1/PzBEI+vPcTeymauWzqGaflRekyEiCe+FtjzCtjdMOlMMKQXeyD19x4ZV4mfDoXwl1WiN+7EmDEJ24TRsQ5NCCHEAJLEr3ck8es5fzDE/spmxmUldRlS6fEHKa5uYUK2G/txhmr2VEWDh4PVzYzJTKIgzdXv8wkR13zNUFsMNhdY7JA2cGtojjQjZjmHUGUN/n88C35zQnVoy268LieOz9wY48iEEEIIMZxtPFzHnX8voqLRS5rLxq+vXcDKqTkAvL+3ik89tp7aFj/ZyQ7+eONCFo3L7PO1vvb0Fh5dc6ht+/L5hfz8o/MieheFGDF2vgBP3w3ehva2uR+Dyx+Q3sAYiJs5foE3VrclfW1aPfj3SwUsIYQQQnTv/ue2UdHoBaC+1c/Xnm5fHuprz2yltsUPmEssfOOZbX2+zur91RFJH8AzG4/y5q6KPp9TiLgVCsLz90QmfQCbn4BdL8UmphEubhI/XdsQvX3PwaENRAghhBBx5WB1c8T20bpWfIEQWmuKO+3rfGxvdD7XMQeq+n5OIeKWtxGayqPvq9k3tLEIII4SP8vU8dHbVy4d2kCEEEIIEVfOm5kfsX3GtFzsVgOlFOfMzIs8dlbksb1x2tScLnMELQacNSOvm1cIkcBc6TD+1K7thhWmnj/k4Yg4muNnWbmEIBo+bF/I3Th5IRan4zivEkIIIcRId/+ls0hPsrF6fzVzRqfxxXOnte376dXzKEjbzYZDtSwZn8k950zt83UK0lw8evsyvvPf7RRXN1OYkcTXL5rBhGxZc1iMUFf/FV7/Dhx8D4J+yJwAKz4LOdNO+FIx8OKqqqcQQojEJlU9e0fuj0IIMXKMnKqeHi/+Pz5uruF3zMQxOK6WrmIhAJ4/epRXy8rIdTi4ZeJECpOSYh2SEEIMK+uKa3jwnf1UNHgBjT+kMZRiQrabKxYU8tymEsobPJw5LZcD1c2s2V9DMKSZWZDKJ8+YzMxR0dfZ+9ZzW3l87WG0hrNn5DK7MJVHVh/CH9KcMyMPiwG7y5tYOS2HO0+diNUSNzNthBAJJG56/Fbd8Gnw+rvsU2csxb50XgyiEmL4eLGkhB9sa69El+908viKFVgNebgQ8UV6/HpHevx67nBNC2f//G28gVDU/YaC0HEeiVKdVt798pmkuWwR7b97cw8//d/uHsfxqTMm8aXzpvf4eCGEOKa/98i4eCq0GUbUpA9Ar940xNEIMfy8WR5ZNavM42F7Q/RKuEIIMRK9vqO826QPjp/0ATR4Ary3p6pL+7/XHelVHC9sLu3V8UIIMVDiIvHzh7r/oCY1ZegCEWKYync6I7YNIK9TmxBCjGSjM/o//H10hqtL26j0rm3HMyZThuELIWIjLhI/ALViYdR267UXDXEkQgw/N02YwHi3WTXOohS3TZokiZ8QQnRw5vRcLpk3Kuo+Q8HicRlYDAVAboqDjqsyKOCm5eOYNya9y2t/ctVcHB0ONhSkdxgOarOotiUeclIc3HeBDPMUQsRG3MzxKyoqItTqwf/i21DXgJo8Drus4SdEm5DW7GlsJMvhINshy5yI+CRz/HpH5vj13sGqZgLhcZ2GAo8/RIbbRkGai4oGDxWNXmaNSqWuxc/h2haUgky3g8IT9Oz9Z/0RvIEQVywoxGooiopr8QZCLJuQidcf4mB1MzMKUrus8yeEED01Yqp6AgR27If9hyGk0TYbIa8Pw2Hvclyoqorgli0Yo0djmTKly34dCBAq3o2yO1CjJ6KUGorwRT+0BJrYWltEliOPSakzYh3OsGQoxbTU6BXnBGitKa0M4fXBmAIDq0X+3QsxElU1efnrqoP4gkFmF6ZRkOYizWUj3WUnN9VJbqo5WiLDbSfDbT5j1DT7eHFLKckOCw2eAPNHp3OwuoVAKMTyiVkUFdeS4baTl+Lg6fVHMJTB0omZTMh28/LWEv6zvoTCdBcvbCnlknkFzClMj+FvQIiwgA8+/DN4G+GkT4BzAJ4hjhRBYxlMPB0cyf0/nxhQcdPjt+oT90FVbZd9ttuvxshKb9sOfFhE8M0327bV6NHYr7u2bVu3NOF/7Hfoumpz//ip2K76OErJN3DD1dHmA9y/8W4a/XUAnDPqKm6bem9sgxJxRWvNC2/7KC4x5wunuhVXnesgySXJ33AjPX69Iz1+vXPfU5t5/MPDUfcVpDn59ydO7tKzt/ZADbc8vJYWXzDq61w2C63+6PtGZ7g4Utvapf3ulRO57wL5ElPEUGst/GoeeOrNbcMKd70LeTP7fs6nPwGbHjN/dufCx1+GrEn9j1W0GRFVPYGoSR9A4NVVEdvBVZHb+sgRQlXtVbiCm1a3JX0A+uBudPHeAQxUDLRnD/29LekDeLXkKcpae1dFTYxsR8tDbUkfQEOzZsueQAwjEkIMtYoGT7dJH0BpvYeH3zvQpf2Xr+3uNukDuk36gKhJH8Cf3z1Ai08+g0QMvfvL9qQPIBSAl+/r+/nKt7cnfQDNFfDBb/t+PjEo4ifx606rJ3I7EOWD1NPhGE9Ll906SpsYPpoCXZclaPY3xiASEa88vq5tXt/wH+0ghBg4DZ4TJ1p1rV2Xjqprib6cVH8EQhqP/zgVy4UYbM3lXdtao3ey9Ei01/bnfGJQxE/iZ4keqmX5gohtNalTl7LTiSosbNs0Zi4Cw9K+352CMVEqbA1nZ+RfGrE9PnkqE1Pk/zPRc+NGGbg7jN4yDJg+Ia6mOAsh+mlybjJTcrufc2QouHrR6C7tH1syps/XtBrRh5MvHpdBprtrjQIhhszJ/w+zXm3ntj4aexJkT+vQoGDBDX0/nxgUcTPHb+3q1fh/8w/oMDRCnbsC+4LIschaa4Jvvklw7z5URgbWC87HSI78oA+VHSa4ZS3K7sSy4GRUasaQvA/Rd5tqVvNBxWtkO/M5v/Bqkm1psQ5JxJnG5hBbdgfx+TUzJlrJy46f771GEpnj1zsyx693Gjx+vvHMFl7bXkEgpMlMspGf5mJCtptrl41lyfjMqK97YXMpr+0op9kbwGW3MCU3meomH0GtOX1aDu/tqabVH8Bls7D5SD2GoThvVj7nzcrjnic2sr2kAUMpUl1WTp+WyzcunonTZol6LSGGzIF34JVvQsADKz4L86898WuOp7kK1vwRGkth7kdhwmkDE6do09975KAmfkqpe4DbAQ1sAW4FCoDHgSxgHXCj1jrKQKx2cmMTQoiRYaQkfnJ/FEII0VvDdjkHpVQh8Blgpta6VSn1JHANcCHwC63140qpPwC3AQ+c6HzB5hYCv320S7v1ix/HYpFvzQbakZI32bbzTwQCLUyacCXTp9wU65CEECIhDPT9UfTNkx8e5tdv7KGqyYuhFGkuGx5/kAVjM0iyGbyyvZygNodregOR8/HyUx08fudyxme7I9oPVjXzlf9sZl1xHQCpTitBrZldmMZ3LpuNy2Zw9R8+4HC46IuhINlhxWIozpiey7cvnUWK04YQca+1Fl74Iux/y6wU6kyDQ6shZzpc+FPIlaq2sTBoPX7hG9tqYB7QADwD/AZ4FMjXWgeUUsuB+7XW5x3vXIsXL9arrvkkBKNUznIn4fj09QMc/cjW1HyUl1+/Gq3bf9/Ll/yA0aPOimFUQoiRYCT0+A30/VF6/Hpv4+E6Lv/dqhMfeByj0p28f1/kffHCX73L9tKuBckAZhak4g+G2FPR1O05r106hh9eObdfcQkxLDx1B2x5Mvq+zEnw/9aBrKPda8N2OQet9VHgZ8AhoBSoxxy6Uqe1PjZR7whQGP0MnURL+gCapSLnQKuq3hCR9AFUVK6LUTRCCJFYBvz+KHrt/X1VJz7oBErqIquK17f4u036ALaXNrC/svukz4yr+rj7hYgbB97pfl/NPqiXZbliYdASP6VUBnAZMAEYBbiB83vx+juVUkVKqaLKysruvxWwS2W+gZaR3rViZnr6tChHCiGE6K0Bvz+KXptT2P8CYRlJkUMyU11WxmYmdXv8mEwXeanO455z9igpXCYSxKj53e9LzoeUgiELRbQbzLJ2ZwMHtNaVWms/8B9gBZCulDqWrY0GjkZ7sdb6Qa31Yq314pycHIzrL4l6EcttHxmE0Ee2tNTJzJv9OWzWZJSyMmHcZYwfc1GswxJCiEQxoPdH0XunTsnh02dMxm4x2grau8JVNqfkJjN7VErbsdG+dnZaFQ/csCiiTSnFL6+Zz5iM9rVj7Bbz1ROy3fzyYwv4002LcTsi6xKED2Hp+Ey+cXFkpXIh4tYFP4HC8IjE9HGQP7f956v+BBbpuImFwZzjtwz4C7AEaAX+ChQBpwFPdZi8vllr/fvjnavjHAZvcQkUH4Jpk3DkyQ1vMIVCAbQOYrE4Yh2KEGKEGCFz/Abl/ih6zxcIEdIhgiFwO6w0ewO4HeYDaYs3QCCkSXXZqGr0oBRobZZhzUnpvudOa02Lz5wukWS30OILkmS3oDqMXKps9OCwGBiGwu2w0uoPkiQjmEQi8jaB3W2O3PM1gy1J5vb1w7Ct6qm1XqOU+jewHggAG4AHgReAx5VS3wu3PdTTc3pfex/WbTM3PtiCd+ViHCctOP6LRJ8ZhpVB/BPplUpPKR9UvEaSNZlTcs/Dae1+OI0YmY7WhNhdFiQ31WBGoYEhNxYxTA3G/VH03vv7qli1t4oWX5DcFCcXz81nR2kjO0obOXVqNh5/kLUHashOdvD2rgqsFoP7LpjOuKz2Sp6r9lby53cPkOW286XzprO/qpl391TS5A1QmO7i0vmjyEiy8/NXdrPhcB3nzcrj+mXj2hLHo3WtPLLmEKlOG5fNH9WWdAoxYBrL4Y3vmv9degdMPbd3rw/6YdvTUFcMubOhYhukFsLsK8HqiDzutfuhbDPMu659TUCrA7b8G+oOwsQzoGyLuc4fyqz0OedqSJaOnKESNwu4r/rit6G4pOvOi07DMVvmnyWyo80H+fr6W2kNmoV8xidP5fsLH8ZiyA1SmLYcDvCv1X6OfZotnmDhssX2mMYk+mYk9PgNJOnx65uH3jvAd5/fHtFmNRSB0PGfiSyG4p17T6cwPYl/Fx3hi//edNzXpzgspLrsHK1rbWu7YHY+D9ywiL0VTVz+u1U0ec16PjMKUnnu0yuwWQZzFo4YURpK4NcLIdD+98cFP4Zld/f8HP+8Fna92LV94hlw0zPt279ZBNV727eXfxrO+z788zrY9UL350/Og7vfg+Tcnsc0gg3bqp4DLlrSB/DicaoGiYTwWsl/2pI+gINNu9lcuyaGEYnhZtWuAB0ft9YfDNLiHf5fagkhYuPBd/Z1aTtR0gcQDGl+/spuAH75+u4Tvr7RG4xI+gBe3lpGfYufx9Ycakv6AHaUNvDenv5XGxWizfq/RyZ9AO/8rOevr9obPekD2P8mlG42f67cE5n0ARQ9DNX7jp/0ATSVw+Yneh6T6Jf4SfzEiKVU1z9TJX+6ooOoozplpKcQohv9GQp+7LVGfz5jVPTXywh1MaCiPD9Fbev29Sf4gzx2LiPadVTP/6B7E5Pol/j5TU8cHb39kjOHNg4x5M4edSVua3uFtYkpM5iTsSSGEYnh5pRptog8b/FEC0l2eYISQkT3idMndWmzWdo/M7r79LAaii+cOxWAz58TOc2k4+uPSXdZGZcVOSf9krkFpLlsXH/SOFKd7VMW5hSmccrk7J6+BSFObOFNYHNHtq28r+evz5oEMy6Nvm/KuZA/u/247E7TrpbcAZkTYeZlHRqj/MtKLYS5H+t5TKJf4maOX1FREd53PoQPNrbvOHcFjgVS+ngkqPFWsrryddzWFJbnnIXdcvy1kMTIU1ZnFnfJSzWYWmBEVNAT8UPm+PWOzPHru3XFNazaW02rL0h2ioOL5hSwo6yBnaWNnDolG28gyJoDNeSlOnlzZwU2i+JL501nVHr7cg1FB2v407sHyE6284VzpnKguoV391TS4gtSkObkonCS9+d3DrDuUC0XzM7jI4vGtH0+lTd4eGFzKakuGxfPLcBps3QXrhB901wNb/0QGstg2Z0w4bTevT4YMIdr1hZD/hwo3wqpo8yE0NJhLctgEN7+IZRsgAU3wqzLO73+oDkvsHyrGYsyzGqfs6+CpMyBercJr7/3yLhK/LTW+DbuNJdzWLIAR6FMBI01f6AVpRRWScREHzX4QiTblFThHAa01uAJolyxK5wkiV/vSOLXe/UtftwOC82+AB5/kLxUM5HTWrOnvAlDQW6qk1RX5ALtrb4g3kAQrTWGMkjrtIB7KKSpb/WT4Y4sLBUMaRo9ftKT7NQ2+7AqRaMvQF6qk0aPn2SHlWZvsMv5hBhQoRB46swkK+A1/+dMjX6s3wOhADiSu+4L+s1lGdDgSAVDvqwYSsN2OYeB5lu9Af12h5vbrkN4Advnb8Wwxc3bSBhah/hg68/YfehZlLIwe9J1LJrWiypRYsQrbQly//pGdtUHyXUafGVeMguy5cEnVkLFTfieLoZ6P6rAhe3q8RgZsoanSBzVTV4+9dh6Vu+vwWZR+IPmF99js5L4ziUzue3v6wh2KNBy+rQc/nrrUgB+9NJO/vTu/oj9i8dl8MANi8hJcbCuuJbPPbGBwzWtzChI5ffXL2RCtpt3dldy7783U9bgwWkz8PhDba9XmGsCHqsGunRCJr+/fiHZyfLvTgyw4g/g6Tuh7pDZW9dabxZ9mXk5XPGHyGUZ3vkpvPtzCPpg3jVw8a/aF1vf8m948YvQWmtuu3Pg0t/AtAuG/C2JvombOX4RSV8H/sdPUC1IDIoDpa+zs/gpQjpAMORl056HKa1eH+uwRBz53fZmdtWbixxXeEJ8f1MTwTgYgZCItNZtSR+ALm0l8PLRGEclxMD6v1d3s3p/DUBb0gdwqLqF2zslfQBv7ark+c0lvLunkj+8va/L/qLiWn76v51orfnivzZxuMasnrijtIFvPLMVfzDE55/cRFmDByAi6QPaKhEfqwa69kANP31514C9XyEAs6fv6bvMpA/MJR78zaBDsO0/8OGf2489uh7e+B74W8wevw2PwKZ/mvtaa+HZT7cnfQDNlea5/Z0qh4phKy4SP+N45fkqqocuENGmpn5317aGPTGIRMSrvQ3BiO0qT4h6nyR+MeEJtiV9x4TK5EYuEsv2koZu93W3lMN7e6rYUdr963aUNtLqD3KgqrlTewOVjV6qmry9inFHWffXEqJPvA3m4uvdKdsS/edjyrea/63a23VpCABPPdQd7l+MYsjEReIX4jgPg9MmDl0gos2onGUR2wqDUdlSaVP03OJOwzonpVjIdMTFR1LCUS4rqsAV0WaZmNLN0ULEp1OndF8x022PPk/po4vHcPKk7l93ypRskuxWFo5N79JekOZkUo47+gu7O59U9RQDzZUOoxZ2v39Sh+r4E04Fo9P0qYlnmP/NnwNJUf4+08eaVT1FXIibpyzLDZd0bbRZcVx8+pDHImBU9mJOnnMfacnjyUydwsqF3yUjRZJw0XOfnOnmojEOcp0GJ+Xa+PYiSTRiyXb1eIypqZBqwzI/E+v5hbEOSYgB9ekzJ/PxFRMoTHcxOt2Fw2pgtSjOmZnHq/esJDelfZ6TRcFnzprCwnEZzC5M41fXzGdMhgu7RWE1FClOKzcvH8dnz5oCwG+uW8g5M/MoSHNy5cJCvnPpbJRSPHjTYlZOzSE/1cHEbDcpDisWw1zDL9VpI8ttIz/VQUGak1tOHs9nz54Sq1+PSGRX/xWmXmAunTDxDCiYDxkT4KxvwdyPth+XORE++nfInwtZk+GCn8C08819Nidc/ySMPRnsyWBPMSuEXvu4FHiJI3FV1VMIIURik6qevSP3RyGEGDlGTFXPUCCA/+cPEzHqMysNx+0f7fY1Qgyml8p28UH1ISa5M/nomLm4LLGtSFnS2sq/Dh2iORDg4sJC5qanxzQeIYQYbmqbfTz03gGO1LYwOsPF6v3V7K9sJqghzWUl2+0gqDVjMpO48aRxeHxBvvL0Fupb/YzLSqKqyUurP8Qpk7KYnJfCuuJafIEQc0enceuKCfzopR28sq0cpWByrptkhx23w8KKydnctHw8dqtBqy/Iw+8fYOvRBvzBIAcqW0h2WvnMWZM5c3perH9FYiSr2Q+r/2AWf1l4M+TNgtUPQMV2mHwOzL+2/didL8C2Z8yhnss/FX0tvu6O8bXAmgegfBtMPhvmXzcU704QRz1+qz56N0SLdeJoHFdLGVkxtB4p3sDv969u2z4laxw/mXthzOJpCQS4dtUqqn0+ACxK8fslS5iVlhazmIToC+nx6x3p8es5rTWX/PY9th7tWQEVQ0E3NV+islsMfMFQt/uvXjSan149jzv/XsQr28ujHvPQzYs5a4YkfyIGWuvgN4ugpcrcNmwwejEc+qD9mHO+Ays+C5v/Bf+5vb29YB7c9U7k+Y53zD+vhV0vtu87+3445Z6BfDcJq7/3yLiZ4xc16QPYf2Ro4xACeKFsZ8T2e9XF1PliVwVxdXV1W9IHENSa/5WWxiweIYQYbnaUNvY46YPeJX3AcZM+gGc2HqW6ycurO6InfQD/XifPNCJG9rzSnvQBhPyRSR/AhkfN/258NLK9dFPXiqDdHdNSE5n0dTyvGHTxk/h1Rx1nqQchBkm6LbICYpLFhtMSu5HT6bauw0wzorQJIcRIleG2YcTwkSHNZSfJbsFt7/5ekem2D2FEQnSQlNW1zej0HOHOCf+3U3VPZYCr01DP7o6xucziMNHOKwZd/CR+BblRmy0XrRziQISAuyYuJSk8p08Bd0xYijOGc/wWZGRwak77B+eYpCQuHzMmZvEIIcRwU5Dm4o5Te159enSGi6RulnmIZk5harf7LIbiqxdOx2W38sVzp0b9zjrdZeWu06QsvoiRiWfAlPPat7Onwcr74Nha2vZkOPNr5s+nfiFyaYfln4a0TpWguzvG5oIzv9F+Xpsbzvz6QL8b0Y24meNXVFSEd+d+ePb1tnbLJ6/FmpJ8nFcKMXga/F421Zcw0Z1Foav7G/5Q2lZfT3MgwMKMDKxG/HyvI8QxMsevd2SOX+/tLm/kcE0L88eks/pANfsqmmjxBZiQ7SbdZccX0KQm2Vg+0ewBeWRNMdtL6rlx+Tje3VVFWYOH608aR7LDytaj9YS0pjAjiflj0impa+Wbz24lxWnl4rkFhLQ5ZHROYRqj0ttHihyqbmFXeSNjMly8t7eKnGQH583Ox2mTsvgixg6vBV8TjD8NLFaz4EvFThi3HFwZ7cd5m+Dge5AxDnJnRD/X8Y6pOQAVO2DsSdELw4ioRkxVTwBSIxdCDdm6hq+1RpeVg8OBkZnRZb/ouVAoQG3dDlyuXJJcMtm8s1Sbg1OzJ8Q6jAhSzEUIIaLzBUI8t6mE0rpmQlqxraSeU6fkoDU4bRbOmp5LVZOP4upmJma7eXRNMU6bgVVBisNGRYOXkyZlMSYjiUO1LYzPcpORZOdQTQtTct38q+gwDqvB8olZZCXb2VPRjN2izOqh+6pJTbLiC2hafQGy3A7cdoMniw5jNRQ5yXaCvZ1UKERflG2B6n2QOxNypnbdP2Zp+89Ve8DXDNOjFK9zJLev8dedY8fUHoQj62DUAjAMc7ulGqaeb26LIRM3PX6rPv1VKK/uunPJHBxnngSA9njwP/kvdFkZAMac2dgukIqffdHUfJS33/8ULS2lKGVh1vQ7mTH1lliHJYRIcNLj1zvS49cz247Wc/nvV+EPdv/Mk+K00uoLEDh+jZY2va36eSI2Q/G325Zy8qTsEx8sRG/5W+GRK6H4/fa2WVfBRx7qWi9Da3j6Ltj8hLk9egnc+DQ4Unp/3f99DT74HaAhZzqMWwFFfzG3s6fBzf+FFOlc6KmRU9UzWtIH8GF7FaHgxo1tSR9AaMtWQkekQlZf7Nj1EC0tZlVIrYNs2/kgHk83/x8IIYQQw9h9/9l83KQPoNHT86QPBjbpA/CHNN98ZtvAnlSIYzY/EZn0AWx7Cva/2fXYg++2J30ARz6EdX/t/TUrdsIHv6VtEe7KnVD0UPt21S54/9e9P6/os/hJ/HpANzR2bWvs2iZOrKU1sty01kFaPZUxikYIIYTou4pGb6xD6JGyBk+sQxCJqv5oz9vro3SadPf642noQedLQx/OK/os/hO/DrWZLdOnR+5zOjEmDK85WPFizOhzI7ZTkseTnhZlLLgQQggxzF02v/DEBw0Dl80fFesQRKKaeRmoTsWDbG6Yel7XY6ecC44OReuUAbOu6P01x62A5PzINlen+huzr+r9eUWfxU1xF8tnbiT46390aXd86fa2n42xY7BedSWhTZvBYceydCnK6RzKMBPGxHGXoTA4UvI67qRRTJ96M0rF//cEQgghRp6vXDCdYEjzxIeHaPEFCWmzpkSqw4qhDFx2C3ecOoHDta3sKmugriXAvsom/MEgWkMIcFoNJmS729baK8xwsWZ/DQ2tfgrSXZTWt9LsDRIKhdCYg9kMFHargVJgKIXWmpAGp83AGwjR7A2iAbfdwjVLxvDlC7qpjihEf+XPhpuehTe+B3WHzCqbZ38LkqMsl+bOhltfhFW/Bn8LLLoVxi7r/TVtLvM87/0cmiph/rWQPxfe+wU0VcC8a2DGJf1/b6LH4qa4i0xeF0KIxCfFXXpH7o9CCDFyjJjlHLxVNfDQU13a7ffejoq2EuowEfI101D0B7ylG7DnziJ1ySexOAen5H591RaKt/+ZgK+RggmXUjDp8kG5jhCJSmvNru0BivcHSUpSzFlgIz1TerqFSDSHapq59o+rOVofOadOAW6HlQnZSVjCZeYvnJPP+3ureGdPldlTCG09etbwx0NIm4u0K6WYlpeMoWBbSSNKgctmweMPEgp/0d6xgIwCMpJsTMlL4ROnT+L0aVF6X4Toj9JN8OYPoHKXuZ06ylxMfep58O7PYcdzkDkBTv4cbPi7Wchl7Elw1rdg9/9g7YPm6yw28DbAtAvhtHvNNf76qqUGXvsWHF1vDgc965vm0g9i0MVNj9+qq++KvtNi4PjibUMbUC/UvHk/LXtfbtt2jllB9vn/N+DX8XvrWfPC5QQDLW1ts07+MdmjTx/wawmRqPbuClD0gb9t2+mESz7ixGIdvl8uJRrp8esd6fHrmyXfe5XKJl+sw4hgsyj+97nTmJgjD8BigPia4RezobUmsl1ZYOkdsOYP7W02l7nkwzHjT4OD70Q/7+lfgdPv63tcj3wE9r7avj3vWrjiD90fL9qMnOUcuhPsRe3lGGgtfjdi23P4fXQoMODXqasoikj6AKpKuvkHK4SIquRwMGLb44HqquH9GSOE6J0mb2DYJX0A/qDmrV1SPVsMoMNruiZ9ADoIO5+PbOuY9AEc6rT0Q0e7Xux7TEE/7H1t4M4neiX+E79hzpo+LnI7dTTKGPgRtq6UcV3akqK0CSG6l5IW+ZGoFCSnyMekEIkkyWZhuHbiT8qV3j4xgDInmRU5o+6b2Kmh0z+KlE7VODvK7keVd4sNMsYP3PlEr8TPE82YbkocfyRKGdphJGPFl7C4zTH7hiuT9FP70TV+HMnpkxk38/a2pDIjbxmFk68elGsJkahmzrGSlWN+LFosMH+JjST3MH1CFEL0iWEovnnJrOMeY1bhNH+eNSoVWy+elgzV+4crQ8H1y8Zy2pTsXr5SiOPIGAdnfxusHSvcK5h/PVz+AOTPMZvsybDis5CcZ26njIIr/9yh4qYCi1nNltyZcOY3+hfXpb8Gd475c+pouPCn/Tuf6LG4meNXVFRE0B8g8Nt/gC8A2ak4bvtYrEPrER0KEGgswZpcgLLYBvVafm89wUArTvdxvqkRQhxXU2MIh0Nhs0vSN9Rkjl/vyBy/vmvxBXh9RwX1LV7mjUmnyRvEYihyUxxkuB2EQppWf5BR6S5afUH2VzWyo6SRFZOzOVrXSnFNC6dMyaKqwUddq4+puSnsqWhiyYRMLErxwf5qMpLs5KbYOVLnwWZAqsvG1qP1ZLrtlNS1MjrDzbisJAxDkZ3siPWvRCQqTz201rUngCl57ftq9oM71yyuEvSbSz2kj2sv3tJQAhYH2JzQVB6lp7CPAj6oP2z2/hmWEx4uTCOmqidA4M//MpM+gKoGvP99C8clp3c5TgcChPbuBcCYNAlls3Xa7ye0bwfoEMakmSibfVDjVoYVW9rYQb3GMTZHGjbH4FQNHUn8oSDvVe/FHwpyavZkXJbB/RsRw4sM7xQi8WiteXZTCe/truS82fmkumy8u6eSuhY/W0saOWtGLnUtflp8QcZmuqlv9fP+vmqyku1MyXXzrw+PUtPiY9XeKhaMS+fqRWN5fO0hnlp/mEAIHFaDmiYvKMXYzCRcNsXB6lZGZySxeHwGvkCImhYfVouisTXA/somPIEg2W4ni8dncOdpk3DZ5QFYDAJnGhx8H9Y9DCkFsOwuyJsJvhYo2WAOB516gZncZU0yX1OxEw59YPYa7nrJLP5y6hfMfZW7zTmAoxaYvYUH3zV7DwsXQXM17H7ZTC4zJ8OBtyFnmlkpFCAUhD2vQmstTLtAkr4hFjc9ft1W9cxKx3F7+5BG7fXhf+QRdHU1ACozE9uNN6Ac5jdp2ufF/+hv0dXl5v6MbGw3/D+UwzW4b0LEDW8wwF0bHmF3k/k3MsqZxp8X3kS6PSnGkQmR+KTHr3ekx6/nrvvTat7fV92jY0+elMWO0gZqW/zdHmM1Ipdm6K80l413v3wGqc7BHRkkRqDnPgPr/xbZdt4P4MOHoGafuZ07C25/Fexu2PgYPPNJzEVLOrA64Zzvwcv3gg7/8Suj/eeld8Pmf5o9jJ33rfgsnHU//OMyOBAuPujOgdtfN5NL0SNS1bO6LmIztHNHW9IHoGtqCO3Y0b5/1+a2pA9A11YR2r5h0MMU8ePtqt1tSR9AiaeeF8u2xDAiIYQQ/bGvsqnHSR/A+/uqj5v0wcAmfQD1rX4eX3NoYE8qBMCGR7q2vfXD9qQPoGIbbH/W/PnNH9Il6QMIeOCN77QncxD5c9Gf2pO+zvs++L3Zc3igQ8X55kr48E+9eiuif+I/8etE+7sulaD9HT68/V1LOOsobWLk8oa63uxbo7QJIYSID62+4IkPGgYavQO/3JMQEQnYMQFv1zZfs/lff0vXfccEj/M8FDrOtyGhAHgbo1zzONcSAy7+Ez9b5DRFy/Rp4OowbNPlwjJjRtumMW0euNzt+51JWGYsGOwoRRxZmT2NbHt7SW23xc4FebNjGJEQQoj+mF2Yxvisng/Xn5CdhM0ytMWdbBbF9ctkyJsYBONP7dq28GZwprdvu3Ng1hXmz0vvjH4eZcDij3d/nSnnQHdLls28DGZfAVmT29ssDlh083FDFwMrbub4FRUV4f1xp+5gqwXHF7r+AeqGBoKbN4MGy9w5qLS0TvvrCG5ZC1pjmbMElZY5mOGLOFTpbeT50s34QkEuKpjDaFdGrEMSYkSQOX69I3P8eq7ZG+BHL+1k/aFaTp6URUaSjf9uKqW+1UeG286yCVkopchPdfKxpWM4XNPCcxtLyEq2U5ju5C+rDlLV6MVutTBrVCp3nz6Jn7+6m/f3VuEPhLAYCl8whEKR4rSiFDR7gyQ7rUzNS8ZQivpWPyGtafWFqGzyEgyGcNmtzClM45uXzGRijqzjJwbJy1+DHc+CIxVOvQdmfwTqis1hoIYVFtwIaYXtx29/ForfN+f1HVoNVoe5NEThAtjxXzj4HoxaaJ7vwNuQPxvmXgPlW2DrU5CcD5nj4eAqc52++deD1Q4tNeZ8w9Za8/i8mTH7lcSj/t4j4yrxE0IIkdgk8esduT8KIcTIMWKWc/C+8DZs3d11x51X48hIH/J4AFrf+CH+Hf81l4XInYH7qj+hLLH7lVaXvMe+jb/A21pJ3rjzmbzgixh9WIYgGPTx3urPU1H1IaDIz1vOiqU/xeiu+36QHW7ezx93fo8DTbuYnb6Yu6d/gwxH3xa53d5wmB/teYqDzeUsz5zOV6ddTZpNqnUKARB4u4zA6kqwKKwr87EukcWkReJ4e3cFH3/4Q4I9/L57Wn4Kp07O5qH3DkQrc3FCqU4LzZ4gGIpgSKPoWi7DUDAmM4nvXT6bU6fk9OEqQvRTwAsvfAE2P27OBTTssOTj5ty7zU9Acq5ZAXT6Re2v2fki/O8r0FgKVpd57KzL4LQvw6MfgbqDYNhg5b3mIvDPfhpKN8HoReax5dvBnQ2tNZAxAS76GUw4LWa/gpEkbnr8ul3OAXB8+Y4hjMbkP7SG1uc+G9FmnX4xSWd/fchjAfD7Glj930sIBT1tbRPmfIKxM27p9bm2bPs9O/dGlv2dNf1uZk67tb9h9sm9H17Poea9bdtLsk/nC7N/3OvzhHSIq9b8mDJvbVvbxflL+Nq0q4/zKiFGhuCuevyPH4hos98xFWPU0H4xIj1+vSM9fj3jC4SY+c2XCYSG5zNPisPK6q+ehdsRN9/Hi0Tx9k/hze8d/xirE+7ZDu4sc52+X8w0K3x25s6F5orItsxJkdVDo3FlwOd3mGsFiuOS5RxiJLD/rS5twdJNQx9IWFPt7oikD6C+anOfzlVeuSZK2+o+nau/WgPNEUkfwO76vv2eK7z1EUkfwOb6g30NTYiEEjrc3KM2IeLRoZrmYZv0gVnNc1d5lIqHQgy2wz14vgt4oDS89FnpxuhJH5jLM3R2oqQPzPl+lbtOfJzoN0n8+sg6cWWXNkvB3BhEYkpOn4JhcUS0pWb1LZ7cnCVd2vJylvXpXP3lsroZ454U0TY1rW/vK8eRRr4jPaJtTppUUBMCwBjt7to2pmubEPFobKYb6zB+4klxWJmWlxLrMMRINKYHz3cWBxTMN38umG/2AEbjjjI9IHPiic/vTIecaSc+TvTbMP4Y7GTmpOjtd1w1tHGE2caehG3mJWZpW8DImY7rjK/EJBYAmyONGcu/j9NdiGFxkD/hUsZMu65P55o1/Q5ysheFtxR5ucuZPuWmgQu2lz4z47tMSpmJgYW5Gcu4dcqX+nQeizL43swbmOIuwKIMTsuaxf+beNGJXyjECGCZnoZlZR44DHBbsV5QOOTDPIUYLHarwZ9vXkxvVmiYkpfMrSvG09dFHVIcFhRgMcwzRDuPAsZmJvG76xfKME8RGyd/BubfYFb2VBYzqVv2CXO5B6sT0sfBRx5qT+rcWXDVQ2a7xQ6ONFBWmH0V3PKi2Q7m+U7/CnzsEbP6p7LAmKWQNxswIDkPLDaz4udH/ybDPIdI3MzxkzkMQgiR+GSOX+/I/VEIIUaOEVPVE+i6jp9h4PjSbRFNoYoKgu+tQns8GHNmY5k9G6WGdhHWRBAKBdi552+UlL5LetoU5s76f9jtqbEOa0AcaqnkxfJ1uCx2LslfSqY9/tdNOtTczK937aIxEOC6ceNYmZcX65CEEGJYeXtXBT96aSd1LX5SXVZK6z00ewNowGpAYXoSnkCIygYPGshw25k1Ko38VCdv7Cqn1Rdk/pg0thxtoMkTwGm3YDUUNsPAFwzhtBk4rAbVzX5cNgupLiv1LX4yk+1kJNlJc9lIT7Kxu7yJo7WteANB0Bp/CNJcNr5+0QwunV94orchRN+01MCGf4TXz/sY5M7oesz+t2D3K5A7HeZda/bIBXyw6Z/mHLyp58LE081jq/fBG9+H+sOQMR6SsmDyWTD+FHjl63CkCCafDad+wawOWr0Xpp4PE6IsJi+GTNz0+HVb1dNmwfF5cxH3UEkJ/kcfgw7vyVi6BNvppw9BlInlvdVfpLT83bZtpyOLi859LmZLOgyU4pYKbl33a1pDPgDyHRk8tuQLuPqw7MVwUeP1cuW77xLo8Hf/tVmzuGDUqBhGJUTfSI9f70iPX8+8vr2c2/4+/H9P375sFjcvHx/rMESiCfjgDyugKrwsmsUBt78KBfPaj9nwKDz7yfbt2R8xh3j+61bY9p/29ssfgNFL4YGTIejtei13TmSRl6RsaKlq377qIZjzkYF5XyOQVPX0B9t+DG7cFJH0AYTWbxjqiOKe399Eafl7EW0ebzUVVcP/pnkiL5QVtSV9AGXeWt6r3h7DiPrv34cORSR9AI8cONDN0UIIMfL8+o09sQ6hRx58e3+sQxCJaP9b7UkfmAnbushlu1j7x8jtrU9BxU7Y9nSn4x6EjY9GT/qga2XPjknfsdeLmIn/xK8ja5TeKItl6OOIc0pZUarrn4alU9XQeOQwbD1qiyeuKH/jdiOx/mkLIUR/OG3x8SxgH86lR0X8skWpwtm5mIqtUzEvwwp2l/nfjqyu/hVi6a4iqBgS8f8Jk9k+78yyaFGX5M966ilDHVHcs1qdTBp/ZURbWuoUsjPnxyagAXRZwTJy7Glt27NSxnJy5vQYRtR/V40dS3KHv3sFfGrq1NgFJIQQw8xXL5zR5+qcQ+mrF8T3/UgMU+NOgfEd5tYlZcPSOyKPOfWL0PGL8OWfNCt0nnR3e5vFDqd9ARbeBK7MrtdRFsidGdmW02EuocVhzvkTMRM3c/yKiorw/uJh8AXad0yfhOOyMyOO1a2tBDdsQDc3Y8yZgyU/f4ijTRxl5as5dPR/ZGXOY+K4S1AqPr4xPZHmgId3qrfhMuysyJqBLc7nLQJ4AgH+cfAgNT4f148fz+gkKcMv4pPM8esdmePXcyV1rfzfK7uoaPAwPsvNlqP1lDR4CARDJDutLBydgScYZP3BGpRhMCU3mUXjMhiX5eapdUeoavZy3dIxPLOhhEM1rYzNdBHUmgynnZpWL5luB6lOG7vKGklPsjEpx82OsiZmFKRgtxrkJjtIc9nYVd7I3oomGjwB7BaoawkwKsPFty+dxeRcWctPDJJgAPa+ahZ3mXYBuDK6HlN7EPa9aRZ+GXtSe3vxB1C5EyadYRZyAfA0wLq/Qs1+yJ9rfus8YaW5bt+mx2H/mzDrCvNaB1eZQ00nnwXpYwf/vSaw/t4j4yvxq6mHPz1pNmYk47jz2tgGluB8/kYCgRaSXLGvEBnSISo8JWQ5crEZg1+IpaS1jky7G6clvoeBChFvJPHrHUn8emdPeSMhrZmQnczWkjpGpyeRnezgUE0zvqBmdLqLN3aWU9fsJ9lpYcWUHAD2VTbhtluxW83KnSV1rewqayQ3xcnY7CTmFKZTUtdKaX0rB6uaWTE5m0aPn61H68lLc7JgTAZl9R6qmr2s3V9DMBRiZmEayQ4rr2wrY+XUXFZOy43xb0ckvPqj0FgGDUdh+kVgdPhCv/4IOFLMoZwNRyB9PBiGmSi21JpVPbOnQPZkCHihrhiwQMY4sHT6Ar2pEjx15pDQtNHt7XVHoKkURi8ZgjebmEbMcg5dlnKobTLbLj8Lx7SJsQkqge3Y/Ve273qIUMhHbvYSTl76Y2w2d0xiOdS0l59tvZcKz1FSbRl8asb9zMs86cQv7IMyTwP3bvk3e5srcVvsfGnqeZybN/PELxRCCDFseQNBzv/luxyoau6yz2kz8PhD/Tq/1YBAP07xl1XF2C2Krd8+X+b5iYHna4YnboJ9r7W3KQXX/gvGLoMnboADb5tDPS028LeYwzwnng4bHgHdXkiRlHzwNoOv0dx258A1j5mLs4dC8PxnYf0/gHDH0oSVcM2jZnXQva+abY5UuPNtyJLn96EW/58uz7we6wgSTmNjMVt3PEAoXP2youpD9ux/PGbx/HXv/1HhOQpAg7+WB3f9gJDu3026O3/Y/zZ7wxWpmoM+frL7f7QEfCd4lRBCiOHsl6/tjpr0Af1O+qB/Sd8xvqDmy09t6v+JhOjswz9HJn1gVsF/6uOw+gEz6QMI+c2kD8wevfV/i0z6wOwxPJb0gVnF8/l7zJ93vwzr/05b0gfmuV+8tz3pA/A2wNPdLNMmBlVcJH62KBUmxeBpbCruUdtQKWmJvHa1txxvsHVQrnWopSZiuyXoo8Lb2M3RQggh4sG2ow2xDqFH1hXXxjoEkYg6LuXQkbex+329Ubnr+NcpjfKFRu3B/l9X9FpcZFT+QerdEdFlZy/Aao0c1lmQF7vqqAuzIq89M30hLuvgDDtdkT0pYnusK5NxSVEqVwkhhIgbH10yJtYh9MinTp904oOE6K2pF0Rvz5oCU8/v/nU9Leo3LXyOKedEf83Cm7q2TTmnZ+cWAypu5vhx8nx4f2OXZvu9tw95KInObkvhtOW/ZvuuP+P11jJ+7MWMHX1uzOK5afI9OCwuttUWMT55KtdN+vSgXevmsSejteadqj2MTcrk7okrUSoeioALIYTozsVzR7G9pIG/f1CM1ppUl43aFh+pThuzR6Wy8Ug9/mCIQEjT6msf2ma3KBxWg+Zwm6EUWmuCHUayWQzF/NFpHKxuobrZFz4O0HDsa+sstx2PP9h2nmhOm5LFx5aOG+i3LgTMuBgu/iW8/RNoLDXbMifAHa+BM80s4LLxUbO4iy0J6g+bc/OmnAtv/QhKN0DQD1Y7LL4Nmsph7xvmPMHpF8G53zPPmTfLnM/35veh7pBZOXT5p82lI5yp8Mo3wN8Mk86CS34ds1/HSDZoVT2VUtOAJzo0TQS+Cfw93D4eOAh8VGt93LENUrVMCCFGhpFS1XOg7pFyfxRCiJFj2Fb11FrvAuYDKHMBuKPA08B9wOta6x8ppe4Lb3/5ROfzHjwCT7zUpd3x5fYFKLXWhDZtIrR3LyojE8tJy1Duwa1E6S9+H/+2Z1E2N/aFN2CJUqHIU7KO5u3/BsNGytzrsGcP3gKtwYCHw7seoaF6C2nZ8xgz7QYMy+Avf9AfnkATbx34G6VNe5icuZQVYz+GkSBrBg6Voy0tPHLwINVeL+cVFHCWrF8pxLA20PdIcWK+QIj/e2UXf1m1H3+Hjrdw5xwKyEiyEQhpGj0BevK1uFJgMxQhbb520bgM3t5dRas/smfPblHMLkwj2WnFahiMzXTx5s5KjtS1EAyZ1z5jei5/vHERNktczMIR8eLoevjgd1CzDwI+CIYL1lnsZpEVXxPYkyFtDFgd5r4xS2HF58DeaU3g5mp47+dwdAM0HoXWOnNph1DA7N3LnQVJ6eZSEOVbIWsSnPJ5SAkvC7bur7DjebC7oWIntFabvX8X/9xsE4NuSNbxU0qdC3xLa71CKbULOF1rXaqUKgDe0lpPO97rFy9erFdd3X31n2PJX6CoiOAbb7ZfNz8f+003DsRbiCpwdAMtT3+StupFjlRSbvw3ypnadoyvahcVz3y8rSqSsrrI/+gTWNyDs17PzjXfprz4xbbtgomXMXXxVwflWgPl4Q2fY3f1B23bZ4y/lXMn3x3DiOKLLxTimlWrqPB42tq+P3cuK/Niv/6iEL01Unr8OurPPVJ6/Hrua09v4dE1h2IdxnFdtbCQ//vo/FiHIRJF/RH47ZL2Sp29MeejcFWnpdQeOg8Or+7defLnwt3vwpoH4aUvRT9m8llww396H+MI1N975FB9rXQN8M/wz3la6/AAY8qAEz6dOno4xyq0fUfEti4rQ9cOXoUs/97XiChZ620gcGhNxDGtB96IKIWrA620Fr83aDFVHH4lcvvQq90cOTy0+hsjkj6AjeX/i1E08WlzbW1E0gfwallZjKIRQvRBv+6Romee3VgS6xBO6LmNR2MdgkgkO1/sW9IHsO0/5rp8x9Qf6X3SB1C2GSp3w5Z/dX/M3jcgGOj9uUWvDXrip5SyA5cCXf4f12Z3Y9QuR6XUnUqpIqVU0ZGKip5dKzUlssFqBZertyH3mBGl104l50RsR+vZsyQP3n3c4co97vZwY7e4cNlSI9rSHfKc0xu5TmeXtrwobUKI4acv98iO98fKysohiDIx5KcN/8/F9CRbrEMQiSStsO+vTSkAo0Oa4EwHWx+GY1rs4M4+fizONDBkis9QGIoevwuA9Vrr8vB2eXj4CuH/Rs3qtNYPaq0Xa60X5+TkRDvENLV9Tp3llFPg2Jw+w8By2mmoQXwAts+5EiOnfb6ebfqFWEfNjzgmaepF2PPb21wTzsA5ZvmgxTR5wRcwLOZ7tliTmLTgnkG71kCwGFYunnIPFmXe7Fy2VM6f8qkYRxVfxrrdXDtuHMf6xccmJXHtOKkMJ0Sc6PU9ssf3RxHhW5fMxDJMijRbjOiB/PraRUMciUhoU8+H6Rf3/nW2JLjgx5FtjmQ459tg9KA8iCU8V1BZ4MxvQFImnP5VSBnV9VhlwIU/MyfMikE36HP8lFKPA//TWj8c3v4pUN1h4nqm1vre453j2BwG7xsfwIdb23d88hocKZG9fDoQQJeVodLSUSnJA/12utBaE6rYAXY3lozuH7Z9VTtRhh1bZtfiLwMt4GukqX4vyelTsNoG/3cwEJp8tVQ2H6QwdQZ2y/D/VnY4KmltpcbrZUZaGhb5ABVxaqTN8evvPVLm+PVOo8fP/7aW8q+iI7T4gnzx/Cm8v7eWsvpWCtKcXDi3gF1lTVQ3eflgfzUWpUhPslNS10J6kp1Tp2Tzzu5KWnxB8tIcZCc7mTs6nV1lDSwYk85Jk7J5flMJ7+ypYG95E4vGZVDvCXDB7ALy0pzkJDsob/Awf0w67+2t4khNM+/trSYv1cG958/A7YifVbZEHCnfDv5WCPnNQizHShrZk+HwWhizzCzykjEBag9A3kyzWEs0jWVQs99c+uHQGvM1B96BGReZCSMasqfB0XWQMQ5SOyR7AV97e0MJlG+DGZeYiaHokf7eIwc18VNKuYFDwEStdX24LQt4EhgLFGOWqq453nnaEr8/PQE1De07zlyOY8nsiGN1KIQ+fARsVoxRUb5ZiAF/zV6CzZU4ChaijlVMGiTNDQfwNJeSnrMQi1USqL4q9zSwt6mCWamjSO9c1SrMHwqyvq6EDJuLqSnZQxxhbFV4/Oxt8DAz3UW6XR5UxMAZSYnfQNwjJfHruaZWH598dD3bSxuxWxV2i8HMgjTKG1o5UttKdbOPTLeNz587HU8gSEmdh5kFyTz54RFK6j3MKUzFabfQ4glS3tBKgzdARpKdGfmpaA0pSVYq6j28sauS06flkOK0sfVIHcXVLaQ5bUwflUqqw0q918+c0Wlcu3QcFqV4cWspXn+Qi+aMIsM9vKtwizjmbYLi983qnS2VcORD0CEYdwr4msHbCDV7YdGtZk/duofNpG7UfKjcBWOXgSMVileB1QX5s+HgKkgtMF8b9Ju9gaEAjFsBzZWw83nY+xak5MKS28yEEmDPa+b1F3+8veKn6JFhnfgNlONW9Uxy4vh/ZuVO7fXi/+c/0RXmnAc1YQK2q65EGbErjVy76mfmUg6AxZ1DzsV/wJrajzHXx7F/0285vOsfANgcGcw74wHcqRMG5VqJ7PnSzfx418sE0TgMKz+efSVLMyN/j5XeJu5e/wylnkYALsyfxtdnnBmLcIfcy0fr+PHWowQ12A3FdxeMYXlOyolfKEQPjKTEbyBI4tcz64truPKBD0584BCyKLBZDDwBs4CG1VA8fOsSTp0iw3fFACvfDn+7GFqqe3DwsRFDnfIDm9tM0mr2m9sWe/vSEJ1ljIfaQ0Aosn3pXeYyD8Wr2q/1kb/A7Ct79DZE/FT1HDwt7dUMg5s3tyV9APrAAUL7D8QiKgD8dYfakj6AYHMljZseGZRreVvKObz70fZre2s5tP2vg3KtRBYIhfjdvrcIhj/wvKEAD+x/u8txjx/e3Jb0AbxYtotdjYlfZCGkNQ/sKiMYvh/4Qpo/7io//ouEECLG7vrHuliH0EVQ05b0AQRCmu+/sOM4rxCij975SQ+TPjATviidQv7m9qQPuk/6AGoP0iXpA1j7xw5JX/ha/xveS44lmvhP/DpqiVKyNlrbEAl5ui4lEfQcd1Rrn/m99WaXfUTb4FwrkQV1kKZA5NIItVFKIdf6WnvUlmiCWtPQaWHiOl+wm6OFEGJ4aImTz6nqJm+sQxCJqLkq1hF0z9sU6whGlIRK/IwZM8DSoRys04kxeVLM4rHnzsaaFlnwxT3lokG5ljt9CsnpUyPa8sb3oZLTCOew2Dgzd3pE24X5s7scd0H+NDqWT8l3prAwY3CG8A4nNsPg7IK0iLbzCtO6OVoIIYaH65aNjXUIPXLt0viIU8SZ+dcNzHlUD5dc6O64rMnhAjAdzJBn1aEUP3P8XnoF/vJUl32OL98RsR0qKSG4aRNYrVgWLsLIim2loGBLNY1bHiPYXEnS5PNwjV0xaNfye+s4vOsxPM0l5I45m+zRpw/atRKZNxjgyaNF7GosY3HGeC4tmIcRpUrmhzVHeLFsF+k2J9eMmUeeMz4qqPaXLxTiqeIadta3Mj/TzWVjMqL+foToC5nj1zsyx6/nvvjkRv69/sQLpLtsBmkuG62+IKBp8ATbBr5ZlDkILtTh0clqmMszWJSixd8+8sZmQIdNFGAoUEqRlmTjrtMmkpvi5A9v7yMQ0lyzZAwfXzEBo5ulHoTol23PwI7nwOKE5goo2WAupZAx3lxHr/YgBLww92pz/t7Gx8z2wkXgqYPJZ0POdCh6GGxOyJ0Jhz4wl24IBdoXinemwsJb4PAaeP/X0FwNFitMu8hcIsLXBM98AuoOw8xL4PwfxexXEo9GTHEXubEJIUTik8Svd+T+KIQQI0d/75FxU4fd+9TLsPdwl3b12Ruxhxdp1y0t+J/6D7qszNyZnIz17LOxTJk8lKEmhJbWcjZu+Tm1dTvJyV7E/Dn3YLfFf+XGtbV7+NOB/1EfaOGS/CXcOPaMPp2nqPYI39r2GvV+D2OS0vj1vEvIiXGPX53Px6927WJTXR2z09L47LRpZDnalw8pb/Xwq1372d3YxMLMdP7f1Imk2OLmI0AIIfpld1kj1/55NdVNxylK0YlSMBTfj88pTOOxO5aR4rQN/sXEyLL5X7Dql2YdiJM/Y/5Rv/INs9fvGGWY6/a11ADa7MVbchuc812ztw7M9fte+rK5DIMtyezhy54CzgzY/oz5OsNq/i/gCS/0rsy1A8F8jSPVXCKicofZ85c9FT72CGTFblrWSBM3PX7dLudA+3BP36OPoY92GsahFPY7bkelpw9ihInnjXfvoLpmc9v22NHnsWzRd2IYUf/V+Jq4Ys0P8IUCbW33T7+G8/IW9uo8Ia058+0/4dPtxQLGJqXz+LJrByzWvvjKxo28W9leWXRpVhY/X9j+3j6xdiNb69srkZ5bkMs3Zk8b0hiFOBHp8esd6fHrufnffoW6Vn+sw+jW0gmZPHnX8liHIRJJyUZ48HSiVunsiTO/Aad90fz575fD/jcHJq6O0sfB5zaf+DgByHIOEXRpaZRGTai4eOiDiWOBgCci6QMoq1gTo2gGzqb6AxFJH8Dq2t29Ps/B5pqIpA/gSEt9v2IbCGurI0s1f1hdzbEvdloCwYikz9zfteqsEEIkoppm37BO+gA2H6mLdQgi0ex/kz4nfQD7wome1rD/rYGIqKu6YmiI8vwuBkVCJX6kRa8uqHJzhziQ+Ga1Okl2j4loS0+dEqNoBs5kdz6KyEnzU9wFvT5PoSsNo9N50m3OfsU2ECanRA7FnZScjAoXXXFZDEa7ImOcnOwestiEECKW0lw2HNbhXTSlMN0V6xBEosmb07/XH6tqrhTkzep/PNE408CdMzjnFl3ET+LX3ef1yiVtP1ovvQTs9g6vUVhWrMAo6P3D/Ui3ZOE3SUoyf2+pKZNYOPdLMY6o/8Yk5fCZSReTZLGjUJyZM5erCk/u9XkcFiufmLSsLflzGFa+M+ucgQ631740YwZjk8wyyaNdLu6b1f4hrZTiK7Onku805/xNTE7ic9NlTL0QYmSwGIqfXT2P4VowM8Vh4ffX927agRAnNOVsWP5ps0qnYYOld8Hi27s5uNM/jtFLYeWX27cv/Y05Pw/AGv6Swp0DaZEdBSfkymj/2ZYEVz3cPo9QDLq4meNXVFREMBgk8LO/mI1Jdhz/7+Yux2qt0fX1aMPAcLlQNpko3Vdah/D56nE4Mk58cBzxhvz4QgFSrP37dtUXDFLqbWRcUvrABDYAtNbU+f2k22xtvX0dhbSm3u8no+MXJEIMIzLHr3dkjl/vBEOanaX1jEp34Q9p1u6vptXvpyDNTVaynfXFNUzJTcVQmlEZSSTbrVQ2ejlc14LdokiyWymr8+CwW5icm0yTN4DXH6Il4Kem3s/E/GRavQFcNgsBHaKi3ofTajA2241S0OoL0uoLYig4UNnEwvGZ+EMwIVtGYIhB5Gs2h2s6wkXovE3gqTcTwqq9kDcDHClQdwhCQUjKNP/XmdbQUg1JWdBaa77GYjMXiC/fDuNXgL8VGkogOcc8f/0RUFZIHwPeBnBnm/E0V0HaaDB6uDagAEZQVU+gPekDaPHh/fGfuqzjp5SClBT0rt0EW5qxTJ2KSk0d4khjw++tp/LwayjDSs6Ys7Da+l5lMhQKsGf/E1RWrWdUwWlMGHtp1EQiHgVCQd6o3ExQhzgrZx5pnRYTPdxSw5uVu6jyNVHozOCs3OlkO7r+Lu0Wy7BK+kJa835lJYdaWjg5O5vxyV1jNpQasqRvR52XDTWtTE9zsDBLhjB15q0M0XwgiCPbIGmCkTD/voQYzp7beJQfvLSD2mYfOgQdZ2unOa1MznFT2XSAmhYfFqVo8gQijlGAzQIKhcWAFr9GAUl2RbbbwZF6D1qD224hI8lGstNGWb0HfzCEPxgCFP5AiBBErA149sxcfn/9YizDtUtSxK9Q0Jyrt+ERqNgJBXNh0hnQXAktdVC6AVLy4bQvQd7M9tcdXQfPfdZM3AiB1WlW32yqhuZyM2GbdiGc/jV483tmMpecA8n5sOpXcPA9SCuECSuhchf4GqGpwlwrsHCRuZh7agHMvNxcF1AMibjp8etJVU8wezz8jz+BPhxe+sFmw3b9dRgJPs/P56lh3as34Ws1qzq6ksew8Jy/YbX17VvE196+hdq6HW3bo/JXsmLZTwYk1lhqDni4Zf2vONJqFkLJdaTx14WfJcNuJkkb6w7zmY2PE6B91d0Uq5OHFt7E6KTh3fP5g23beLGkBACLUvx4/nxOys6OSSwvHG7kJ1ur2rZvmZzOrVOG9+9vKDXuDlL6X1/bk1/6Agu5Z0kvLEiPX29Jj1/P/eDFHTz4zv5Yh9GtNKeVTfefF+swRKJ56g7Y8mQPDlRw07MwcSUceA/+dlEfLqZA2UD3fMkUChfDba9Iz18PjYiqnr35/kuXlLQnfQB+P8H1GwY8puGm/OCLbUkfQGvTYaqO9K3sbn3D3oikD6Ck7B283rr+hDgsvF65uS3pA6jw1vNyxfq27X8e/jAi6QNoDHh4pnTjUIXYJ1VeLy+Fkz6AoNb8M4bVbB/dXxex/cSBegKh4f8l01CpXeuPKLRWtylI0CO/HyEGi9aah947EOswjqveE2BPWUOswxCJpO5wD5M+AA1vfM/88fl7+nhB3bukD+BoERx4p4/XE70VF4lfr0TrwdShrm0JRkd5j9Ha+nou0Gji//cYivLeQh3+ZnQ3ZY+Dw/xvSOuukQdj2JvfOceTnC9Sl/9r5PcjxKDSGuJhhJN8VooB1dtnl7alqob4mafTElli8MRF4tebz0FVWIgaNaq9wWrFsmDBgMc03OSNvwBbhyIsjqQCckaf2adzpadNJTV1cuT5c0/C6Ygy0TfOnJkzl3xHett2pi2Z8zss4P7R0Yu6LNWQZLFzWcH8IYqwb3KcTs7Oz2/bNoBrxo6NWTwfmxC5tMpV41OxytyVNhmLI6dXp82xYHHK70eIwWIYihuWxe4zsSeS7QbTCkZGTQIxRDLGwYxLe378yq+Y/z3/x328oKLX5UPy58CE0/t4PdFbcTPHr6ioCO+P/9RlX+fiLgDa7ye0Ywe6uQVj2jSMzJExt8jXWk35oZdRykreuPOxOaKva9gTwaCPnXv+RmX1BkblncKUSR9DqcQYf13vb+bl8g0EdZDz8xaSaY9c/25fUyWvVWyn0tvEaFcG5+XPosDZ99/lUAmEQrxVUcHh5mZOzslhWoyLGm2qaWV9tYepqQ5W5CWd+AUjTGtpiJYDQexZBslTpbjLMTLHr3dkjl/vPLxqPz9/ZRfNvlCX3jWXzWBcZhLVTV4avUFA4w10HU1hUeayZgrwhztGHBZFmtNGVbMPDditBqlOC26bhaoWP4GgJhgKoYFAp84UBZw0IYO/3bYMuzUx7rNiGAn6YdszsO5hqN4PudNg0tnh4i41UL4ZkvPMpRtGd/jo3fc2vPB5aCw1ew6tDrMKZ2sdtNSCxYAJZ8C534bXvg3+Flh5n1nQ5cUvweG1ZtGYcSdD9T6zomdzNQR9kD8XsqdCeiHM+Wh7tVFxQv29R8ZV4ge0J39TCnFceWHU43UoRMjrRRkGhsMxVGEOC1qH8PsasdlTB+RBMhDwYLUOfrWlFl89DmsylkGe3Ku1xhvy47Qcv5CGN+jHbljj7mE8qDWBUAiHRR4eogkGNUqZ3/73VyikQYNh6f5cQb/GYhv8vyEd0GCASoBeVUn8ekcSv96pbvJS3+TBFwqR4rRjNRTVzV5cNhsoTU6ygwZvAKehKG304rRZGJXuoqyuFV8gQFApUh12spLtlNa24LRZ0ChcNkVtSwClwB8MYTE0JTVeZhSmglIoBTbDwGY1B1rVNHtxWi1UNHhJS7KSlezEaZPPbTGIfK0QaAFL+Lk44DErdVrs5jcZKHPIpdVhJovH+FvMNQDrj4QXWg9X+LQ6zWUhfC1gd4EjFQzDXM5BWc1zKcNc9iEpy0z47B2+BPZ7wusLxsXgw2FjxCzn0KW3b89Rs+3cU3AsmNHWHNywkcDrr0Mo/JVadjb2W25GjYA/rLIDz7N73Y/QIT+GxcnM5T8ka1TvFygHqKndxtr136axqZisjDksW/xd3OEF3QdSVfNhHii6nRZ/HQqDMyfextkTu1tctH821R/ge7ue5EhrNfPTJvDtGdeR26lXtN7fyv3b/8ua2gPkOVL58tTzOClr4qDEM9CeP3qUB/bsoSkQ4Oz8fL48cyb2EfB33xPBoOattX52Hwxis8Hy+TZmTe77x9/edX4ObgqgNYydZWXqssgvCZrKQ+x7zYenVpOcp5h8nh1H6sD/f6EDGv8zLQQ3+cChsJ3nwrpkZH3ZJURPHKxq4oJfvUurf/jO154/Jp2/3LKETLdU+BUDKOCFxz4G+49T8M+wgrKYPXu5M6ByN4T8vZt7Z1ghezpUbDUTvmjzCyecBpf8Fl6/H7Y/YyaE534f5n2st+9K9FH8PxW+8l7bj6GaWgKvvtqe9AFUVRF47fUYBDa0gv4Wdhf9AB0yv6UJBT3sWP1VdKj3E2a11qxZ900am8yqkNW1W9iw+WcDGu8x/9h8Ly3+OvO6hHh9/59o8tYO+HWCOsT9O/7ZVtFzY/0Bfrn3uS7H/XH/O6ypNSu/lXsb+NaO/+Lt+M3XMFXW2spPd+yg3u8nqDX/Ky3l34cOxTqsYWPrniA7DwQJafD64O0P/dQ39e0BsKYkyL51AYIBc3mkg5sDVBS3n0trzb5XzaQPoKlcc/DtwfkbCq71EtzgM+fht2r8z7YQqpFJ8kJ0dutfPxzWSR/AxsN1/OTlnbEOQySa1Q8cP+kDCAUg6DWTvbLNEPT0vuBKKGAmfdB9UZkD78CT18O2/5jHNFfCs5+CxvLeXUv0WVwkfi5Lz76Z1+XR/3B0aelAhjMstTQdRnf6RxoMtOLvwxIM/kATTc1HItpq6wbnZlTbWtKl7WD9xgG/Tp2/mbJOv4tdTUe7HLezqSxiuzHgocRTP+DxDLS9jY1dqnjuapCy4MdU1kTehLSGqpq+DXNvqOp6Q2uobG8L+cFTF3nu5srBeeAMHe10Y9agSyTxE6Kzo3WeWIfQI1uODv/7jYgzh1bHOoJINZ2WVQn5oXxrbGIZgeIi8WsNBnp0nDG6MDxOuVP7pEkDHdKw406dgGFEDg+x2tOwu7J6fS67LYX0tGkRbbk5gzPlJj858v8bhcHUrOUDfp0sewrjk3Ij2hald/27WJQeWfUtx57MGNfwr2Y6Kz29y7DOhZnDP+6hUpgX+bsxDMjP6dvHX0ZB13k4mYXt57LYFe6cyM+h1MLBmbtjTOj0pZgFjHFxM4JfiCEzNS8+ikecPKn392whjmvKObGOIFL+nMhtmxsKF8UmlhEoLhI/AJK7mbdyx0faflQpKVgvvxycHYqRTJyI9ZQVgxvbMGBY7Mw+5edY7WmAwu7KYe7pv+3z+ZYv/j55OUux29MZU3gOC+Z8fuCC7eDm+b8g1z0eUDgsSVw18+vYLYNTTOaHM29kUfpk0m1uzs9dyGcmXdzlmNvHn8JlBfNItyUxN7WQH8+5CmsczJPLsNv5/rx5TE5OJtvh4MYJE7iksDDWYQ0b0ydaWDzbitsFWemKC06143b1rRBKWo7B7JU2ktIUrhTF9JNtZI2KTOwmn28ndYyB1QmZUyyMO802EG+jC8siO9YznJCqUPkW7Ne5USnD/+9ViKH2yG3LyEsZ3nPnLp1XwOfPmXbiA4XojUW3wsJbzDl80Vjs4MqE5HxIHQ3TLoSM8eDMMIu6dEd1+pLRlQFTzwdHGtiSwOqCY8tjKcMs/jL/BrjuCVjxWfN6BfPg2sfAld7/9yl6JO6qegohhEhcUtWzd+T+KIQQI8fIqerZ2Ai/f7xLe+d1/IK7dhF4bxV4PKi8PKwnL8fouKA7oINBgmveJLR7EySlYFl5EZa8yN4R3VhDYN1/0Ud3gjsD64LzMcbNHfg3NoyVlq/iaMlbuN2FTJ7wEWy2+Bgqczxaa14oL2Jj3QFmpo7h0oKlWKN8C1bmaeCpo+tpDfq4uGAu01PaF0cPac0ThzfxUtlu3FY7d0xYwsKMxOhd8wZDPHO4ggNNrSzLTuOM/MQZLhoMarbuCVJVF2JMvsHU8YP38ddUHqJyRwCLXZE3x4JDeuGEiLlbH17Dm7uqBux8x1ZyCYa/P7dZFAYKb7D7Ob0KuqwLqAC3w8L9l8zkI4uH9yLzIk4dKYL1fzfn+wVaYfyp5v/e/hF4GsHmNAustNWK0ICC5FxwZUNLpbk98zK44Mew9Sl4/zfQVGb25uXNNnv8tv3HLPKiLJAx0Xydr8WchuXKgLErYMIKqD1oLvuw8CYoGFnP1rEWNz1+q66+q9v9x5K/4L59BJ76T5f9thuuj0j+/C/8k9CODe0HKAPbTZ/DyDEf7rXfh++vn4PGyBuE9dIvYpm8tB/vJH4cOvI/1qz7Ztt2dtZ8zjjljzGMaGA8sP8l/n64vbrVlaOW86UpV0Qc0xzwcu3aP1PlawLApiz8edFNTEk25wj+cs8qnjyyue14Bfxq/iUszhg9+G9gkH1t4x7erahr2/7MtLF8ZFxe7AIaQK+s8rGnuL3wyfL5VhbOHPghmM2VIbb9y9tW1MzmhnnXO7HY43+NvaEgPX69Iz1+PXPzX9bw9u6BS/oGy59vXsTZM/JPfKAQPXVkHfzlXDMhGwg5M6Byx8Ccy+qEO9+G3OkDc74RoL/3yLj4GtrSw0W0g6vXRG/fsqXtZx3wE9q5MfIAHSK0fX3bZqh4Y5ekDyC05Y0exZEI9hc/E7FdVb2Rxsbi2AQzgJ4rWxux/Xzph4Q6lR1eVb2vLekD8OsgL5W1V5x6tmRbxPEaeL40/ktw1/n8vNch6QP479HK2AQzwHx+zd5DkdUut+8bnOqXVTsDEZWs/c1QVyyVNoWIpXf3DP+kD+AXr+6JdQgi0Wx8dOCSPhi4pA/MReQ3dx3NJwZPXCR+oR72SipX9KIgqmOxF8MC1ijf8jtd7cc73NEv4Iz/oY49ZbeldmoxsNq6+b3EkRSrK2LbbXViqMh/BqnWrn9HKR3a3JauBQJSrfG/aLbDMLpUBk2xDk41yqFmGND5rTgGqc6DxdH1iyprlDYhxNDp6RfIsZaVNLwL0Ig45Ewb2POpAU4dnOkDez5xXHGR+B037euQw1nOOAMsnZ7ukpOxLFzYtqkMA8tpF0Qe407BMrd9CKcaPRNj4sLIYxxJWJZc1rvA49iMqbdis7YnulMnXYPLmR3DiAbG3RPOxxL+0DJQfGLCBV2OWZo5gSUZ49q2C53pXD5qftv2Z6acTMdHiGSLnY+NmTdYIQ8Zl9XCzZPah0Q7DIOPT06MuYtWi2Lp3PYPC4sBy+YMTqXNvNlWHKntfyFpYwxSx8TFR60QCeve86bGOoQTUsD9l82KdRgi0Sy9E9LGRNnRxy9DFtx0/GqfJ9IxccyabM7zE0Mmbub4FRUV4f3xnyJ3zJmM48IzIppCXi+hdevQjU0Y48ZiTJqEsnX9Aw3VVBDavgHSM7FMX4CyRhZ60Fqjj+4gVLYX3BlYJi5COZIG/L0NZz5fA+WVH5LsLiQjPXHGX5d76tjScJDpKWMY3c06h1pr1tcdoiXoY1nmBOxG5N9HaWsDL5XtJsPu4vz8qbgsg5NExMKBplYONLWyICOFDEfivC+A2voQVXUhRuVa+rycQ0+EApr6wyEsNkgpNFBx0tswHMgcv96ROX49t6Okjlse/pCqJh8Zbhs5yU4sFs2+8mY8AY3LCnarQatfk+K0YjUUHn+QJIeVJk+AVn8Qf3gYd5rTwkmTsmhqDXCguhmUYlpeMnkpDoqK67Aq2F/djNZgsxjYLIrCDBf+cCWYRo+fYEiT7LBiGAZzCtP43hVzSHbETc09EU/8rbDvDagtNgurzPkIZE+FVb+CxlLInWXurysGdy40loA9GWZeai7PUH8YfE2w5HazGEtzNaz/G7TUQNALY0+CvLnw389CzT5IHwfL7oJdL4Kn3iwaU7jEnMs3/hSo2GHGNOlMsEovd2+MmKqeAMybCpt2t212TvoADIeDUE4OutWDVgqs0d+ikZmLccp53V5KKWX2/I2e2e+wQwEPnuJ3sGfPwBr1W5eB5fNU42utxp0+GdWPLnmLxUkoFMBqGfyE1xtoobKlmDz3RGyWwR02medMJ885/7jHKKVY1KHXr7MCVyq3jF/EnqYqWoP+YZH4+UMh1lZXk26zMSs9vc/nmZDsYkKy67jHaK3Z1+glw2EhK46Sw4w0g4y07v9N+P2aitIgriRFZnbfh7kaVkXGhP4Pk9V+je9IyByhXmigLJJACtFXU/PT+M6ls/jjOwfISLKS4XawbEIGL2wpZUx6Evuqmqlp8pCd6sRptXDKlBzW7K/mYHUzZ07P5WBVC4aCygYPzYEgDS1+xmYmUdPiY1JuMlVNXsobvPiCIdKTrMwqSGNSbhKzC9PZeKiWd3ZXkWQ3mDM6ndEZTtburyMnzUl5fStj011xMxxVxCF/KwR84EgxK3O6c2Drs+a+5Z+Cw2shrRAu+TUc+RAqtkHWFGitheWfgKYKKFkPVXtg8xNgTwd3BoxeAmXbwJ4KRz+E3Bmw5E44/AF4G+CMr0LFdmiqhtZqSCmAoN+s8GnYzWRz2vkx/dWMNHHT49dtVc+x+TiuvQSAUGsr/j8+CD5f+36bDftdd6KSYtNb13rgLapf/yrHqj04J5xF9tnfH7TrHdrxdw5u/QNaB0lKHc/c036NI6n3VRnLK9fy7gefQ4dL+44ZdTYnLRmcuHdWvcfjW76JN9iM25bODfN+wvj04T10sszTyOc2Pc+hljqsyuDuicu4buz8mMWzp7GRu9euxRsy/87Gu938adkyXJ2HPg+Aaq+fLxYVs6/Ri0XBTZNyuHVy7oBfZ6gdPRTkvbd8bYVZ0jMUZ13owGaLzcOY70CQ+n/6wG9uqyRIv8mBNS+xh41Kj1/vSI9fzxysaubcX7yNLzi8n3n+9vElrJwa/5+nYhhZ8yC8dC8nmDh1HNEWIRlAzjT49DpIzhm8aySQEVHV87gOlbX9GHzt9cikD8Dvx//Gm8RK7bs/pGOJP8+B1/HX7BuUa3lbKzkQTvoAWhoOUrzjr30614cbvtd2HoDDJa/R3Fw6EGFG0Frz7M6f4g02A9Dsr+P5XT8f8OsMtIcPruNQSx0AAR3igf1rqPG1xCyeH23b1pb0ARxsbuaZw4cH5Vr/3F/NvkYvYK5f9de9lZS0+E7wquFNa83a930R1TjrajX7dg1gJbReanyxPekD0C3Q9Jq/+xcIIbr145d3DvukD+Bzj2848UFC9JSnAf73VfqXuA3yvxtPPTz/ucG9hmgTF4lfSpQqitHourro7TXVAxhN74R8jV3aAo0lg3Itb0tZh8U3TZ7mvl3L52vo0tbQOPAJa1AHqPdURLTVeAbn9zOQSj2Rv5+gDlHuaerm6MFX7vF0aTvUMjiJaGlrZJKngbLW+E5IQkHwdv0V0tQUuwfFUG20tuH/4CrEcHSwqjnWIfRIbUvsvmwSCaipAkJxcH+uPRjrCEaMuEj8GoM9600w5s2N2m5ZtGggw+kVe16nIYuGDceowYknJWMGTndBRFvO6DP7dK6c7MiqpoZhJz/v5D7H1h2rYWNGzqkRbXNy+xbzUDojZ1LEdqErlakpsat6emZ+1wV/zysoiHJk/63Mj1zqI9thZXbG8ecEDncWqyJ/VNePwzHjYrechWNW12s7ZibG8hpCDLUrFsZHheJTp0QvOCZEn2RPhsxJJz4u1hbeGOsIRoz4Ke6ybDas2dql2fHlO9p+ts6di25oILR6DYRCoBTG0iVYZ8WuPHL2+T+n5o1v4C3biCUpm8yV38CwDc58Q2VYmbvydxRvfwhvSxk5Y86hYGLflqBYsfSnfPDhV6isWofDmcnShff3q1DM8Vw965u8vv8hjjRsZ2LGQk4ff8ugXGcgXVE4C43mjYp95DtT+Pj4xW3LRMTCZ6ZOJaQ1b5aX47RYuGPSJOZnZAzKtc4dlU4gpHmlpJ5sp5WbJ+V0Wf8vHp18up11q/2UHQ1itcHcRTbyCmKXaKVcbEM5wbc9CAY4F1pJOjV+PrKFGE7uOHUiNU1e/vDOgViH0q0Fo1N58MYlsQ5DJJpbnodnPw3Fq8zCKrYksDmhuQrQoGygw72Chj282Ht43oNhhf/P3lmHR26d+/8jadBjZl57mXmTzYaZ20CbNk1S5ltm+N3b3pTT9pY5pTRN0wabhjlL2WSZyczMw5LO74/xeixrvJ7x2mt7V5/n8fP4HL0650gzI+nVec/3LTkPHC6o3RZR9hwK/ZQiubGFDkIGNExhoa70SJJ2NRjZ5vBA5mwIBcDbFtl/zXvh3I9O+mmwiDBjxF2sxesWFhYWZz6WuEtiWPdHCwsLi7OHsyadQ/DxZ+Bog6ne8aUPDuXIEuEwofv+Bp2Da/pcLpQNG1DWrI7aCIG2awv60b1IqRko51+JnDE+JSGts4rg9j8ivB3YF1yDY+nNJhuhBujb9UeCzbuwZy8ibe2HkZ2pMVo7dfq7jnL4jf9H0N9OSsYill7wQ2z25LF3HAdCCF7d9f9oaH8dhy2ZDcu+REneBZPSV7xoQufv9U+wsXM7pUmFfGTWO8g7A5LOx8uzTU38tqKCgKZxQU4OX168GPsMn4nrDQoeOhymrk9nea7CTfMjubWGowvBlqMqh5t0spIlLl9qIz1pZh/3VKAd60V7ox1kCeW8XJTZKZPX18Fa1D1VSE47tg2LkQszJ60vCwuATm+Qa36ykfaBqRWiWjMrnd21PegxtnkcMvu/eTXyDL9uW0wz2g5HBF6qNw7O5gGKE/KXR/LzDbQY7WU7JGUDIjJTZ3NCyBuZ7ZMkcGVA2BfRlNDCxBR/saeA6jPpTpiQZFh5J1zzPXBOzvOqhZEZM+M3ajoHouGewb/eB62tpu22K69AWbUKAG33VtSXHo9uTM3A8cEvIcmJhXQJNcDAfbcifFHhGNcV38Cx8FqDXfem7+E98u+oTen5ZF/944T6igddC7Pl8cvRteBQXXLGQtZc+dcJ7wtg4567qWh4aliNzB1XP4/TPnkPi2Px57pH+V3Ng0PluZ5Z3L/mh1M2ntPJod5ePvzmm4a6GwsL+fIUhjlPBHdvDnKkM/qIdP0cG3csNeYN3HgkzAv7o4IIuakSn7jKaSVNTwC92UfoD8ei929ZwvHxhchZE59TU6tsJvyvTdEKhw3nx65HSor0Zc34JYY14xcfa771Ap3e6a8+nJ3sYMf/u3Kqh2FxphD2w0+Xgbd9qkdycpa/A275/VSPYkZwVqRzyHG44jOM4fQBaMeiSd+14yPWCfZ1I1oTV5HUWg4YnD4AtepVk52/2lgXqNuKiFOsJhH6uw8ZnD6Age4jE97PCRratoyo0amof3rS+ouHVzveMJQrvLXU+1tGsT6zeLHFfJwb26f5hX4M+oLC4PQBvNlsfnt4qMFY19Yn6JhCNc6ZiHa01/jSVhfox3onpS/9WKOxIqSi18S+dltYTAS6LmaE0wfQMcUzkhZnGHXbpr/TB3D4P1M9grOGGeH4tYdi6KzHwhE77YOUHhW5kDJGKGbJClJq4iIYcmphZIp6eF1ascnONqJOSc6LTKNPMK4ks4KjbRJn35Jc5vDYnPSpnV0qdhuVLZMUF1mO9KkZzGmm3OMx1eW54nxhMk1JskPqiJ90vsc8i5eZbPwd2hVIcVmzfYkgZ5pn9qQYdROBlGEO54lVZ2ExUciyhDJDLgkzZZwWM4SMMiIJ2Kc5meVTPYKzhhnh+J0UT/ThVnnLjebtmZnYNpw3VLStvwIpe9BBUGwoF1+P5En8oUNOLcR57ocjikeAnLMQx+o7TXZp530W2R1ZvyI5Usi44MuTEoLmTMqlcM6t0QpJZv7ar054Pye4aOU3UOTog2FRznnkZi6dtP7i4aNlt1Psiny2LtnJ5+a8jyRlZjs/8XJNYSELU6NrR12KwtcWL57CEZ06Nlni/SscuAdXIme5Je5YYn5pcsVSG1nJkd+UXYHrV9lx2WfAjW4aIS/JQF6UFi0vz0CePzlrkZVVc5BKB18cSRLKOfORC6w1fhaTy/+7ftFUDyEu7rl12VQPweJMIrMcLv26aaJiWqG44LofTfUozhpmzBq/HTt2ENz4Jry+d6h+uLDLCYSmoe7cCXY7SkkJUlaW2UYIRGcbkicFyX1qqRV0fw/C341ykrcVQgsT7qnBllaCbJtcRyToa6ev6wBZBRuQlcl5Y38CIQQNbVtI9ZSQljxrUvuKF13oVPsayHNmk2ybnLQZ05nK/n66gkFWZWZiO0MEAgKqoM0nKEqWUOTYDp0uBO19glS3hNthOX3jRe8JIkkSUlrs6IkJ7aurH8lhQ0o25oC01vglhrXGL368QZXfvVqBXZEoz03BZYPvP3MEt8PGkoIUunwqc3NS2NfQTUd/kJxUBxfNy2ZfQx82RaKq3Udxppvm7gCa0OjsDxLWdTKS3czLSeZ4az99viB56UmUZSfT6w9S2eZlZWk6DpuNa5bkcdmiPPY19PDnzdV0eoNkJTvo9obI8Dj4v9tWWcIuFpODtwM6KyMCL+llkJIL+csi6RT2/AMy50LVK+DJhvKLwJkSEXIJ9kcmOFKLYN9DkRnEknXQ8CZkzYX6N8CRCv5OkBTwdUSEYeZcCv4e2PsPKD4H+hpB10CxwUB7pJ3OYzD/2kh7tsl9Xj2TOGtUPQGD0wcQ+u3fcX5sxCybLEM4jKiuQaRnIGebVR0lSULKzkNvrkevPoI8ax6SZ3xhkbI7HdzpJ7UJd1cR7q5CcaXDJDt+A70VdLduR1acZBWMP+G6rqvU1D9DY9Mr5GSvYcHcdxkcaCEELZ07CWsBkqaRcmZIV6n1NdEe7GJdxvJx5dbrDvnY1lVFb9hPgSuN9ZmzcSrmn0rFQCcVA52sTi8k1zX1oWohXafJ70eeYaImjV6Ng90qi9JtlCSbRZZcNonS1JMfkyxJ5KWd+nH39+l0tOtkZcukpp1ZD2B6ewi9KYhc4kLOjB1uLqefvpuvnDl1QlAWZyf/2dPI7zZWEdQiL7wloktbj7d6kdDZeKydVSXp9PlVjrV52V3XSyCkoxIJw9zb2IdDAaddxhvQcdplPC6drZUddPlUBNA00Mfuhr6hfuu6W5CAh3aalckBnArMzklmT0Mvq0snJ/+qxVmMrsOr90DFCxGHLjkHHMngTIWMUlhyC2SUQ9tBOPYsHHtu8LlWgmAfFKyEo0+DKxXueAhqNsG+hyNOoc0eUfbsqQObG7LKYNYF8PpvYN+DEYfu+IsQ6I0ogUpEtje8Ab2N0F4BF38eSs6Z0lN0NjFjZvziUfUUQhD61a/A5x/aJq9aif1Ks0KW+trTaNtfjRRsduxv/xByUdlEDhuAvp330rfr3khBcZB99Y9xFU1OgtbD2/6Htrrnhso5xZezeMN3E25H0wI8/8odDHijNymXM4cbr3lyqPzi9i9S17oRALczkxvO/yMpSYWnMPpTpyvUywf3fJ2mQBsAq9IW8Yvl/4NNil+x9VBfE5/c8yB+PTxUV+rO5Per7yTVHp2ZuK92F7+tiojJ2CWZHyy7lvVZpRN0JInjVVU+8uab1Hi9AMxPSeE369bhVKYuAXk8vNAY5Ht7BtCJ3A++sMzD9aVTE55bU6XyxqYwJy6J6zbYmTN/Zr0bGw11ex/hpzoiT7ky2G/NxbZ06l9WxMKa8UsMa8YvPu6493W2VHRN9TDG5DOXz+UzVy6Y6mFYnEl8pyDidI2KFHEIg30nsZlkLvg8XPE/U9f/DOKsUPWM9z2+VlVtcPoA9D17TXbCN4C2c2O0Qg2jvv7SKYwwNnrIS9/e+4YNMETfrj9OeD8AoUCnwekDaG94iaA/cTWn+saXDU4fQCDYTl398wC0de8fcvoA/MEuDlY/yFTzePOLQ04fwO7ew2zr2pNQG3+t3WZw+gDq/F081bJ/qBzQwvylZudQOSx0/lizfXyDniCebW4ecvoAjvX388ooKrfTiT8e9Q3lsxLAvcdOdnOaXPbvUhn+Hmz/rvDoxjMIIQThl7uiUxs6qC93T+mYLCxONzPB6QP41SuVUz0EizOJN/84htMHIKbW6QN4/ReRmUmLSWdGOH6OeGdsfDG+3LFmNMNh8xcsXuXQBBBaaDC55bC6kHcU61NDU2OPX1P9MetPhqrGHmMwFLlxhmNsj1V3uvFq5mONVXfyNoKx69VofVjXCenGFAID6tRKcPtU1VTn1cZInDoN8KnG36cvLJiqKIRwWIwoM2VjmVAEEDIehwhYN1gLi+mIqp8B1xyL6YN3+r8ABiLPymMle7eYEGaE4xeM88ugLFwQWeM3DKnQHH4opWUglRlDKZQV68c/wNHG487AXXaxoc6z6OYJ7wfAnVxEUtocQ11SajlJKYmHHxYXXoYyQg1TkuzMLouohhZkrSXVUzpsm8L8kreOY9QTy/V5F+Mcliojx5HBBZlrEmrjpsKVpjq3bOfqvGiqihS7k8tzjef6psKpTWVxRX4+Hls0LDHNbufS3NwpHFF83DgirPPGWa4pS7w+d4ExrHPOAuWMSAIvyRLKauN6Ottaa32dxdlFtmfyBYsmgksXTv/rtsUM4vzPEFfc3FSrfs69ApSJT3VmYWbmrPF75ln402OmbSfW951A6+lBffQxGOhHLp+N/cYbYrYpwiG0vdsQ3R0oc5cgl09OTL1Qg3iP/JtwdzWu0vNwz7poUvqByOxexZ6f0texl9Ts5cxd8RkU+/iULb3eJnbu/QHdPYdJTi7lnDXfJMUTzUnoD3ZztPZR/KFu5hZdS07G1Do+J6jw1vFky8u4FRc3F1xFrjNxmfg3u6p5puUAHaEBypOyuaVoFWUeo4BNWNd4ovkwFQOdrM8s4eKc2RN1COOmzuvlP42NyJLEW4uLKXS7x95pihFC8EJjiP3dYRan27i62Dll4jRCCGqrNNpbdbJyZMrnnhmOH4DQBdrufvTGIHKZG2WZZ9oem7XGLzGsNX7xc8k9r1DTNXY4uSKBdpofjWQJbl9XwrdvXjZtf5sWM5TWg/DAO6CvCRARERbFERFeSSuCNe+PiKs89lFoOwRCB9kBJxZi2JwRhU7FBhd9EVoPQPUmCPsjDqNQB6PbJHB4IHs+dNdEFD4Bo4wSkbYlGbQQ2JNgzXvhqrsjCqMWY3Kq98gZ4/hZNzYLCwuLMx/L8UsM6/5oYWFhcfZw1qRzCP7gD7E3vOUKnIsiOfT0/n7C9/0NholcyGtWY7/8csMuWks96oO/BXVw/V1mDo47P4nkmHg1QaGF6dn2M/yVz6N4cklb/2mTqqe36U1ad/wc1ddGavlV5K37DJJs/GiC3haqt32LgbY9AHgyF1C2/r9xpxnzB4aDPRzb8T2627aTnL6A+Wu+TFJq2dD2xtqnOX74XnQtQOmctzN34ftijrutYyd7D/wUr6+FkqIrWLn0syiKMVSmuWMHbxz6KQP+VmYXXsm5Sz6LIic+VX+ofRP/OvANgpqXVGcOH1z9K3I80byAh3t289eKn9AeaOa8nMt599zP4jiFHIV/qX2ZR5q24JTtfKDsSq7Ni4aDqrrOr6pe4dmWg2Q6PHxiziWclzUnZju/qdzGg/V7UYXOotRcfrvqJmwj3ljt7G7m58e30xrwcmVeOZ+atw679VZrQvGFBP/ZGeZ4i0Z+usyNq+3kTWIqhsZjKpU7VXRNULrExuxVVniKhcV056EddXzx4f1jG04hNlli85cuJT99+kdrWMwQQj748fxI6oXpijMN3nE/zJ68iDiLKDNijd9JeeLFoX/DDz1scPoA9J270GtqhspC6EanD6CrnfBzj0zK8Pr3P4D30MPowT7CXRV0vvBl9GECL1rIS8MrXyHYXYEW7KP7yMN0HnzA1E7Ntm8x0LozsvhVaHg7D1G5+esmu+O7fkhH46toYS+97bs49HrUpr+vin077sbvbSQY6OT4wd/S0viqqQ1V9bP1jS/R03uMcLiPqppHOVrxN4NNWPXy4o4v0dV3nFC4jyO1j7C/8v6Ez4+mqzyw76sEtcg56Qu286fdnxraHtQC/OjAl6gZOIpX7ePF5sf4d919ozU3Jq92HOB3Nc/SEeqnMdDFt478i+phi58fadzJPxt20Kv6qfZ18LWDj9MXNgvEHO1r5291uwkLHQEc6mvj24dfMdh41TBf3fcKFQPd9KshHm08ygN1B8c9dovYPLsnzIEGjaAKtR06D74emjRRloEunQOvhvH3C4I+OL5dpa3GWpBuYTHdme5OH0SEXa77+aapHobFmcRfrp/eTh9AsBf+8Q6TGKLF5DAjHL/UeGd3umNLlGt1ddFCf5/R6RtE1FWMZ2hjEmzebewn7CPceXSoHOg6gq4a1xz4Wo37APQPzvQNJ9BbhRrsNdT1thvtvL0VqKHIj767Yy+GOGugq2OXqd2evuOE1QFDXXuHcUydfcdNSp4tnea2xqLT14gmjJ9HTyDqiNV5K/CqRpnhw72J93OCPT1VhrJAsKe3Orq915jGIqirHOprNrXzYpv5+7Kv12hXMdCFd8SFbHd3S8Jjtjg51e1GhcqOfoE3tjjrKdPdYlbD7Gq2HD8LC4uJoctnPfxaTCCtB6Z6BPER9kHn5DyHWxiZEY5f3ygS+yZSU2NWywXDlD2TUyMLVEdSMDnJtx25RtETSXFiz4iGDroy5iKNcGzd2YtN7XiyzHXO5GIUh/GYUzKNdu6UUhR7JFFzWqa5jfQYoixpKbNRFGOoSWaGcd+M5NnYRih/5qQnLvCSmVSIPCJdR4ojKshSnFSOSzEK1MxJGb+QzOLUEnNdSlS0ZlFKgWGbTZKZl2xWWbswu8xUNz/FKABT7knHNSJkd3Gq0cbi1CnONF7G0pMkksYfCXxSUnPMl8y0GHUWFhYW4yHFOWNW4FjMBDJjL1WZdihOyCgf287ilJn5Tyzrlg79a7/lZnAY16FJCxeizJsbLcsyys3vM0rXelJxXHvbpAwvZcVduOdcCZKC4skl89JvIrvShrYrzjQKL/wGtqQckBRSy68ia+ldpnbKzv06rvTocTiTi5l9/t0m9a+5q79AWs6qyGGlzWHRuVGbtPQFLFr+Wez2VGTFSdnc2ykoucrUl92ezPo1d+N25yFJCsWFl7No/nsNNk5HKhevuhuPK2JTXngFy+e+J+HzY5Pt3LzwayhSZJ2Uy5bMXSt+NLTdbfPwyUXfItuZj4TMuTmXccus2OsS4+HKnJXcXnwhTtlOis3NZ+a8hQXDHL93FK/lmrwlKJJMtiOZ/154PVnOZFM7y9MLuLFg0ZBIcok7jf9ZZFxLmmp38o0lF5Ln9KBIEpfnlnFX2bJxj90iNtettDM7N/J7zkmRuG29Y9KUQdNyZBacZ8fmjAiQzVpmI3+OtWbTwmK688Wr5k31EMZEkuCxj2+Y6mFYnEl84LmIgud0xuaEW+8F+8TrbFiYmXGqnkMiL/MKcN4SO1WDHg4jdB3ZbkeSR/dttWAAyWZDjjUDOMEIXTUJtozHRtcjibrlOOxGs4l85jqSNPYD68naScQmHkJqAIdt9B++pqsoE9APgCZ0ZKRRZbNVXUeRRt9+AiEEIV3DOcZ3SNV1bCf5LlqcOpouUOTTI4MuhAARyZFnMbFYqp6JYal6JkZjVx/d/UHyMpMRAhyKREufD7fdjiTppLldhMIqKhLJdht2m0xI1QiEdWRJIEuCLm+YFJcdu01G0wQ2RSGkaQihYZNlugdCOB0KDkUm2eVAkiQ6B3zouoQuBMkOBX9YJc3jRtd0FCVyb0jzTFKogoVF0AdqCGyOiIMV8oKugWyLaEcojkjWBV2NrAiyuyPCMIo9sjxKqJG3nYqdofQMoWBkEsWVFFmfd+KZUg0OOptSxFQdjNqTAF0fTCUxKIqmq5G+LOJmWqt6SpKUDtwLLCXyVXo/cBT4J1AG1AC3CSFiL84bgUHZ83gzwR/8wZTHT+3oQHv4EfB5ITsb+5VXIhcYw/eErqM++QB6Uw1ycTlcdzvyJD2Uh3tq8FW+gOLOIGnedcgnyas3ltMHYzt8Qlep3Pcr+jr3k1N0MSULzbOHEWcmvlmKk/UXCPWw48iv6RuoY3bR1SwovSnh/EO60DnQ+hLNA8eZl3kus0dJuL6v6w2ebfwXCgrXl9zBwvQVCfUznN09VWzrOsrc5AIuy1mOMiJxqSZ0/t28h1faj1LqzuR9ZRvIcRoTXh/r7+DV9iryXclcnTd/zD5P5vSFdZ0XWuto8A1wQXYhi9MSzz0Y1DSea26mNRDgkrw85qXMnATdFX0qrzWHyHPLXFnkxKmMz5mKx+nr6NaprNdITpJYUKZgs0X30XXB3p1hOtp0ikoUFi8fXa1TkqS4cuJaWIzGRN8fLcbm/54/yq9erUTTx37hLTOUxey0IAOfvHwOn71y4Wns1eKsQajw1Geh/nUIDkDohI6DDMRapy5H/twp4EiFYF/kT2gg2wflIvSIMygpkTpZhkBPdH9JBiEiSSqRQQ9FNkl2cCSBGgBXGqx9fyQ/4GmYhLGY5Bk/SZL+CmwSQtwrSZIDSAK+BnQJIb4vSdJXgAwhxJdP1s7atWvFlrd/ZNTtJ5w/4fUS+tWvTdttt9yMMjcaJhn83XehvydqkJqJ88Nfif/A4iTUfpi2/3wkkqQSsGcvJPemPyFJkzfzs+O5O/D2RhfIZhdfzpIN353wfkLhAf718s2EwlHhlfmlb+WC5V9LqJ3Hj9zDGw1RRdVbFn2NdUVvNdi82PQY9x77vqHu04u/w3m5VyQ87idbtvOdow8Nld9acA5fmf82g81/H/w3L7UfGSonKQ7+ec6HhkI+d3Q18Nl9T6IN/nbWZRTzs5U3JjyWE3x131Y2tjcCkUvtd5dv4MKcooTa+PTOnezs6gJAkST+b/Vq1mQm7kCebnZ1hPnim31DyZJXZ9n5v/Wx1+qeKo2tGk+8HOLEM19RrsxNV0TfsD/77wA93dHrYVGpzIWXWW/gTzdny4zfRN4frRm/sfnfJw7y5601Uz2MMbl9XQnfu3X5VA/D4kzj+2UQmMbvkGZtgPc9M9WjmBGc6j1y0jwQSZLSgIuAPwIIIUJCiB7grcBfB83+Ctw0VltKnK/WQ69tjFmv7YyqQIqAz+j0AfR1oYdDcfWRCAOHHh1y+gDCHUcIteyZ8H5OEAp0G5w+gI7GV0axPjVqW141OH0Ax+ufRNPjVyQLqj62Nz5uqNtc9w+T3ZP1f49RZ055EQ//bNhsbKd5BwNqNF1DT8jHy8OcPgCfFuK5tkND5Yca9w85fQDbuxuoHOgc13ha/N4hpw8ib5j/VX88oTYq+/uHnD4ATQgeHq5kO415tMY/5PQB7OoMU9WnTkpf+4+pDH/R39im094deafv9wmD0wfQWK9PWloIi7Obibw/WsTH37bVTPUQ4uKhnQ1jG1lYJELFy9Pb6QOo3QoD7VM9irOCyVx0VA60A3+WJGm3JEn3SpLkAfKEECd071uAvFg7S5L0YUmSdkiStKO1vS2uDiVb7PBFSRl2mKOFIk6CGETM0M0JWqMWs78YM4nSJH3EsmQ+DkmSkRKIf5Mk2dSOEqPdWHW2GHXxYBtxjmRJQh5WF/nffAzD9xvZBjDupOyKJJt6syc4IxwrjNQ+Q9YT2mKEZ07WOj05RrsnqmKdciuS02ISmbD7Y3u79bAUD4kuQ5gqZsgwLWYS013cBQApEjZqMelM5tOhDVgN/EYIsQrwAoZ4ShF5nR7zlboQ4vdCiLVCiLXZOTlxdWi/6KKY9co55wz9LzndkGW8l0o5Bci20dfzjJfkpbch2T1DZWfhWpx5kxfCYXemkZa90lCXXz7+EMSTMavgEpJcxs9lSfk7ExJ5cSguLih951BZQuaS8vea7G6d9X5DWULipllmu3h4d+llDHe13lF8IUnD0mmk2l3cVGBcP5hhT+KavGgKidtLVuAcdpyX5cyhNCl9XOPJcbm5vqBsqGyXZO6Yldgaj1keD5fkRlNOOGWZd8yaNa7xnG5uK3fhHHYVuijfwazkybn4r1hoY/i7ofJimaz0SOcul0ROnvGJq3yOMmMeFi1mHBN2f8yJ8/54tvPpy+aObTQN+PCFs6d6CBZnGuUXQGpiy0dOOwuuhaTpvzzlTGDS1vhJkpQPbBNClA2WLyRyY5sLXCKEaJYkqQB4VQix4GRtnVjDYBB3GcQk7uL1oT36KPT0QGkpjosuRMrIMO0X3vQseuUhlLlLsF1w9fgOMg40Xwf+mleRXZm4yy6KS8DlVGk49k962neSW3o1uSWXj73DOFG1AAeqHqC7r5K5xddRknf+uNqp6tpJ08Ax5maeQ35y7Jwztf3Heb7pERRJ4Zrid1CYNP68i9XeVt7sPs4cTz5rM2I/DGxuP84L7UcoT8ri7cVr8NiMa72aA/1s7qihwJXCeVmlJoGYRBBCsK2zhQb/AOdlFVCcZE4fMRaaELze3k5rIMD5OTnku2eOSlarX2NLa4g8t8L6XDvKJDpb/V6d6gadZI9EWaFsmAUUQnD8iEprs05pmcKs2dZC86ngbFjjNxn3R4uxeXJvE19+ZB+BsAYitqQFgE0Ch00irAl0gSEcfbJIdkh879aV3LiicGxjC4tE0VR4+VtQ8VJE3KVvMKTY7o4IvQg9Irpy4l2TzQHIkFoI7gzwdUJ/c0S90+6KCLro4YjKp+QAuxPsydBxKLKf4oy0IfTINLbsAH83oIMrHZKywd8FKQVw3sdg5R3WdHecnOo9crLFXTYBHxRCHJUk6ZvAiemvzmGL1zOFEF86WTtDjl91Lfzr+aH6kU7fcLSeHvB6UYpGf8uhD/RDKICcOfobU+HrBbsbyX5qU+V6yAtCQ3aOX7hC18KEfG0o9iTsLrMzC6CFfQT9HTjcWdiGzTZOZ1Q9RF+wk4DaT55n9klTNnjD/UiSRJJtdOeoPdhFuj0V+yjtdAb7ODrQyMKUYjIdo6tf9ob92CWFJFvsz77a20VvKEC5J5M0x9TnnxFC0Oz3Y5Nlcl1TP55E6AzopDok7OMM8wypgrAGHufpu3EEfQKbAxSbuU8hBGEv2JOslA+jIVQN0T2AlO5Bskd/q2eD4wcTf3+0iI9DTb08vruesCqobu8jNclBfmoSATWMTZKoaPPisClctSifzZXtpLptXL+imDcqO6jt8rKyNJ2GTj+56W7m5SSzp66bwkwX/T6NbVXtaJogPdnB9csKOdDYy8GWPvKTXeSluUlx2Tjc1MusDA9ZaQ4ONfTSF1RZPSuDWVkezp+bY0UZWEwOVRsjjpkrBao3RdIopORHVDdrN0P2gojjlV4GrfvBnQZZ8yPLk7wd0HYYVt0OHcehuxZqt0FqAXhyQHGBCEBKUUTXwt8Lof7IDTC1CBxOqN8FaJCzKOJIphREUkpIAgpWWGGeCTDdHb+VROSqHUAV8D4i4aX/AkqBWiJy1V2jtQHxq3rCYF613/8BensjFYqC7UMfREmNOlxC1wn/6/eIhqpIhScFx12fRkoeZhPwEn7y/xB1+8HhxnbRXSjLE1eRBOh54xcMHPgXCI2kedeSceFXE57566p7mZrX70bXAgCk5K1l7kX3oAxLD1F76E/UHPxD5A0LEsXz72DOyk+Oa8yni32tL/LwwbsJ65E8L7Kk8LbF/82qgmsNdrrQ+dOxe3i5+QkkCa4svJX3zP2c4SbZEujgy4d+yNGBajLsqXx13ke4KHudoZ2P7/4Nu/uqh8qr0+bwixUfMqzzC+kqdx9+klfaj2KXbbyndD3vK4vOZrYGBnj39n/RfyI3DXBB5iy+v/zaSUscPhbVAwN8ZudOOkMRMaFyj4efrVlDpnN6q1K2+TX+e2c/R3s10hwSX1jm4cL8xMa88UiYVw+pqBosLJR5+3oH9nGmhIiHUECw54UQ3c06NgcsWG+neGH09+zr1Dn+TIhAj8CRLDH3KjsphdZNbTjhncfRXtgTeeiQJGyXLsd2bmRi6yxy/FYyQfdHy/EbG29QZc23niegTl/BJgn46/vXcdH83DFtLSziorcZfrY04uhNV2Q7vOdJmLV+qkcyI5i2qp4AQog9g+sQlgshbhJCdAshOoUQlwsh5gkhrhjrppYo6rY3ok4fgKahPvywwUY7sD3q9AF4+wk/+5DRZvvjEacPIORHffmPiIHEVZECTTsZ2Pf3yJS40PEdewpf5QsJtaGpfmq2fXvI6QPob91B69F/Rg+ht5KaA78bdPoABA3H7qe3Y2/CYz5dBFUfDx/89pDTB6ALjUcPfxd1hDrojo7XeLH5MXQ0NKHxbOO/2N21xWDzq+r7OToQceq6w318+9hvCOpRVdWNHQcMTh/Art5KXmrfZ6h7omkvL7cfRRBxAv9Qs5mj/a1D2791+CWD0wewuauWV9urmCp+dPjwkNMHUO31cm9l5ZSNJ15+f8TH0d5IwFVvSPCDvV6CCcRVtfXpvLBfZTByi8NNOm9UTO4Nrmp3mO7myO9MDcGhzWFC/uiYa14LE+iJlEMDgqqX4le6PRsQviDaC7sjTh+AEKiv7EX0+0++4xnGVNwfz2a+/eTBae30QeQa9vG/7xrTzsIibv5y3fR2+iDyfPzPO6Z6FGcNM0L6L9sW/3olUVtrruzrN9o0maXuRWersdxRbzTQNUR3U9zjOIHabXYGYtWdjJC3BV31meoDvdF2vL2xH/JHq58O9ARaCOvmhz1VD+ENGZ936r3m46j3Gs9jldf4mfWpA3QGe4bKu3pin/eDfcbvQ5W3w2RT5Y0q59X6ekzbASoHzPudLqoGBkx1lTHqphvVA8ZVNgOqoD0Qf9rktl7zg1ysuolkoMvYvtDB2xsds6/TOP5Ar0Cf5g+cpxPR1W+WLBGgd/XHtLewmAjeqJ7mcvaDeIOjrTy0sBgH/c1j20wHfB2R9YMWk86McPw61PjfBCtrVpvqpJISQ1letNJkI89ZZCyXj7BxJSPlJ64K5iw6J7IIdnhdcWLT2a7UWTg8Bab61ILzhv5Pz1mDJI9UJpXJyDuH6UqOZxbpznxTfbIjkzSXUXl1ReZ5hlQREjIrMozncX3mKkN5lruIgmHKozfkG8M+T3BFjlHFc32WUVXNISmszYiqZK7PNH6fovtNnZLmednZcdVNN87NMX5niz0yRUnxX5bKcmTsI6Io5xVM7mUtu8TYocMNqdnRPtNnGbenFsnIMdYBnq1I+RlgHxHqblOQCyxFN4vJ493njV8Q7HRSlD5zhLksZgCl541tMx3IWxoRirGYdGaE43dSPv5OQ1GZNw9p+bKoOlBODvZbbjbazJqHcsE1kQWnig153lJsl77FYCOvuAplwzuQMouQSpdhv+VrSPbE10vZ02eRdeX3cOQuwZ41n4yL/x+uwjUJtSFJMvMu+Qme7GVIihPFkUbRio+TPfu6IRuHO4tlF/4Ud3IJkuzAmVTA0gt+iDu5OOExny5kSeG9q37CrLQVyJKChESWu4SPrPmdyXZu6hI+seh/KU9ewOyURXx68bcpS5lvsPlI2Tu4vegGStwFXJi1lh8u/ZJhDeDc5AI+Vn7tkAKngswny69jaZrRYbsoex6fn3clczw5LE8t4p5lt5LjjIrAfHHBxazPLBlyQx2SwhfmXciyNLMTe7r4/KJFXJKbi0uWSVIUbi0p4c6ysikbT7y8d14S75jtotgjsyHXzvfWpiYkbpDskrjrAgezsmVyUyWuW2lnWcnkqnHOWqYwZ40NT7pEVrHMmmudBoGXsovt5CxWcKZJZM1TmHPVTMihdPqQbAr2Oy5ByvCAIkOaB/u7LkZyWCqqFpPHe8+fzdpZ6VM9jJOSlezg358Ynzq2hUVM7noUMsqnehQnJ3sB3PXYVI/irGFSxV0mCmvxuoWFhcXZwdki7jJRWPdHCwsLi7OHU71HzphXrMFnXoV9x031I1M6iEAA9eWX0WvrkFJTsV1xOXKeMWwwfGQP+rMPgRoGhxPl5vdiKzHmj9P9faj/+TGipQqcSSgX34Vt4QUTflyJoIb6aT38d/y91aQVnU/OHOMspRCCmgO/o7X2aWz2FOas+hwZuYnNLgL09lVxvPIf9A3UIksKGekLWTD3TlyuLJPtsbonqG/bQnpyOcvm3InDnngOurHoD/fyn7r7afHXsTb7Yi7Kv27snU6BgBbmH/XbOTrQwpr0WdxStCpmnr69Pc081nQQp2zjnSXLKfdMTqhao8/LP2or6VfD3FBYyrqs2OlHjvf381BdHZoQ3FpSwuK0tEkZz0TyanOQl5tC5Ltl3jHbTZbLeJ7DmuCZKpXjXToLs2Sunm3DNiI9gi4Eb1ZoVLVpFGTInD/fhmMSQys1VVCzT6WvQyezUKF0sTJpKRtEWODbqqK26DjKFFzrJq8vC4szmV5fkA3ffwVvaPquobt0fjZ/fv+5Uz0MizONF78NW38aEVFBGvyLfy39yVEwZ8SU42xfjuQEXH4b3PBTK4/faWLGzPjFm84h+Nf7oHWYUIui4PjQB5EG0zlozfWof/+FqQ3Hh7+KlBrNjRf8w8eh3yjWYbvx8yjzpu6ifPSl/6K/dedQuXjVJ8lfFFVCqtz7SxqO/m3YHhLrrv0XSSnxr20IBDp59qXbCKtGYZDUlDlcdenfDWF4+yvvZ/vh6LksyFrLtef9KoEjio//t/P9VPQfHCp/YN6XubLolgnv5wT/ffDfvNR+ZKh8V+l6Pjb7YoPN0f52PrjzUbRBFdUUm4MHz30XGY6JXZ/hU1XeufVlukIRFVEJ+MWaDazMMDrhrYEAd27dil+LXIAdssxf1q+n1DN9czm+0BjkO3ui37OyZIU/X5Rm+I79fneIV+uiN5UryxXet9wYOvn8/jCbjkRVy5YUK7zzvMkLr9z7YoiWquiYylfamH/O5KxN6HsoRPBQtC/3+TaSrziz10FYM36JYc34xcf8rz9N6HRkYj9F3rm2mO+/bcXYhhYW8bDvX/Do6Dmvpw1LboG3/3mqRzEjmNbpHCaKtDiTp4u+PqPTB6BpaMeiM4X6rs0x9w0f3jOsnQ6T0weg7X85rnFMBiFfm8HpA+isfsZQbq15csRegpbqkXUnp6llk8npA+jrr6Sn96ihrqLB2H9z5w58gXYmkiZfncHpA9jY+vSE9jGcoBbmlXbjcT7TcsBk92JbxZDTB9CvhtjSWTPh49ne1T7k9EFEDPG5lgaT3WttbUNOH0BI13l55G9hmvF8gzElRs2AxrE+45vDzQ0jyvXmt/V7a41S1YcaNEKTpKKpqYKWauMYmo5NjlS2CAuCh419BfdNc1luC4tpiK6LGeH0ATy6u3Gqh2BxJvHK96Z6BPFx/LmpHsFZw4xw/HrDobGNAJxOkM2HJCVHZz2ktAzTdgA5dVhYnDMJiDHlnGIOdTxdKHYPsuIy1NndRtVGuzPdtJ8zKc9UdzJihXNGkHE6jecuaYStTXFht03sDFOKPQ1FMkYkZzgm73OwyQqpduOsXbbDHL6a5UiKq+5UyXSYBYWyHS5TXZbD/HIkVt10InNEWKcMZDiMv7t058nLEBF4GY7bAbZJypcuyxFNqOE4kyYpPEUBacQEspxshcJYWCSKPIPCo5Ock3Txsjg7STUrwk9LYjxnWUwOM8LxixfJ6US+wKiIJRUUIM+bN1RW1l4M9hGhUu5klPnLh7WThLziSqON3Y39XKM66OlEsXsoWvFROKFI6UilaLkx/HXe6i8bUke4PIXkl12fUD8FeRsoyBu5llFi4bx3k+Q2OpGrF3wUhz110EJmzYKPYbdNrPOTYk/j7WUfGkrlkGrP4G1lkxe2oEgyn5xz6dCaPrds5+NzLjbZ3ViwiAXJUcf7guwyzs2ceLnwZemZXJ1fNFQu8yRzS0mZye7i3FzWZkbXGC5LS+Oqgul9wb9rrpvsYY7c7XPc5LqNDz13LrVjH7xK2WW4Y6k5zPHq5XZOCELKElyzwo48SWsFJFliwXr70FIExQbzz52c0EtJlki+yh69StvBc+WZHeZpYTFZnDt7ZqQL+e0dia/Lt7AYlbf/hZgTGdMKCa69Z6oHcdYwY9b47dixg+AP/mDcML8E583XmOz1nh70ikqk3ByUUvPDuBA64R2bERUHkJetxb40dq47vb0O7eArSDllKAvPR1KmXgsn6G0h0FdLcvYyFLvZyVLDXlqqn8TlySer8KKEpPGH091zmFDYixA6nqR8UpJjOzVh1Udb9z7SkstIdk9eOoM2fxMt/noWpK3AqZhnvCaajuAAFd42lqQUkmKP3Z8uBAd6W3AqNhakxBZcmSgqB/roC4dYnp6FcpLP9HBvL5oQLElLG/dnfzoJaoID3Sp5bpliT+w33X1BQXWvzux0mRRH7GPyhwQNXTr5aTIp7sk/7qBP0N+pk5YrY48xCzmRaP0CrVXHViwju6b/Z3qqWGv8EsNa4xc/W4638YWH9tHcFw0zz/bY0XUNl8NOZ38QJLDLMgIIazqKLJHpcaDqGmEVuv0qEpCXYiegCnxBlbAOhakO+kMaAwENjcijdpbHjqrrSIA3qCNJghP52SXAoRARq5Iklhelce971uFxWS93LCYYIeCZL0NHBbjTIK0UvO1Q/Ro4U0BxRoRVitZBZwX0NYAWApsTQl7InAN9jaAGIHM2tB6EkA+K18Gs9dBdCxUvQMgPJeuheAXU7YCe2ki7jlQQGmgBKDkPGt+M2Cl2SM6Dcz4Enumfd3i6cNaoesYkwxy2qQ0MoG3fAbqO7LAjiouRRoR/SpKMZLMjXG6Ez4cIh5FGzgICck4p8iXvOeVhqv3NqH2NOPOWItliOxGqvxNf624kyU5SwRqUUaa9gwON+Hur8WQtibldC/vQ9TDOpPxRH/yF0Oju3I/dkUpK6uyYNhnpi9B1lc6u/QgRW52p39dEv7cBCRth1RfTJl4qut6kZaCKNQU34I6hDJrrLiTNkcmmlmdId2axJuvCmMcX1lX29R0lz5lF8SiOqCZ09vfWkm5PosxjDoUVQlDtbafF38s8T+6oY9aETsVAJ1nOpEl3/OYkp45p82ZHBy+0tLAyPZ1Sj4fUGN/p6YZTkch3y7QFdPLcMvYYIVmpTokVuScPf3I7JObljx0i1duvM+AT5GfLKIq5r4Bf0N2lIUkSDqdEZlbsoAhnkoQzafT+hBAMtOjINglPzqkFVigpEkrK5Id/CV2gH+5BhHWUpRlItjMqIMTCgmVF6aS57bT1B9FExPkKhDT8YR1vKEhxupNuv8ZAUCXJISNLMg67QkjVCIR1kpwKNhkUCUKajk2WUBQJt0NCksHjiNjqOugCfGGVdLeDQFhD0wWKHNFAtCmQ7FIIa1CU7qTbq9LlDdPWH6TccvwsJhqhQ3o5HHw8EhXmqYJQH9g9kJQTccCa9kB3DSy8ERa/Bao3gbcNvIcjjl7ZBnCkwIFHQQuDKwX8PbDngYhj586CtCQoXQftRyMhpitvh8xySMqM2NVshcZd0NsEgedgwY0RB1Sz1q6fTmbMjF88qp7q3r1ozz1v3Gi3Y//gB5BTIgm49XCQ8K+/DeHhwhIStrs+iZI38cnO+/bcR9+O34LQkd2Z5Fz3S+yZRmert/IZmrZ8O/JGBJBkJyVX/BhPgdGhP/zcB/F2DgqNSDLzLv4/0grXD21vqniU47t+MFTOLb2GRev/19BGKNjDGxs/xkBfFQBFpdexfN03TOP2Bzp4dfNHGfDWAzCn7FZWr/jS0Pbdx+5l9zHjDOy8khu4cMV/x3VehvPLN95LY//hyGEh8/5VP2NulnEWtrLvEN/Y/SFUEblAZDsL+NE5/8ClRBdBNfhb+K99/0trsBMJiXeX3MTHym83tNMVGuDje39Lra8NgLfkn8NXF7xtaLtXDfKBnfdR5+8aHA98df613FC43NBOva+Xu7b/k5Ae+cwKXCk8ct6dCR/7RPGhN97gcF/fUFkBvrNyJRfkTK5Deqrce9TH3yv8CCDHJfPT9akUjTLzd6q8vifMrkOR709yksRNVzhIS446N7VVKm9sDqMPe89RUCRz4eWOhNYIaSHB4X8H8bZGrq0Zs2XmXeuY1jOwwhsm+Osj4BucjrBLOD6yADlr8mfXR2LN+CWGNeMXH8/sb+Jjf9891cMYkw9eMIv/d8PSqR6GxZnCQBv8ZElkBm86c80PYP1Hp3oUM4KzQtUzXrSXYqhuhsNoL78StdnywginD0CgvfDoxI8n0Evfzj9E3rYAur+Lvl33GnvWNVq3/2zI6YvUBWnb+UuDXV/LrqjTFzGidscPDTZV+4xpKtrqniUc7DXU1VY+NOT0ATTWPU13537T2I9V/H3I6QOorHmE3r5KAHyBTvYc/5Npn+P1T9Lec8hUfzKOdW4bcvoABDqPHfm+ye6Px34w5PQBdASbeanxcYPNX+seozXYOdiO4G/1j9MSMKqz/rNh05DTB/BEy5sc7Y+qZP6ned+Q0xdpB35a8SKqblRX/MHRV4ecPoDmQD+PNpjVP08HDT6fwemDSFadXx47NiXjiZc2v8YDg04fQHtA5/4K/6T01efVh5w+gAGfYNfBaFkIwe43jU4fQHOjTmN9YvmO2g9rQ04fQHeVTm/dROVMmhzCm1qjTh9AWKA+a6kLWpw5fPrBPVM9hLi4d3PtVA/B4kzixW9Of6cP4EXzBITF5DAjHD+nFOcMgGaWegcQ/dGHYtHbFdvGa05hcKrogZ7BhJlRNJ8x3YHQw2gh40M7gOozOixBr/khTAuOeNjXAiabUKDb2I7fnG4hGCMFgz9gTmfhH7QLhLoQIva5TjSdQ5fffFz+sPl89IbNn1tb0Lhve8h4rDqCrnCPoa4jxrluG3YeO0Lm74FPDxPUjaEIXSGzg1Ln7zXVnQ5a/LGdpY6A+fswnegKClOK147g5DhIvhinyOuPOme6DsGR74MG8fsSi4oIec32oYFpHlnRbX4wEH3hGIYWFjOT8AxJ52BhMaH01o9tMx2YCc7pGcKMcPyCozgZJgoLY1Yra6IqWcpas0IjgLJs4iOL7OmzsGcvMtQlzTWK0cg2Fyml5jGlzr7aUM4svRxJHpHWoORSQzkt25j01eZIw5NWZqgrKL2G4QpPDmcG2bnmpPSzSozjdLtyyclaHek3ZS6ZqfNM+7idmRRmxxbKGY0VeVchj0jXsCzvcpPdJfk3muouL7jJUL4m90JDeZa7iIXJxrDaq3NXDSmEAmQ7UliXMXeofEXuIsN2gHMzyvHYjBr+txQZ11hKwO3FU5N0d3VmZkzBl+mu6jk/TWFWsvGlzpWF5vQVE0FupkR6qvEczS+L9q0oEiWzzC+YbDYoKk3sMpk1Tzkhvhtp2wEZ5dNbol0+x7ywXlk3delrLCwmmvXlM0PVM9szvdPwWMwwzv3YVI8gPvKXj21jMSHMnDV+3/8Z7DSHEZ5Y3wcgNI3wo48hamoiFW4XyvnnY1u1yrCPenAn2ouPQTgEig157UXYLzSrg04Emr+b/n33o/bW4y67GM98c3oFPeynY/9f6K99BSSF9Hk3krnoHUiy8WHR23WEmje+i+rvIqP0UkrWfM6wbkjXVY688Q162nbhTilh0bnfwhVDvKS9ZRsNNU9gd6RQPu8OPCmxFTubWjZRU/cULmcmC+bdiScp6lj7g53sq7yftq59CKGTlbaAZXPuINVTkvA5qu89xGOHv8tAuJtluZdzw/zPxlwP9VD173m15Ulcips753yaVVkbTDYvtG3lxfat5LuyubP4LeQ4zTf7rZ2HebJlB+l2D+8quZhit/EBd2d3Lb+sfIWesI/zMmfziTmXkWQz34z/VrOLR5oO4FLsfHru+ZyXNfHpHOKlpr+fz+7eTWcwiFtReOesWdxZXo49Rl7L6URnQOcfVX5afBqXFTq5bJIcPwCvT7DrcJgBr2DuLIV5s4wvHFRVcOSASkuThqZCarrEwiV2MkYReDkZfY0abQc0ZBvkr7CRlD29PwcAdV8X6mstoAuUc3Kwnze6sNFkYq3xSwxrjV98CCG45icbOdo28dE9E0VOioM3vno58jS/blvMMHbdB098GkwxNqMg203RaokjRXLzZc+LLGVq3j9K/wrMOg/e+yRM43Xw04lTvUfOGMfPurFZWFhYnPlYjl9iWPdHCwsLi7OHsyadgymH3wk+826czsgsgQgECD3wD+gYtj4tORnnx41T3eHXX0J/42VQw+B0Y7v6VkMCdwDh60Xd+DdE83GkokXYLroLyeVJeNxCDdD9+k/xV74ACFwl55Nx4ZeRR0nXcCp0t+6g9tC9qOEBCmffTOHcW002oVAvR/f/gu6OfaRnLWXhsk/jcKYZbAYG6nl188fwByPr9TIzlnHZhX+YNFXCTbUPsKv5KTyODK6c/RFmpS8bVztdoV5+WfU3DvQfZ2XaIj45+y5SbIl/Zj0hH7+seoUDvU0sTyviE3MuJdUeVQ8VQnB/3R4ebtyPVw1R4ErhI7PP5YLsMkM7feEgv6rYyd7eVpam5vBfc9eS4ZgclUQhBN85eJBXWltRJInbZ83ifXPmTEpf8RLSBH883s3WNh+zku18dEEmxR6jVHltv8rvjvho9OlcmOfgvfPdkbxWgwRUwT8OhTnQrlOWJnPHEjuZk5Snz+8T7NkRpqtDJ69AZsUaO/ZR8gaOxUCrTv22MGGvIHuhQsEq26T8fkRIELx/AFGrgkPCfq0b2+rxzZqGn25A29MJSCjnZGG/oshkozf3o75cg+gPoSzNRTm/eFqrlVpYDOcdv9vKG9XdYxtOEeluOy987mJyUiYv8sHiLOXA4/Dw+4lIv00zFlwPtz8w1aM4a5j58QQ/vW/o39CTTxqdPoCBAUIPPjhU1A7uRN/yXMTpAwj6UZ+4H9FvFOYIP/NL9EMbEd3N6AdeRn1pFMdzDHrf/DW+I48jwl5E2Ie/6gW6N/9g7B0TJOjv4MDmz9Hbvhtvz3GO77qHjsbXTHYHdn6Xhpr/4B2opbH2Kfbv/JZhuxCClzZ9eMjpA+jq3s+OPd+Z8DED7Gp6mqeP/4yWgQoqu7bz592fwh/uH1dbdx/9JU+3baTO38wTLS/zg+Pj+8y+c/Rpnm45QJ2/iydb9vP9o88atv+7+TC/qdpGe9CLTwtT6e3iqweepdZnfKC458jrPNl8nHpfH8+0VPKdw5vHNZ54+GNlJc82NxPUdXyaxh+rqnhz5G/hNPPnim4erO6lzhtmU6uPr+1sZXiEgSYEX97ez9a2MLUDGvdX+vl7pVGF5b79YV6o1mgeELzeqPHzHZO3APz1jSFqqzT6+wQVRzV2vjG+UBctJDjyRJC+eh1/l6B+q0r7ocm52YYeHEBUqqACPkH4ER96R+J9qTs70LZ3QFhAWEfb0o52yPh9FmGN0N8PoFf1INp9qK/UoO1snqAjsbCYXH73WuW0dvoAevxhrv/5pqkehsWZhr8bHn4P09LpAzj6FBx7fmw7iwlhRjh+mUqcb7+qa2JWi8ao+qNedSSmjVZ7PGqv64jafYbtevX48v/467aY6gIx6k6VnrYd6JpRlrCreavJrr1l60nLXl8joZBZQbO5ZXJuRkc7jeciqPmo6dmbcDua0Hmj2/iZbe0a32e2rbPKUN7aZSy/3mmW29aE4M2uhhF2RtXRbZ2NTFZo9Wttbaa6p5uaJqWveNnW7jOUa71hmv1RddTaAY0WvzHmf1ub0dna02q8UR3r0vGFJ/4caqqgrcU4lqaG8d0kB1p0RvwU6amdnBuuXm1OfKsdTtw51vaZH4jVPcbrgN7YD35jf3rF9H6QtrA4wV+31kz1EOKirX8UeWELi/FSM/HPnBPOq9+d6hGcNcwIx69r5FPUaGRkxK5Piob7SVmxBQvknPyojSwjZRoVQqWs8SV3t2eaw+3sGbNjWJ4anlRzm0kx6pJTy09adruykSRzBLBnHKIt8ZDrMY5RQiLXU5ZwO4okU+o2fmazk8b3mZV5jAqHs5OM5fKk2N+zck/GiLIxhLbMkz5pYXHlyebQ4SVpaTEsTx9lyUZBnBS7TJYzKliU71ZwjRC7LB+h8lmcarxEZbslXJMQoK7YJJJTjJ9NWvr4Lo+uDIkRwrC4MyfnUitlmNuVChNXEJUK3KY6uTDJWM5yw4hE9lKO0cbCYrqyojh9qocQFy77jHgss5hJ5C4a22aqmXvlVI/grGHmX2GGSR/bb7whpiqQ8u67ov+vvRAKjOqL8tK1yHlGJ8F21UcheVDtMS0P2+UfYjykr/8USkrUIZHdWaRf8KVxtXUykjPmM2vJh5BkByCRXXQJhXNuMtktXf1V3EkRmX9XUj5LV3/NsF1RXJyz+n8NdbLs5IJzfzThYwa4oPSdzM86DwC77OLaeZ8ia5wO29fnf5RcR+QzK3Ll8aV54/vMvrLgGvKcqQDkO1P54vyrDNvvKF3FmvRhnykS7yheztoM47i/uPA8ClwRhyzP6eErC88b13ji4QuLFpHrjM6ML05N5eaSyXHW4+UjCzKYmxL5fabZZb60NBunEr3kJNkkvrgsmWRb5De7ME3h/QuMjsR7ltkpSI5sT3fCh1fZkSfJeT7nfDvuwe6TUyTWrLeffIdRcKbIzLrAjjy4e2qJTMGqyVlObX+HB4YFRMhL7NjmJC4Hb7+yEClzWEO5LmwX5RtspBQntqtngyPiWMpladg2jO+3amFxuvnlHatx2ab/etSf3LZyqodgcaaRNQeWmDUfpg2uNLjs61M9irOGGaXqGaysg4efG6ofnsrhBEII1Lo69OPHkYuLsS9cGLNNfaAP0dOJlJWH7I791lroOgx0QUomknRqPnK4rwmEji218JTbOhlqeABdC+FwjZ6zSAidgL8NlzsHSYo9O6BpITo6dqPYksjOGp/YSiL0BztxKG6ctlObQdCETnuwi1xnJvIpnOdIOwPkOlNGdTQ6gl5UoeNRHKTYY4cj60LQFvSS40xCmcTP/QQ1Xi9uWSbPbZ7BmSra/CrpDgWHEvs8BjVBX1gnZ+T03yBCCLoCgjSnZBB+mQx0XeD3CZI80inPzmphgRYCh2dyxyyEQG/WkFIl5ORTyxeodwVAkpAzRg+vF2ENAhpSyuTkG7NUPRPDUvVMjJ21nRxvGUAgaO33U9nmZVZmMnNy3fz2lSoUWaIgw8XszCRQFPbUdNHmC5DhsrO0OJ223iCF6W4GAhrdgTClGS4Cmk5hipvddZ3oCOyyTI9fZUFBKrIk0dEXoCDNycaKTtx2heuWF3De7Bwaur1sOd5BhsfOspIMrl5SYIklWUwevh7Y908QgLcDWvbBvCtgzmXQWQkdxyG1APIWQ1cVSDbwZEDDHmjdD2mlkFkaSYWWMQt8gzoCjlTobQBdBWcK+DsjCdlnXQjeNkjOAS0MsgJdlVC/G+zOiO2Cq6HAyuGXCGdVOodYyp4jnb/gK6/A9sGbYGYmtpveipJtTk4c3rkJcWQvUm4htvOvRkoyqz/qdfsRnY1IZSuQM6Y2Gbauq/TUv8ZA+17s7mwyZ12BM9kY2qiG+mmrf4Hejn0ILUxOyeVkF186rhuJEDotba/j9TVTkHc+nqTJO34hBMc6t9Hlb2Bh9vlkjAjZBFD1MI/V/oVmXy1XF93GgvTxXSiaA1187+jDhHSNL8y7ibnJ5uM61NfMls4KwrrG6oxSzs0oj3kOn205yuaOGs7NLOGGgkVTfsM+3t/P3u5uFqWljRrmqQvBGx3dtAQCbMjOJM89OSqjAId7ghzsCbA8w8X8tKlXqRNCUNuk0+8VlBXJpHgmzxHXVUF3VSQfYOZsBZtrfN+NcJOOWq9jK5GxF86sAA29vhu9pRd5VhZybkrc+1mOX2JYjl/83Le1mm8/eZiQPv2ee1wK/OrOtVy+yJx718LilGjcDY9+GHoaQPMT8fxGojCUZ09SQNhAVkHXjPbOVPDkQ199xNFDAT0wrBkX2D0Q6BzWtgTuLLA5IDgAaSURp9HXDu7siKJnybqJPuozlrPG8dvy9o+Muv2E8xf8+wPQ2Gjabr/9ncjDwt5C//gNorE6aqDYcLzvC0jp0Vky9ZU/o+1+JlKQFWxv/RJKuTER/OlCCJ2jL/0XA21RsRJJtjHv0p+RmrcGgJC/k50vvoeQv92wb27pNSxabwzdjIc3dn6DuoaImqUsO7n4/F+SnTk5b2UeOng3u5qfAsAmO/nA6p9Tlr5yaLsuND7x+lvpCkWP7YPzvsIVRTcn1E+dr513bP+hoe7nyz7Eusx5Q+V/NuzgZxUvGWxuzF/OVxdea6j7+oHneaW9cqh8bkYJP1l5Q0LjmUiebGzk+4cODZU/Pm8e7yorM9ndvf8IL7REzqNTlvnpmmUsTU+d8PE8XNPLLw5HxUE+vySLt5ROfD+J8NzmEBV1EZEVmwJvvdxJ/iQkVtc1wcGHg/jaI9dWexIsvc2FIzkx58+/XWXg6ajYTfK1dtznzIwMPOqmCtSNUcEs+1tXoCw1v9CJheX4JYbl+MXHB/+6nRcPm0Wwphufu3Ien7p8/lQPw+JM4fBT8M93TfUoxubm38OKd0z1KGYEp3qPnBGvkF3xDjOG0wcQfjH6IC98XqPTB6CpaHtfj9r4+9H2RENK0TW0Nx+Pd7gTTn/bboPTByB0lZZDfxsqN1c/YXL6ANrqniPk7zTVn4wBb+OQ0weg60GOVfw9wVHHR7e/ecjpA1D1IBtr7jfY7OzYZHD6AB6uSTxVw/eOPmyqu+f4o4byX2rMSqhPtuyjLdA3VO4PB3l1mNMH8EZ3PR1Bb8Jjmij+WmVUHr2vuhp9xEudRp9/yOkDCOo6D9YalUgnivsqek5aPt309OlDTh+AqsGeI2ZFzAnpq1ofcvoAwj5oO5R4X97XjAqn3o3jSy9xuhGajvq68fuobqkcxdrC4vQwE5w+gJ+/eHxsIwuLeHnqc1M9gvh44b+negRnDTPC8bPLp/iWWxsmpa6PIquuqUabkTOh2uQ8JMaD0GI/8Ak9Wq/ro0m4C3SR2Nh13dyfNmr7p4YmzH2pI/oKxxiPmuAxAYRj7KMKbYSN+fshAFVEpf41occMlAgLPUbt6SE84vuq6uYxhnTz+CYr5Ck8ot2pDq3SYnw0mjY5Y9JjHGuMr9XYjNxnmqZgMiEEjPyuxfoALCwsTEzDKFSLmYw+dc+uCTFTxnkGMCMcv/54nY5R0jnYLrl46H8pORUyR6R0kCTkZedGi5505IXnG0yUVcZQv9NJav5a3Okj00JI5M6/baiUX3YDit28TjEj71xcSYmtGUhNKSMvd320J0lhbvnbE2ojXrKTSlmQtSHaFzIbSm8z2JyTcwlJijFdwXXFiYcEfHbOW011Hyu/zlC+rXiNyeaCrLkUutOHyukON6vSjGsDFyRnU+CKfx3TRHNbqVGp9pbSUpQRaw7Lkz2sy0wfKisS3FoSX/hdorytLG1EeWrDPLPSZYrzopc7SYLl8ycnbDKjXMGZGj33igNyFicuuuJebxyf+9yZEeYp2RSU1cbvo7Ju1hSNxsIiwsqSqU1vEy+3n1M6tpGFRbxc9j9TPYL4uOCzUz2Cs4YZs8Zv69atiJ/81bTNJO5y/9/hROJqhx3lhhuxzTU6TULTCL/0OKL6KKRnY7/yZuTMHKONrqEf2YzobECevQa5KLY66OlCDQ3QUfEE/e27sLuyyJ5zI8nZSw02AW8TTZWP0tu+F11o5BRfQvG825GVxGXpNS1Ibf0zeH1NFBVcSmbG5OWBUfUQu5ufodPfwJKcSyhJW2Ky6Q/38NeKn9Dmb+KKwpu4KP/6cfW1s7uCe44/hio0PlF+HZfmmtctvtZ+jFfbjxHSVdZnlXN13hIcI2adVV3nz7U7eLOrgZXpBXy4/Bzs8qkpKp4qr7e3s7unh8WpqVycmxtTbCao6TzX3EqzP8jFuVksTJs8Z3VTq5eD3UGWZbg4P2/q872pquBojUbfgGBuqULOJOXWAwj7BR2HVTQVshcquFLH11fwqEa4TsdeIuNcOLXfr0QQQqAfbomIu5RloczOGXunQaw1folhrfGLn8//czeP7G6a6mGMymevmMunr1gw1cOwONPY9Xd4/msQ6Dn1tiQFbEkQ7j+JjQ1MEVYKKLZI+Is9GcJe0MMgO+DGn8KqO059bGcJp1XcRZKkJCGEb7ydjZfhN7YhZc8NC3FeeGFMe30wzEiSRpdk17Qwuq5iszlHTa8ghB5X6oV47IQQCKEjT4BzoGkhFCW2lHqkH4Esn/pDbTzHpevahByTLnSkwazXo31mutBPKUXDCVRdxTZG+LCm68gn+f6cQAiBLgTKGOdbF2LS8s8NR9V1bBPw2U831MHP41TPoRAibvXVk9nG086Ja+tUq73ONGaq4zcd7o8WYxMMhgmEVGyKgk2RCauRa4uma9gUGV1ErjdOm42uAS8ZHjeqLlA1DbuiEAqHcdjt2BQFXdcRQhBQVVx2W+QeL8kEVA2XLXKP8YXCuOw2HHaFsKqhyDKaLgCBpkfusYok43LZkCc5XY3FWU6gD5DAmRxJr6CFI6H5Nmck/YJsA0mOOGdaCGwnVL+liK0kRZZCKYN2EFkGJQHhIDjccGLJi2wbDN+UIsutHM7IthNLAWQ5YoOAcUxOnM2c6j0yrtghSZI2APcCyUCpJEkrgI8IIT4+3o4TxZTKYesRgluPwMJynG+9AgC9q4vwX/4K6rA3DWVlON76FqTB5NZ6wE/4V98cWsMXAigoxXH7x5EGH5iFGkZ96Q/ohzdBUhq2i9+NsmADI1EbdhJ45fvofY3Yys7HfcX/IDnNMyjtz32BYN1mABx5y8i54bdI43CWmg/eR+Pe3wACJJny8/6XrLIrh7ZX7fs19Uf/DkJFVlzMXv4JiuYlHqJZ3/gSew/8hECwm1nFV7N6xVdMjmZd62Ze2/0NwuoAsmRj1YKPsGLuuxPuK6AO8Mihb3Og7VUAHIqLy8o/wMVldw3ZhPUQ9x77PptbnyPNnsG7536W9bmXJ9zXgb46Prf/j/SrfhySjc/PeytvKTjXYNMX9vOx3X+n2teJBFyZu5hvLr4xZnv/c/AFXmqrQADzk7O5d80t2EZ8rju7mvnh0W00+vs5P7uYry+6gBT7xOc/e7y+np8fO0ZI13HKMp9ZuJAbi4omvJ/TTcuAxjc2hegfjPbOdsM3LnSS5U7MudV0wcbtYY5Ua7iccP4qO/PLYl/+jh1SObA3jK7B3IU2VqyxDTlvQhcc3hqm8aiGzQHzz7FTtMDYjhYWHH4siLctco1JK5VZcIMDyXqoOyOZDvdHi7HZWtHBu+59Y6qHcVJykh1s/erl2JUz7+WdxRRyz5xozr3piD0ZPrMPPFlTPZKzgnivLj8BrgY6AYQQe4GLJmtQCXEkqtAZ/ue/jE4fQE0N2qbNUZsHf2MWbmmuQ9vx2lBR2/UU+sFXI282BrpQn/0lwttj2EVoIfzPfh29tx6Ejlq9icDrvzENb+DwY0NOH0CodT+923+b8GHqapDGvb9mKJ+K0Kl+/ZuIQbGajoZXqT/y16HpdV0LULH7Rwz0HEuon0Cgkzd3fQN/oB0hVGrqn+J45T8MNqHwAK/s/CphdSDSl1DZeeRXtHcfTPi4Xqy6lwNtrwwelyCk+Xm24pdUd0dVTJ+u/wevtTyFJlS6Qu388vA36AklplQK8MUDf6Zf9UeOQaj84Nij9IaNL+i/c+Rpqn2RtgXwfNshXmo9YmrrtfYqXhx0+gCODXTww2MbDTYhXeN/Dr5Gvb8PHcGmjnp+X7Ur4XGPRZ3Xy4+OHBkSbwnqOvccOkSj77RPPkw4P3ojPOT0AXT44dc7Exca2n9M41Clhq6Dzw8vvR5mwGeOdujq1Nn1ZphQMHIpOXJApb4mqqrScESj/pCGrkHIDwc2hvH1GYVL6raEh5w+gN46nZa91sL1M5jpe3+0GOLdf5reTh9A+0CIb/w78fuohcWovPTt6e30AYQH4M9Tp6NxthH3ayUhRP2IqtOmMZfninN90MBAzGq9uTla6Iot6azXRiWURUuFcaOmItpqjPa9jYgR8dJaq/mCHag3pwcINif+8D/QdchcKTTC/sgPuq8r9s2ir/NAQv309B4zqXp2oTYCwAABAABJREFUjnDouvurYqp8tvckfsNq6I29T31ftL6i32ijijC1A4lJXnvVAD1hY7oFHUGlt9lQd7i/xbTvjp4aU93mDnPdgd5WQ7nR309POGioO9g38RfgQ729pjoBHO7rMxvPMFq9ZuesqifxdcmtHUbnTBfQ3mVWmuxsj1HXMcyJaxuxXZjr+pvMbfQ2WKqWZzJTeX+0iA91hvwEXztmTstkYTFu9j801SOIj57aqR7BWUO8jl/9YDiLkCTJLknSF4DDkzguA62BOGcuUmMrB8rFxdFCTmwVQ3n24qH/pZFCLoodKd8oECOnlSAlZRvqbIXmBO/usktMda6S9aa6sUjOWgqMCBWTbNiTIqIJadkrYuwlkZa9MqF+MjIWoyhOQ11OtvG4MlPnYlNcjCQvM7G+AEOi9tHqF6YZbRyyk9kpiYnNeGwusuzGMFxFklmQbAyHXJFWzEg2ZI1UVIXLcuea6tZkGNsqcaeS5XAb208foSg7ASxLTx/5zUAClqbNDBW7k1GUYg6PXJCZeMhkYa7xUifLkJdlvvzl5J28LqPAuF2SIH3EPqkl5jYyZlmhW2cwU3p/tIgP+wwJtb5mSWIq3BYWJ2X1e6d6BPGRPX+qR3DWEO/TyEeB/wKKgEZg5WB56rnknKF/7be/E5xGp4WFC1DOj67Ps7/zo+aFpGXzUVZH0zcoq66NpG9wepAyi7Dd+Hkkt9FpkBQb7uu+j5yzEOxJ2Bdcg/PcD5uG55l/Pe45Vw8uhJVwFq8ndfUHEz5MWbEza92XhhbUSrKNORffMyS+klV4AeXL/gvZ5gZkbI40Fqz7f3jSZifUj9ORxnlrv0tKchl2ewpzZ99mSuVgtyVxxbof43ZmAhI2xc15S79EVlriP9zLZn+ANQU3oEgOZEnBY8/grQu/RGlaVLH0mqLbuKboNjy2FIqSyvjMku+SYk/cqfnp8g+S5Yh8jkmKk28uvB2PzejAfmXBNSxOKUAi4hjeUriKC7Pnmdo6L6uUmwsXo0gRSZqVaQV8Zt4FBhubLPPdZZeyICWLJMXONfmz+VC5+eXAqVKUlMR/L1lCss2GBKTYbPzvsmXku91j7jvd+dK5DrKGHUZxCnxstXP0HUZhyVyFFQttOB2Qnipx9QUOktzmB8H0DJlzzreT5JFwumDZKhvFpdF1m4XzFcpX2rA7ISlVYvlldtwpxsto6QY7qcWDdRJkzpPJXTYzUjFYjIvpe3+0GOKhj5rX6U83SjPcfO36xWMbWljEy0WfhbRpniIkKRve+/RUj+KsYcakc7BUyywsLCzOfGaqqudUYd0fLSwsLM4eTpeq589jVPcCO4QQ/x5v54kQbG6F+54w1Y/M4yeEIPTwI1BXB04nyi03Yys0hneGNj2LePPViLSsJwXbdbejzDKG7ukBH+oTP0R01CLlzsZ+4+eQnMa1hiLQR+jAYwhfJ7b5V2HLN+bVG2or7Kdn8z2EOo/iKjmPtHP+K640EcPx91TSXvE4gb467EnZZJVdS2q+8XMPB3upO3wfve27cKfOYtai95GUmnjiZFUNsGvv92hs2YQs2SgrvZGliz6EEiO8s7uvkuMNT2JT3CycdQtJruwYLZ6cg22v8nL1n+gPdlKevpKbF38dl814rvtCPbzY9Cj94R4uzL824VDPRHiyeR9PNO/DJdt496zzWJthPoe/rdzG440HCegaOU4Pn513Phuyy0x2Wzrq+VP1XpyywifnrmNRWuLnJx6q+vv58ZEj1Hm9zE9J4StLlpDjMn9e04mgJvjFwQFebQ4hSRJXFDr4wIIkku3G30ZIEzx8RGVfm0ZpqsydS+2kOo2zdf6QYHuVSr9fsKxUoTRrfClGdF1QdVyjp0snv0gxzPadQOiCxmMafR06mQUy+XPMl9GuSpWmHSqyXaL0AhvJueMbT7hJJ7hPRUqScK+1ISeNP1xNhHW0nf3oHWGUhUkoc8eXW1E73oVe0YWUnYSyKh/JdnaHsU6H+6PF2AghuPLHr1LRMX1FrzbMzuCBD0//mUmLGcaOv8CTnwVO50JXiSExwpOa2WDxW+Atv4ikmbCYdOKa8ZMk6ffAQuDEKtFbgWogC6gSQnxmsgYIkTeaW97+kVG3D3f+gvf+Ebq6DNsdH/0I0uD6v/Cbr6JvNE8p225+H8qcqDMR/NX7IDhMDMSVgvPjfxwqCqHjffDd6J2DQjCSQtJbf46teI2p7eYHb0brj4qIuEo2kH3N/416PCPx91Ry6Ln3IzSjUMjs879N5qzBVBa6yo5n34l/IKoxICtO1l79AO5k87q1k/HsS++kf6DaUJeTtZpLLjCqlnb3V/HEpvei6ZFxeVy53HLJP7Hb4n+g3Fz7D546/lNDXborny9fEH1eUnWVL21/F03+yOJfRbLxzZW/ZV7askQOKy7urd7Mn2q3GOq+t+RmLs6JhrF+bf9zvNpRZdr3O0uu4tLc6HrAbZ0NfH7vS0NlCXj4vFvJd0/sxa16YID3bNuGPuy37JZl/n3xxSTZpm+I4ce39HCox6iBUZ4s8aeLMgy57/53c4CjndFjS3XAL65yYVciNroQ/PbFIM2Doi8S8J6LHMzJS9zZen1jiNqq6JhWn2tn/iLjOTy0OUT9oajN3LU25qyOho93Vascf2qYQJIEK9/txJmSmIMUbtDp+XNw6F6tZElkfMyJpIzP+Qs+0IJ+NPrQa785B9tKc/qZk6HuakZ9Kip+JS/MwvH2iQ1Nm2kzftPh/mjN+I3Nqrufp9sXHttwillRnMq/PxE7R7GFRcLUvQF/umqqRzE22QvgE29O9ShmBKd6j4z3SWQ5cKkQ4hdCiF8AVxC50d0MTPo3KsOWwJqeEU4fgPpm9Mukb3sx5m7anqj6ptZWY3T6AAL96G1RZ0hr3hd1+gCERuig+eVuuKfO4PQBBOpfR4j437x0VD1lcvoA2o8/OvR/T9tOg9MHoGtBWmueibsfAK+3yeT0AbR37sLrazLUHa9/csjpA/AG2qhr3ZRQf9saHzHV9QRa6PQ1DJUP9uwYcvoANKHycrN59ncieLhxp6nu0abdhvLmzpqY+z5Yv9dQ/nPNPkNZAH8ZUTcRPNPUZHD6APy6zusd01fCuTOgm5w+gOoBwZHeaOqDLr8wOH0AfSHYP0x9s6FLH3L6IHKet1clLqoYCgnqqo37VRwxpmHQdUHDEaNN/SGjTdP2EakbBDTtTDydQ2CXanhBq3UKwtXje2MrelWD0wegbk9c9VXbabyW6Uc6Ed7E02ucYUzp/dEiPmaC0wewt2HmqzFbTCMeNWtPTEs6jkL70akexVlBvI5fBpHktCfwAJlCCA0weyQTzIB6ig8WrmHqEHLsGRDJ4Rr2f+wZK8nuHva/2SbWfrI9RridrGBS6DwJSoy+IvWeof9to9okFs41UtEzimQK9Yw1s+eweUx1J8OpxB6fQ4mea1cMm5GhoBOFWzEnV08ecU5so4TpJo94QeEZKSIEk5K8fbRZvSRlfOGFpwPHSYaWNGxGy67E/qW4hx2y02a2cJlP/ZjI8uBPcxi2Ee1ImLWhbA5j/4rDPB7bOKJupRg/RWm8Xx+7ZLraS85xhGiO/OAUCaxk01N6f7Q4s5gZ2qMWMwZXbLX7aYkjsedHi/ER7x37HmCPJEl/liTpL8Bu4IeSJHmA2FNoE0g4njjhQaT5IxQYZRnbuuiMqHL9u2LsJKGce2l0l/RcyBmxrit3NlJGfrSdnPnY5lwWbcKVhmPl7aamFU8uzqJzDHXJS99pCGUbi5y5N+NIyjfUyTY3+UveM1ROzVpGRr5xbYAzqYD8shvi7gfA5cqiqOAyU/2csltwOTMNdQtKbybZXTBUzstcSVFOYqkqrpj9IaQRX8M5GWtJcWZF+0lbzqrMqOpqmj2Ta4vekVA/8fKx2Rcbyg5Z4a5ZxmO6s3SlaT8ZiQ+UrzPUfWreOSjDPme3YuP9ZbHSbpwabykqImWE81fscnFO9uSsJ5wIUuwy1xebvZhLCuzMSokeS4pD4rJZRmdjdrrEwmGpGPLSZJaVRG3cdtgwP/EQV5tNYvHy6H6yDEtXGr08SZaYuyZaJ0kwd42xr1kX2A1Pb7IdCtckPh73uTakYfdBxzwZe4w1h/EgJSnYzhumhGuXsF2UnnA7totKI87eIMqGYiTX9A0nPk1M6f3RIj5WlMyM9DbvOrdkqodgcSZxhzmqalqy6CaIkU7LYuKJW9VTkqRC4C4i+YmSgQYhxMZJHNsQJ9YwBH/wB9O2keIuAOrhw2hbX0fKzcV+7TVIIx6K1a52tEf+CAEfLFqFY8NVSEnmNw3qnmfRj72BvPB8bMuvMG0XQqA17kR4O7HNOg/pJG9WfJUvEmh6E8/c63AWrIzjqI1oqp/exi2EfG3YHGmkFa7H7s4y2Agh6G7ZRnfbdjypc8kpuQxlPFMNQGPTaxyr+gc2m4eFc+8gJ3t1TLuw6qehbSs2xUVR7npkKfEH025/M9sb/02bt4qluVewssAcHaULnYPdO+gLd7Mq63ySbJO3CLjB182TzftIsjm4sWAFGTFmcg/0tnBfzU7aQl6WpObxgfJ1ZMaw6wkF+FvtftyKnbtmLcWpTM5Dsl/TeKy+nl1dXZyfk8NbiosNTud0ZUdbiAcqfdgUibeVuTgnN/aM88F2jTeaNBZmyqwvVpBHHJsQgpp2nT6/YH6BgjvGrFu8dHfq9HTr5ObLeJJjvxvr79Lpa9fJKJBJSjXbhH06TTtVFKdEwWoFZZwCKHpQEDqmISdJ2GfLCb0witleQyAi7jLHjZQyvu+i6AuiV/cg5SQhFya2RjAeZtoaP5ge90eLsfnT5iq+89RhtATFzE/86k5VA10BRgtC9zhkfvqOVVy5JH8UCwuLceLvhd9fAt3VgBRJnyA08HdGtitJIFTQ1UhUnD4YZWdPAVcGeFsG62Qiv4IRvwSbBzzZ0NsIqCA7IH1WpKz5IqEqig1Uv3FfSYGseXD5N2DRdZN8Es4cTpeq5weBTwPFwB5gPfA6YJ4amkxGXDVjOX1CCLDZICsLkZpqcvoAlIxsxCU3oB/Zh5SdD6PkO5NnLUdZcAHSKGIckiQheXJQchYgOUd/AFL7m7BnzsGeNR97+vjyqSg2N5mzriDQV4fNmYbNaX57KUkSnvR5yIoTT9rscTt9AAX5G5AkBVm2k5U5uoiK3eamvPDycfcDkOLMoTh1MeuL306qKyumjSzJLMs8hzZ/E0EtcFLHr87XRJo9lTS72UYTOnW+dvJdGTHDOgGKkzJ4f/n5bO2spGKglXWZ5SabpWn53LPi+jGPzWOzc33BXIqTUnGMjCOcQNyKwoq0NOq9XuYmJ6MLMSMcv7W5DoqTFWyyRLZrdOco0y1x2yI7yaM4dJIkoeuCHp+OXYnkzBwvGVkyLnekvdFIyZRJyRx9vPYkmVkXnnpYr+yUcE1gDkC52IVcfGpqr1KqE2WFlWT6BNPm/mgxJneuL6NzIMiz+xto7Q0R0iAvzUavT0OSJOySwOaw45QFsiKT6XGRneygos1LSNW4dEEOu+q68Id0urwBkp0O0twO5uR5UDVBQ7cPCYnGHj8OBQrSk9AFtPf5SUtyUpbj4XhrPwP+ME67Qp8/iM2m4LLZuG5ZgeX0WUwO7jTY8GnY/xCEAxH1zLUfgsY3I87gqjsj4Sv9TdB6EHqaQAuAKxN6ayLJ1fsbIKMc1rwbBtrgyLNg90BSKpzzQXj+G+BtB9xgd0LZBdB5PKKe70yGvkYI6+BwR8r+HkgrAXTImzyVdgsz8ap67gfWAduEECslSVoIfFcIcctkDxDiV/XUm1sI338/jDgm2/vei5KTA4Do7SJ07z2RL+Nwm3f9F0phJLxT+PoIP/Y9RGslKDaUDe/Etu4tBnvd24HvP59F7zgOihPXhv/CseI2g41Qg3S++FUC9VHhGHv2IrKv+T8Ud0ZC50AN9nL81c/h7TyIJNsoXPZBCpa8N9qXEBx9825aa08olkqULnof5ctGP2+j0da+g42vfxohIoIUkmTnkvN/SXbWyoTbGosjHVv4294voouIR7+h5B3cuOBzJruQFuSnh77Grs7NSMhcUXgzH5j/JYNNd6iPzx/8Hof6K7FLNj5c9g7uKnnr0PYabyufP/BnmgJdJClOvr7g7VyWs9zU1+7uOj6190G0wTdTHsXBv875MBnOxOLP9/e28bX9r9AVCpBud3L30otZk1Ew9o7j4JaNG2kLRpcTOSSJn65dy/L09EnpbyII64K7dw2wqTWEBFxX4uQLyzyGWa2+oOCH24JU9ghsMrxtoY23zDOGX2q64J7/BPANWwp801oba8oTX+gnhGDH62Eqj0W+j0UlMhsucaCMU0nTInFm2ozfdLg/WjN+Y7PxWBvv/tP2qR7GmLz0uYuYkzvxM+kWZynhIHwnj1Ofr55kis+FDz4/1aOYEZwuVc+AECIw2KFTCHEEWDDeTicL9amnTE4fgPrgP4f+Dz3/iMnpA1Cf+NvQ/9r2xyNOH4Cmom3+O6LPqJAY3P6niNMHoAUJbPk5uq/TYOM99h+D0wcQ7jhM/977EjougJbD9+PtPAiA0FUa9/6O4EDj0Pbu1jeHOX0AgrrDf8LXV0uivLnrf4ecPgAhwry56+6E24mHRw59e8jpA9ha/098IbOq2cbWp9jVuTkyHnReaHqEg91GBc6/NTzOof7I5xYWKr+pfoCWQPRz+0XVUzQFIqqvPi3IPcceJayb1Ra/ceiJIacPwKuF+P6x5xI+tv87+gZdoQAAPeEgPzy6LeE24uFIb6/B6QMICcH/HT48Kf1NFC82BtnUGvHWBPBUfZDtHUblvScrVCoHFTtVHf55SKXdZ/z9bj0WNjh9AE+MQ0UToLVZH3L6ABrrdWoqE1cItTirmBH3x7Odj96/a6qHEBfv/P3k3CcszlL+dhPT3ukDaHgDQv6pHsVZQbyOX4MkSenA48ALkiT9G0jcoxgns5Lie/slvN7YGwKB6P9dbbFtfNF9RbdRshwhEL2thiq915g6AV1F7zPup/Y2EAu1ty72GE5CoH9EfwgC/dH2R6ZyGKv+pH0FO011Pn9rDMtTxx/uN9V1+c3nrdlnPo5mv/E81vtbDGUdQWOgZdh2o/Peq/roU80Xmq6w+XvU4DenCRmLer/RgW309RPvmtpE2BkjhQlA3Wi/h2lCg9f8AqbBa3SyWgaMNgJo9RrPYW27uZ2TRGmelP4+844DMeosLIYxpfdHi/jwhWbGC5zukW+xLCxOhc7jUz2C+OlJ/NnYInHicvyEEDcLIXqEEN8E/hv4I3DTJI7LQK3P7BzEQi6bFXtDaXRdnbxklNnRktlRm7lGFU486UgFRrVQe7lR/VFKyUfJXWioc5ddFLMrd9klscdwEjKKjf3ZnBkk50QVIjPzN0QWyg5DsSWRlrMq4b5yssxCLvl5G2JYnjpFqcZzZpddFKeZE0Kvzb4Iadi6LbvsZGWmcUwXZxk/t0x7GktTo4nXL85eati+NKWULIf5pcLa9DJT3dV5S0Y/iFG4KNu4nvOCnJJTFueIxS0lsVXgLs6b3uuwzs+zG1bi2WVYn2tcF7e2wPidTnXC/BFr6y5ebF4DlxJ72e6YFBTJyCOuikWlZ326AouTMNX3R4v4WFI4M2TtL56fM9VDsDiTWP9fUz2C+Mm1AiVOB3Grek4lJ1vjZ//iB5AHn9SEEIQffgRRPSwBeWoKzo9+dKgohE7oifvh+IGoTU4hjjs/iTQs75m251m0w5uRkjNQzrsNOdv4cC2EILT3QdTjLyKlFuA850MoGWbH01f5Iv377kfztiE700hefAvJS94+ntNA2/FH6ax+Brs7i8JlHyQpfa5he3fbDip2/Zigr5Wk1FnMW/MVUjIS/yGpqo+tb36Fto5IKGVB7gbOWfNN7PaJz7ESUgP8Zc9naOg7TKozm3cu/TbFabEX+m5re4nnGh/GoTi5qfQ9LEo3O7UPNz3Lc22byXZk8MFZb2eOJ+p8hXWVv9S9zOtdR5ntyeOjZdeQ7TQ/DHjVIF/Z/yh7euuRJIlr85by1YXXJnxsPjXMvdV72NvTyuLUbD48e/Wk5PEDeKi2lp8fOzYU0HFtQQGfXbhw1Bx/04VNLSEeqfZjVyRun+1mdbZ5Xd4L1Sqb6zUyXHDrQjslMVQ0n9sXYsvRSIBuigs+dY0Tl318Dltrs8bh/Sq6DvMW2SiZNX3zIZ6JzLQ1flONtcYvPgaCKpf96FXa+qdvasXCNCdbvnL5pLwgtDiL+dN1ULdlqkdxEiS48zGYe+nYphanfI+cMY6fdWOzsLCwOPOxHL/EsO6PFhYWFmcPpyWdw3QgVg4/MKd0UKuq0R59FPTBdT8FBTjvutNgE969Ff3lJ6IiLwWlON71cSTpxMyhjrbzKfSqXUhZRdjWvw3Jkx6z/3DNVsL7HwabC+fqO1BihAQG2w4wsO/vCDWEZ8mtuEuMIYqhvno69v0Z1ddOavnVpM8zJ13vadxM29F/ERxoRrEnkV5yMfmL340sGz/C7tY3aTz+LyRJoXjBu0jLTjxhuBCCN3b8N/VNLwGC9NT5XHLBr7GPSI/Q1XecvRV/JRTuZ37JW8ad1qF1oIpXa/6KN9TNmsIbWJFvzuMXL8+2buLp1tfIdKTx3tJbKEsqMtns7a3mgfqN6OjcVnQB6zKiYbxBTeVrBx9jf28jea5U7l78Fso95kToWzpqeLTxIC7Fxp2lq1iUmjvuMU8UjT4ff62upjUQ4Iq8PG4sNidDfaqxhRda2slxOnjv7FKKkowxkfu6+/lnbQuagLeV5rI2a/KSHvtUwX3HfRzuUVmZZeeOOW4cI9QzB0KCfxwMsadNxyZLXFGmcP1cmyGPnxCCNyo0tlepBMKCogyZy5fayUsb34xfdYVKTaWGO0liyQobKTFmGMeiu1qjcUeYUL/AmS5RfI6dtOLEZw7DTTr+LSoiJHCtteFcML7ZR602gLq1BwTYzk1FmWPOOQkgvCrqay2I9gDy3BSU83KRZGv2wWLm4w+pnPudF+gLmtcETxeW5Kfwn09diGz95iwmCiHg1+uh/chUj2R0kovgwy9B6uSonlsYmTEzfvGkcxDd3YT+cK9pu7RoIY4bbwRAO7AD9dl/mW0Wr8Zx3TsBULc9grY1qgQq5c/D8a7vmPZRWw7ge+TDUQfS7ib5zoeQhzkK6kAbrQ/dhlAHBWYkmdy3/AFHbsRBFFqYisfehuqNiqcUXvhN0mZfM1Tub9/L0Rc+ykhlprwF76RkzWeGygM9x9j1wnsRgyqZsuJk7dX/wJ1sdn5Oxp4DP+N45QOGutSUuVx92d+HysFwPw+9fAuhcFTA5Opzf0ZRzvqE+gqqPn645Ra84e6hurtW/JDFObHXR56Ml9u38bXD/zdUznKk88i6X+Ialq+vwd/JHdt/TGhQtVSRZP6y+tPMTY5ccD666+/s64uKyyQpDp6/4DMGR2N/bwsf3fXY0KeRpNj557nvIssZ+2H6dKDqOrdv3UqzPypW89XFi7m+KPrZP9vUyncOHhsq57mcPHj+WmyDodKNvgDv2XqA0KAyiiJJ3Lt+MXNSJue4/mdnPxtbokIGby118tllxpcL39saZP8I8ZbbFtq4aUE0JHTrMZVn9hrVQJMc8LnrXDjtiT1A1VapvL4x2pY7CW641ZVQOof+Zo1Dj4wQaJBg2TudJGXF70TqXkHXzwOIYU2lvdeBI8HQU70rTPBXDaAOfmNlcH6kCDnfabIN/vk4oi4qCqRclIf90tN7M7Zm/BLDmvGLj3O+8+K0DvM8wTWL8/jtu62vv8UE8be3QeULUz2KsUnOhS/MICGaKeR0pXOYUoqT4ltbplVUxqwXx6JfJv3ovtg2R/ZGbY69btzWctyUzgFArXjZmBoi7EetMcZRB+q3RJ0+AKHjq35lqOhvP2Bw+gD6al4ylLvrXiGWHG9XndGuo+G1IacPQNeCdDZtMu03FrX1T5vq+vor0LToTbOp/U2D0wdQ3fRywn1Vde8yOH0A+1tfGsX65LzUYfzcOkM97Ok9ZKjb1HlwyOmDSEL31zqi6z0P9jca7H1aiGP9RrXQl9sqDZ+GTwvzetfUivgd6eszOH0AL7cav1evtBq/w62BIId6o8JJW9p7hpw+AE0INrYZP5uJQtUFm1uMztErzcayNyxMTh/AtiajOt/+enPqBl8IqmLsOxZ1Nca2/T7oaEusna6KGOqBIjILmAih45rB6QMIHUpcmVA/6os6fQA6aId95iEOhA1OH4B+qCfh/iwspiMzwekDeOnI5ChoW5ylVL0yts10YKANOizH73QwIxy/Bl98svRS2iiqXe5h4WxpoyRO90RnGqTUEapaDje4kxmJHGNaemSdLdlsY0spGLY9DzDOJthH7OP0xH7j7hxh54phF6tuLNwus6qYJDmQ5ejMWXKSud1YdWOR4TbvE6suHgqc5nEXuHJHlDNNNvmu6HfCo5hnQXJdxu9VgdusBJrvmtqEu3kuF8oIQYACtzGMM99tPDaZyKzf0HaX+dhj1U0EigTZLuPlJz/JWHYqkBwjB3tOkvE4MzyxL2MZSYmHS3mSzfvEqjsZzlFCQ50pibUjp5vt5fTEL9lSujmiX8qIEeXvUsBpbF9KnxwxIguL081MCZ5Mc8e46FlYjBen+dl12uKxFG1PBzPC8YsXee5cyMoy1dtuuin6/7mXgss8g2i7+X1D/ysXvAuSB9tR7Ngufg+S3WXax77oRpSiNdHygutQitcZbJzF55I0Nxq26Sxci2f+9UNlR3Ih2Ss+MJSKwZFWTtbSuwxtZM99C8m5RgVLmzOD4lWfMtTlll5FZv55Q+Wc4svJKrjANO6xOG/ttxn51Viz8isGpbGc9MUsmvU2TtxOs9OXsKjsbQn3lZ88hwtL34U02F9hygLOL7k94XYA3lV8I/M8EWVVGYl3l9zErKRCg82FWYu5NHvZUHlD5kKuyl05VP7CvCsNaSNuyF9GpsP4fbmxYBGr0qPtXpe/gDXpiYXTTjQ5LhcfmDNnyPkrTUrirvJyg82dZSXM8kScQUWC984uJc8d/V6fn5vOJXlRJ/jc7DSuKDA7yhOBJEl8ZqkH92DUYqpd4hOLjefZJku8b4Ud27AntlQHvGOR8cHo8iU20kY4eRvmKeSPw0latNRO2qDDJUmwZIWN5JTE2slZrJBSaBxPeplM5tzEQjQdZQquldF97KUy7jWJr/GTFyShLImeW3meG2Wp+WFAssnYry1m6IQn27BdXmiys7CYiXzzRnOaoOnI79+9bmwjC4t4ue3+qR5BfFz6dXCnT/UozgpmzBq/HTt2mAVe3nUNzhg5zNSmJrRNmyE7G/ullwyleziBEDpafRXa9o1IGdnYL7keSTY+UAlNRbTXIKXlIcWY4RmO1lmFZHMip43+8K/2NSC0MPaM8pjbw752NH8Xzsz5o0o5+3sqEUJH10IkZcxFjjE7BeDtq0aSFJJSSmNujwddV6mofphwqI/5c99lEnY5wYCvmZA6QGbqvJjb46Un0Iov3EtB8rxTkrIWQnDcW0u6PYVcp/klwAnqfe1oQqfMY85151WDvNZxjOVpxRS7R5khBioHOnEpdorc0yc/VEcwSGcwyLyUFMO6xBPoQnC830uWw072KLN59d4AmhCUJY8zGV4CeMM6dV6N2Sk2nKOso/OGBZXdOk4F5mTI2GIIH2i6oKVHEFQFWckSaUnjf6clhKCnS+ByS7jHMWt4Al+nTtgncCRLuDPGPx6tW0eEwZZ7au/p9M4w6AI55+SzeMKvIrpCSPkuJOX0vxu01vglhrXGL376A2E+/Oc32F7XS7JbwSYkevyRUHEdyEhS0AUUpbuRJAipOi67QudAkJAm6PaF0fTI606NiDqeww6+YUuMZcBtg4AaWaChAy4JFAVCg3WKAkKDE5HcNgluXpXPd29dhX0KfnMWZzhaGJ74FFS+CvYUSC8Efzd0VIPaD7ITsudCXyNoGniyIpFuuoBQPwT6wWYH1Q/J+ZA5OzI7F+yH6s2ga6D6Ikuf7MmQnAPBPnAkR/YJ+8GRBCmFEQGXtqPg6wDZDrMvhWu+FVnjZxEX01rVU5KkGqCfyDVSFUKslSQpE/gnUAbUALcJIca3kOiBZ2GkqmdzM9rj/4aBAejsQF+5AnnELKAIhdGP7EXSVOSS2SCZL7SSYkPKn2uqN7QjBFrTbkQ4gK1k9Ld0QldRextAVrClzxpSDx2OPSkHe9LJp7nd6XMI9NcT6K/H6clHdpsf3KsP/I7G44/gcKazYN3XSMtZabLxDtTT13OMzOyVOF2xnaNjlf+go3MfyxZ9dFSnr6FtG0dqH8VhT2NJ2dvISh9/8k1vqIdXa/5CYcp8Lil7r8n584b7Odizgzx3MbOSR3cyJUlifnLZ6P2oAbb3VJDvTGdhiln1EsAp2/AoDl5sPcyajFksG8Whz3F6eKzxIEk2B28pWIRTMf+cfGqYHd3N5DiTWJRqVgedSFr8frZ2RNbxZTgc5LrMs9QAA6pKTyhMusMR04kq8bjY193P1vYe1mSm4pzEB5H+sGBLa4iGAZ3LixwxnVWPXWJ57slnuhq6dPbUqiQ5JPJST+2yJgQE/IJQSOByy+N6EREaEPi7BZ4cCddJ1EW1gMBXp+PIkHDmxLZTTsFpHI6cFV8ImeS2IRXFPodC1dGre5AcClJpqpVv7BSZ9HukhYFjrf3sb+5HFdDjM6+X7Rys6/YPxNxfwrjaXgVUo64UOuAdsew4IAaNT+w3omtNwNP727hrQy/Li0d/2WhhMS566qFxJ3jbgFborQZZAdkBzlRQg9B2cNBYh55ecxshABt0VUT+sANqJFrN5orcONEg3Avdg/v72qL7B3ugvxma5IjdCY49Beveazl+p5FJnfEbvKmtFUJ0DKu7B+gSQnxfkqSvABlCiC+frJ14VT3Dm7egb91q2q5cdSW2lSsB0LvaCf/ph8Zx5hVhv+OTSHL8D1hC1/D95zNo9dsBkNNnkXTr75HdRvl7PeSl/T8fJdwVWbTqyFtGzvW/QlISXzvTdvQh6nb+HyCQZAdzL/oBaYXR0M7Nj12BFu437JNXdiMLz/l/Q+Xayoc5tOdHgECWHaw+7wfk5BvTSzzx7LUEg11D5WWLPs7C+e8x2Ly4/UvUtb5mqFs25y7WLfpEwsf17PFf81rtX4fKTiWJ/774BZTBVBXV/Uf51p6P49MiN+MbS+7ijjmJ91PjbeVje39LTziyZvSWwvP44rybDTZ94QAf2PkXGgPRC9/lOQv51pK3GuwO9Lbwsd2Pow3+fjyKnfvPeSd5rqiT3ODr42O7nqErFBH3ub5gLl9bdH7C446HF1ta+N/9+4ceSmTg7uXLuSQvOqMZ0nU+s3M/+3siojxzkj38et1yQ5J3IQRf21PBlvYeAPJdDn597iKynRO/1uvFxgDf3hNdv1uYJPPXi9OxJyhl/tC2IPvqowIsEvD+i+2U5SbuAIaCgpeeCdLbEzmTOXkyl17tSEhevbta4/gzoYjukwTll9jJXWIeS6BFp+FfQfTB1/6Z59rIvnD6ru8R3hChv+xDdEVEhOQ5GdhvXzLhzt/ZNOM3EfdIa8YvPr757wP85fWpFeGKh09eOofPX71wqodhcaaw62/wROLPS6edNe+HG38y1aOYEcxEVc+3Aiee8v8K3DTWDvE+CsVy+gC0F6MqkeEXHjVtF62N6DXHTPUnQ63bNuT0Aeg9tYQP/dtk56t4ZsjpAwi17sdf/WpCfQHoWpjGfb/jxPtGoYcGyxG6mreZnD6A1pr/oIYjDpOuqxw7+NuhNnQ9NFiO0ty61eD0ARw8akyREQz1mZw+gANVDxAKx35TOhqqHmJjrTEGPaj52DSs7tHaPw05fQBP1T9AT7AzoX4A/lb/6pDTB/Bo0+s0+I3t/Kd5r8HpA3ip/QhHRih7/qxiy5DTB+DVwtxft9tg80DdwSGnD+Cp5gqqvT0Jjzsefnv8uOFNtA78tqLCYLOxrWPI6QOoHPDybHObwWZv98CQ0wfQEgjxWJ3RZqL41QhlySafzqbmxJT3Wnt1g9MHkW/3U3vMSp/xUF2hDTl9AO2tOk31ial61r8ejor9isFyjBdsna+Hh5w+gK7tKqp3+obeaztbhpw+AL2yG72qZ+oGdOaS8D3SYmxmgtMH8ItXYquTW1iMi6e/ONUjiI+df5rqEZw1TLbjJ4DnJUnaKUnShwfr8oQQzYP/twDmRVaAJEkfliRphyRJO/QBfyyT+NGHPbgFRlEIDZjlzU+GCPTFqDNPj+sx7PSguW7M/vQwmmocoxqM9hfwtYzcJdqfGhxsQzW1EQ4Zx+L1Npn7Fsa4lLAa+/MQQkPVEvusND2MwBxy0xeMph4YGJE2QkczOILx0qeaP+O+sG+ETcBkA9AbNh5XX9jsoHSFfGPaxKqbCHpDIVNdX9gYg9QfNjtDvaERNqrZpi/GfhNBQDU7OT3hxBwffyi2fSDBdk4QDJr3i1V3MtSA0V4LGbO+nEAf+VXTQR/leKYDIhA2V/pj1FkkwrjukcPvj+3t7adrrDOWmaBlYGExKWjWNdrCyGQ7fhcIIVYD1wL/JUmSISu3iFyNY16RhRC/F0KsFUKs1eIVmSiInQZAmhddq2dbf4XZwO5AnrMovj5O7FJ+AdJw4Q/FgX3BtSa7pLlXIdmi45ccKbjLL02oLwDFnkRmqXHs2XPeMvR/QfkNxBKsdieX4HBH1vEpNhcFJVcatheX3Wgozym/lZFfi5ys1YZyclIeSTFSPuRkLItZfzKcNg+lactM9ReXvXvo/0sLjGNckLaCwqRZCfUDcEO+cR3mvORCFo1Y53d13mJsI46/wJXG6nSjUM7bi5eb2n9bsfE4ri+ca/hEyjxpLE2bHLniG4vN6xVvKDKuTbwoN5uUYWGdLlnmygJjXP26rFRynNE5dkWSuLZwctYmXlVkXKNql+CSgsTSR5Rmy2TEyC9/7tzxrfObNVtBGbac0OGE4tLElDRzFhv7zl6gIMcQrkldZmzXXSzjmKD1fJOBsiwvIgd7gmQ78rzJUX09ixjXPXL4/TEnx5JAHwtJkpiXG18+4Klm/gwZp8UMYfGNY9tMBzJPrqlhMXGcNlVPSZK+CQwAHwIuEUI0S5JUALwqhDipKsjatWvFlt/+CV56w7TNOULcJfiPB6G+PlpRVobztrcbbMJ730Df+HRkVXZeEY7rb0dKS/wBRu9rIrTvYYTqx7H4rSi5sePyw10VDBx+HElW8Cy6FXv6+NQ2dS1E+/FH8XUfIzV/HVnlRkfT21vFrpc+iK5GZjXTclax7MKfoAxzPDUtRF3VI/T3HCMrdx2Fpdea1uj09Faw9c0vEgz2kJ+3gfPWfcc0lmC4n1d2fo3Wrn3IksLsoqs5Z/GnsNsSV4IMa0EePnQ3xzpex21P47al/0tZutGx2tGxke0dr5LnKuaa4ttIso0vN80bXcd4oX0P+c503l50Pml28032aH8Lf6rZSmOgmxVpxbxv1vlkx8iF80TTYR5q2IddVvhI+bmcm2VWmN3R1cwLrVVkO5N4W/EiMhyxBVdOFU0I/t3QwDNNTUjA9UVF3FhUZBJLqff6eayhCU0I3lJUwJwU8/G3BUI8UtfKQFjj2qJslqZPTh4gIQR/Pe7npaYgWU6Zzyz1UJaSuMPmDQqe3RviWIuOQ4HzF9hZP07HD6C7U6fymIqiwNyFNlJGycs3GkIIOg5r9DXqeHJlcpfGdvwABio0Bo5r2DMk0lfZUJzTWyxFb+pH290CTgXb2kKk9In/Pp9Na/yGM957pLXGLz5UTefmX21mf5N5ScR0oTzLzStfvGyqh2FxpvHQ++CgeZnTtCFvGXzktYjgjMWYnOo9ctIcP0mSPIAshOgf/P8F4G7gcqBz2ML1TCHEl07WlnVjs7CwsDg7OFscv4m6R1r3RwsLC4uzh+mcziEPeGxwNskGPCCEeFaSpO3AvyRJ+gBQC9wWT2OmHH4nuOo8nKuWAqD39BD+x4PQP/hGT1FQNmzAdt56wy6hh/6AqB0UXMnIxvGuTyC5jfFi4dfuR9/15GBeEje2Gz+HUrYinqEa0LxtdG/5IaG2AzjzV5K+4QsoSaPnlxuNoLeFyk1fxdd9DFm2k7vgNopXftxg01j5GJW7foQQkTVZ6XnrWX7hj5HkxD7mcHiALW98kY6uvUiSwtzZb2fFEmOy+J6BGl7b9Q26+o8jy3YWlt7MusWfRJYSf2PzZsO/eeLoPWhCxSY7uH3pt1mce7HBpivYzp+O3cPxvv0sSFvB++d9ifST5OkbjZ6wlx8ff5ydPZUsSinmC/NuosBlnO3tDvn48fHn2d1Tz+LUAj4/7yryXcZcfb+vepMH6veg6jqrMgr5yfIbsCWgCnuCBt8APzm2m6N93azNzONzC1aRah+fgub91dU83tCAx2bj/XPmcHHu5Mgj//xwM/+u70YXgvXZyXxvTeJht1NBICh4bXuYxjaN3EyZi9baSU2Ofmb9fTovPRMkMGw558pzFBYuHt/n0XZQpXmXChIUrraZQkDjQfcJBp4OE6rRsBfKJF9nRxlHYnrh0wg/3YFWFUAucGC/Phs50yibpb7ZjvpyM4R0yHTgeFs5cr5xBl/b14q6uR50gbK+CNtaK8H7KTCh90iLk/Pa0Tbe8+ftYxtOMdu/ejk5aZMTGWJxFqJr8NNlkRx90xVPLnzwBcgom+qRnBVM2oISIUSVEGLF4N8SIcR3Bus7hRCXCyHmCSGuEEJ0jdXWSXn+9aF/w//6V9TpA9A0tE2b0Gujal7qluejTh9Adwfhf99naFKr3o2+84moIkPYj/r49xGh2MIfJ6Pr1bsJ1G5C93fjr36F7k3fTbgNIOL0dR0GoaFrAVoO3UdnzfND2/u7j1Cx8/tDTh9AT+s2ao/cF6u5k7Jz7/do79yFEFpE+bPi7zQ2G1U8X9r+JTr7jiCEhqYFOFj9D47UPJJwX/7wAI8d+S7a4LhVPcT9+76MN9RjsPvNkbvZ0bmR3nA3b3a8yu+OfjvhvgB+ePwxXmzfS3d4gK1dR/ifw/8w2dxz7Dlebj9Kd9jHls5K7j78pGH7wb5W/lK7k5CuoSPY2d3Ij49vGtd4/ufANrZ1ttAdDvJCax0/PbZ77J1i8EprK7+tqKAlEKByYID/2bePZv8piiLFYFt7Pw/XdhHWBZqALe0D3HusdcL7mQxe2x6mok7DH4DaJp3ntxgFcV57wej0Aex5U8M3DqXN/maN6lfCBHoFgR5B1cthBloTUwcFGHgqTPCghvBC6LhO36PjW6gffroTbb8XvBp6hZ/QQ0alVr1uAPWZRgjqkRVlnSFC91cg9Oix6y0DhP99DNHpR3QHUJ+pRKvpGdd4LE7jPdICYEY4fQAX/fCVqR6CxZnExh9Ob6cPIvkF/3bLVI/irGH6KgkMo9STEp9hrKSTgF4Tdfy04wdN20VzndG+4s0YjWiI1qr4xnGiXSEINu001AUbEw/J0bVwxOkbQX9L9EbW07bTtB2gve7FhPtrazePsal549D/vkAHvV6zNHZTR4zzNgaH2l811QkEtb37DHUHunectBwvO7qNKQ4O9NUSGKF6taO7xlDe01uPqkeVR59vMaf+2N5Vb6obiwE1zNF+Y17mHV3jS52ws8v4bKgJwZ7uic/5/EKT+Te2tX36rpkZTkOrUT22tVMQHlQWDQYEA6McRmtz4qqmvTFSQPQ1mNVrxyJUZdxHrdcRMdRQx0KrNnq0oimICETHqFfHUMn1aojuqAqtHsPJ06vNdRYW0w1dnzmqnn418RdEFhajsvfBqR5BfHRVQmgU1X2LCWVGOH513jgfLJNiyPsBUn5UDVsqjBGWlmEMGZSKYit8Stlm5cSTIUkS9uz5hjp79kl1bGIiK3acyWbhkKTMaFvJGbHbTctdk3B/aWnzTXVZmVGxFZczA3eMMMustMSTzs7JWBezviB5nqFcnmI8vrKUxM8jwMIUo9JlWVIuLsUY8rYgJd84Rk8OtmGLjs/NNIvzzEtOXPnSo9godhuFUxakZIxifXLmp5hfjsSqO1XWZZvFYBanJS7oMxXkjFDMzEiVsNsiYioOJzhHia7Kykk8fNmTa760JuUkfrm1FRr3UXIkJFviAjBygTFcVcqywzAhGakgxmfokJHSovvJBWaRHzl/coR/LCwmElme3qJJwxlFB8rCYnyUXzLVI4gPTy44LEXb08GMcPzixX7TW8FmXEcjL16MPD/qyNgvfysMV/B0OHHc9D7DPsqiC5DKh6UwkCSUyz+I5Dau84qHjIv+H7b08kjfmfPIuPCrCbcBMPuCb2FzRZ2C9OJL+P/snXV4HNf1v9+BRTEzGGWmmB1wuGHGJm2SQspNOf22v3KbppBymzalJA00jA06DHZsx8y2mFna1eLA74+1dzU7K1srS5EVz+vHz6N758ydO7Azc+ae+zm5Uy+ObSd/McXTjFNBnCmlTJn72aS3tWThd3G7Y6kxigpPYlLF+dGyKEisXvQTHPbMaF1p/krmTrku6W1lugo4seyaQTUCZ0/5HFkuY2qOz1R9l1L3ZADKU6Zyc9X/Jb0tgK9Pu4QZqRHnr9yVx/dmXGWy+eb0s5meGvlYUOHO5rszzjMsX5lbwal5k6PlYmc635mRvBKbIAj8v9lLKTvo/M1Kz+YrVQuTbgfg3OJizi8uRhIEUmSZL06fzpQxcPw+UpLF0tzYy35lioMvz0ycRuVY45QlNvKyI29VmWkCp6+IOTWCIHDSaXbip2lOmiqQnpH8bTKrUqJokYwggShD8QkymUmmhQBIO8+GXBTps5QjkHbxyOYb2s7NRTiYPkPIsWG/NM+g5itNz0BakhPLCGMXsV1RiSDH9l2syEQ6uRxsIkgC0rISxBnJz7O1sBgPvn3OyD4WftDc/6ll490Fiw8TH/kZSMmlSfrAEW1w9X3j3Yvjhg8sncPRMFi1bLDIS3wqh0NoXi+6KCLa7QhyYkEF1e8DVUFKHdqZ08IBdP8AYmoWwgiEOwxthQYQR+FrhhLsQ5QciHLi4QlNDRP0tSM70rDZk3dUBxMK9SOKduQhtqXrOiHFiyTakKWjm4yuaGH6g51kOPKQDiNG41cGcMlHfxwHlAApQ+xXzCZIijz0DTOghgmoCpn2oxvx0nUdn6qQItuObHwEgqqKJAgjEppJBr+ioWgaafax1IcaG0JhHZuMKY0JRM6F36/iH9DJypGPeqRAUyP316HSOQy7naCOOAqpHvSgBnYh4b4D6IqGHlIRXPLQNmpkHuBgp3A0OV5UPUcLS9UzOdYe6KS930cgrBLWNDr6A5RlpbKloZOF5Tlomo6OjjeokZ1qo9+vkJtiY2tjH5IONpuI3SajaxppLjtTClPZ19LPrtZ+5pRk8H5tL2XZLtIcMooKuZlO+gaCaKpObpqDvoBCW6+PoKqT7rKT6hCRRZH5ldksKLM+pFiMEZ5O2PUkpBVDyAOODPB1gT0NXNmg+MGdA9014MoA2R75apk9Gdp2ga8bwj7QVag6C5o2QGc1ZE4FQpBSAOkFEOiFoBf8vYAMzlSQHZHRPCUEihdyp0dEZzytkFkGqfkwxPPGwsyxrOo56sQrewZvv8vk/Cn7D6C+/DIEAlBeju388xDtxq/kamMtyvP/hb4eFLsd6azLkauMeeN0Xz/a7rcihZkngcs8eqKrYcL7Xkb3tiNPWY2UZQ4jDXUfoG/9X9B8XTiKFpE661Lk9BKT3ZHwtG2mbsMvUENeMkpPpmjWR3GkGEdaAt5W9mz4CZ7undgcWUw74dtkF5qvDW9/DW3Nr+N0F1JUejqimNjh6OndRVfPNnKzF5CfZ25nX8MzVDe/RE5GFQunf2LEzt+ezndp7N/J5KxFZLsSjx75FC9vtb1ASAuwMv8ssh0jS1qs6hp/rH6GNzt3MTu9jO9MvwK7ZN7/hxrW80TLFnLsKXx92plUpBhDOZv9/fx8z+t0BLxcWDyTq8rmm3Lmtfi9vNRWTaPfQ6EzhTMKJlHuzjBtSxCEUXH6ALb09rKjt5f5WVksyjbnplzb2c3ufi8LszKYn2XuS08wzEutXUiCwJlFOaTbEt8idvX5eaCmk2yHzOerCkhP4ADqus477T72e0IsznExO8t4fYRUnfsP+HmlOUiJW+KWOSkUuM2jYrs6VXZ1aUzJFJlfkHjUrKVX5dUdCpIIZ8y1kZM6tFNitw39gBEEAU+fQEebTjisUVg8srxCmqbRuFZloF0jd4ZE3gzz8Qn3aXj2qIhOgfQZEqJ96H6NhtMHIDiGPi56Xwh1ey84JaS5mWBPvO+C9KEKFLE4jvjsfzbw3Pahxajuea/16Daw4ejWX12Vy79vtEb8LEaZ6jfg0ZtgoGOYKwhEVL6G4NnR6NQgppwJH30IU8iNxZgwYUb83r7i5iGXH3L+lI0bUde8Ylxot2P/8peiX6/V6t0oj/3T1IZ0+sXIC1cCEacv9J9vgvegYEZaDvbrfokQNx9r4MkvoTYcFDQRbbgv+SNyUSzlQ6hzD+2P34DhByQ5yL/oLuw55nl0Q9HXupF9r3zeWCk6mH3Ov3FlRMJIg7421j57SeRrzCBmrbydvNLV0XJXx/usf/OLUfXPvMJVLF51h2mbu/b8i+2774yW583+ElVTPxotv7Xlp+xteCpaTnEWcuXpjyMIyf1wXzxwJ6/W/CtavrDq66wou8JgE1ID3LrhYzT7I4IyqXI6ty2+hzxn8iGG12/4DfsHWqLlTFsKz638vsHmezue5OWO3dGyAPxt0fXMTo9I17cFPFz27n1og87ryTmV/HzeOdFytbeHT2/8H341JgxiF0X+sPBs5mSMTZqFfx44wD+rYwJEX6qq4sry2HzEv+2v5d6amAjNV2dM4ZKymBx/dzDMTe/uoDsUEbspdNr5x4rZpMU5fy819/LjrTGVMJck8vTpVdjjbtp/2NnFI3X90fK35+bykdLYB5RPvtHDfk9MyEAS4L+nZZHrjLXzYrXCv7fFxHcumS5zxUyjk1zXqfL3V2MKnaIAX/6Ig+zDOH9DsXt7mM0bYuds7iKZ2fOSd8q33Bcg0BO7PgrmSVSeHPsAFezSaLgviHaw2458gfLrHAjjNBdJ6wwQ+vveiKonIBS6sH9yOsI4TDiyRvySwxrxGx5n3PEa+9uPffGIkgwnb3/79PHuhsWHhe2PwSM3HtluvHHnwTf3H9nO4qifkRPCvc4d5kiS+u5ac2UohFZTEy0qbz6XeN23Xoj9vfutmNMH4OlC2/uO0b5zX8zpA9DChLY8ZLDpW/8XTF9N1CADO5NLe1C/4ZfmSi1Ix77Ho8W6nf8yOX0A1Vv+YCjX7X/QkPKho/VtPP1mtdI9B4zx1nv2/ye2aU1hX6Pxk89AoJWWrvcPvyNxqJrCW3XGdApv1JnjvDd0vRl1+gC8Sj+vtTyd1LYAukIeg9MHkbx+2/sHqb7qGmsGOX0QOYP31sWurb/XbDA4fQBvdNXSH46l+3i8aY/B6QMIaRqPNBrbHi10XefBQWlLAB6orY3+rWg6D9cZJZ0fiCu/0NIZdfoAWgMhXmszK4P+a7/xq6Ff1Xiq3mjnVzSerO831D1YE1ME3dOnGJw+AFWH/+z3Geqe2W88hv87oKDFfax6abvRRtPh1Z3JK3EC7Ipra/f25NsJ9GkGpw+gY6fxt9m3RYk6fQDBdh1f3fip+akbuqJOH4De6kernhhqrRYWw2EiOH0ATX3Jp42ysBiSNT8e7x4MD18H9B/liLvFsJgQjp9ytKOShhC8Ib5gj8aHbVOM8lCNJrcxYcg+Dzp9Q8VHD6NPQsLLQIgrHbnPyR5CQRBMI4SJ5hUl3nbyJ2yoNcRBS4SD/0zrDurX0KHog23GZaTEWDYt5/DLE14bw912cjZDnosjNDQ6V8Lw2/9Az+J4TnEY6wNrYWFhYfHBM5Hu41ao5wfChDjKvVrwyEaAvGqludJhR6ysjNmcfI7ZBpBOitVLM0+CtEGTrNPzEKuMbUu505ArVgyqcGCff7XBJmPp5zH96iQnqbMvP+x+xFO+5JumOkFykj/tkmi5YuaNCIJ5Ts6U+V8ylCunXY0waE5fftFJpKZXmtabMe36uPLHon+Losz0sgsNy1NdxRTmLCIZREHipPJrDXWnVFxvsjsh50RK3ZOi5XRbFqcWXWiyOxLZ9jSmpxYb62ypzEqPhUOKgsCZ+cZ0HgJwffnyaPmTlUsMziLAabmTSbfFhGAuLakiJW7uoF2UuLIscaqQo0UQBK6tMM4x/eik2DGTRYGrKozpSD5aaSyfXZRDniPW52KXg1MLzfMEPzHNOL/SLYlcWGZMQ+GSRS6tjIkLCcA1kzKj5ekZMtPTjbcfWYCPTjEK5Vw4zRhmet5U2eQcnjk3TslXgNNmj2z68sy5trhy8u04M0Rc2cY+5s8x/jYzF8iIg3SDHAUC7vLxux1Li3Ng0Pw/ociFOHn0VWEtLMaLGQUTI/VIWdbESI9jMUE444fj3YPhkVoQEXmxGHMmzBy/DRs2mMRdwKzsqdTUoL68Bnw+qKzEft65JmVPrbWR8P8ehN5OsLuQPnI58tTZBhvd70Xb8zYIAmLVSgSn+aGhqwrKgVfRvG3YJp+CmGnOtRfqraP/kLhLyWJSqi5ETkt+bpqnczv1792OGvaSWbaawhnXYHcbfyQBXxv7NtxOX9dW7M4cpi/+Dpl580xtDXjqaWt+HVdKEQXFqxGHUNFs79xIV/c28nIWkJuzwLR8f+PzVDe/QE7GTOZP/diIxV32d71HY/9OJmWdQEXm3IQ2AcXHOx0vE1T9rMg/g0z7yNTPNF3jrzUv8FrnNualT+Kb0y/BlmD/n2h6n0ebN5NnT+WWaWdQ7jY6QG0BD7/Y8wZtQQ+XFs/hkpLZphG39sAAL7VV0+IfIN/p5vSCSZQkEAkaTTZ2d7Ozr4/5WVnMy8w0LV/f1cPufi+LsjKYnWlWfe0LKaw5KO5yWmG2aX7fIbb2DPBATRc5dpmbpxeQNoQQyNoOHwf6Q5yQ62JGhlEhNazpPHTAz8vNIcpSRb40O4Vcp7mdvd0quzo1JmeKzM1PvJ32PpVXdypIEpw+20ZWysidqPY2lc42jZw8kYKikYu7NK1XGWiLiLvkTk8g7uLR8e5REZ2QViUhHkZ05oNA7w+h7uyNiLvMzkKwjY8jas3xSw5rjt/w+eqDm3hsc/N4d2NIPjK7gDuvty59i1Gm7l145CbwDPfalwCNwwq8DIsjiMQcYsYFcNW9lrLnMDnaZ+TEcvza2uDfMUGRodI5hFpa0OvqEKZMwZ6XWP1R6e1Cra9FyM7GXjopoc0HiaaG0LUwku3wqQrC/i4E0YbsSJyqQVUC6JqKjnrU6RwAfL5W7PYMZNn8FVLTFBQ1gN12dF9SdV2nxbOP3mAbpakzSXclnwz9EGFNodnfTo4jg9TDpH3wKH5ckh05wSgpQK23E58apCq9CGkIwZr+cIDWgIcSVwYpcuL8av3hIGFVZUANUZ6SmfT+HCKkqXjDCm5Zwikldsb8isKu3l7yXC7KUiZOIlRV1/EpOmlH6Wi096vYRJ00l4Q8hCiJquqo2uGVPUcLNaRH8vgdpUCKrunoIRCdo5DOIXwwFYM98bHW/Qo4pKMWmdG8QZBFROfhhXH0UBg9pCC4HdGUOZbjlxyW45ccf39jH7UdXgQgqGoEFY0Um42QEqY/qJGfKqPpImluG56BEPs7PEgipDjsTM5PIRDQcLkk+nwh+nxhwopOTopMc2+QOSUZON0yPr9CKKxS2+3FZZNZUJKFNxBmV+cAgVCAovQUgqpOZoqN+k4/q6bkMrc8i2WTR/7ss7A4LM1boHYdpGRE5tKFVWhcD5NXRlIveNojOhGZFZFUDz3VULkCOmuguxpUP5QsgJLF0FMH2kE9gPp1kZQQaQWRNA2BfggPRNI3VL8BzjQoXgjpRWBzQ81bEOiDjv0w9bRIuoe5l8IQ7zUWZo4bx284qp6qz4fyxz+Zltu++hXEg6N+ms9L+G+3gRI22Eg3fBU5t3AUez18unY8QOeWu9CUAOmTzqR45XcR4sIENTXEzueuJ3BQiCQ1fxFVp//JMMpUvfVPNO65Pyrekpo9mzkrb8PhLki6T4FgNy+9ej2BYCcAFaXnsPSEH0SX7214mvd2/p5Q2EN5wYmcsvBH2GR30tup7t7EXe9/xlCX7SrhG6seS7qt+xuf5g/V/0E/+IVpaeY8fjf3O4Zj1B3y8t2d/2FTXzU59jS+Ne1STsqNjfYe8HZw44Z/oQz6SvXjmRdyekEsRNOvhvns+4+z19sVrVuSVcod88+LOomNvn6+u/119g0SCXKIEo+suIxsR3KhPA/XV/OnfTtRdB0BuLSsklumzzHs17c3b+bNjpjoigzctXw508Ygiftosq49xC+3eukM6szJkvnBojSDqudwqG5TufvNENqgW9lZc2VOmmH8DW3do7Bua5iwAlPKJM5YYUMaA9VKTdWpeSVM514VUYbSJTJFi0aWriO4S8XzbAh9AGyVIumX2xFTRtbn8MvdKO/2ga4jLU7Hdk5O9BrSvWFCD9ei1w9AqoztgjKk6eZ0H0dCC4YJ/f1t6PUDIEzOxXHNEpOdrmmEn1qLtqsxUmGXsV28AmlKkeX4JYnl+A2P36/Zwx0vHfuqgf/8+GJOm5n8M9vCIiFBD/y8HPTxEw8bFvOugUvvPLKdxfGh6jlclHvuSVgffjSmoqk8fZ/J6QNQH/jzmPXrcAR7a2jf8Du0sA90jf7qF+jZ+7jJrn7DHVGnD8Db/j4d+2N23a3raNh9j0Gx09u9gwNbfj+ifq1d/92o0wdQ1/gc3T07AfAFOnl7622Ewv2ATn3bm2w78J8hWjo8d2/5qqmu29/E+82J1VeHojXQye+r7406fQDv9W7l+bY3DXZ/rXmeTX0RFdOukIcf7f4vATUmr/iNbY8YnD6AH+x+GkWLqTL+p26TwekDWN/TyEut+6LlO/auMzh9AEFN5UubXiAZGnxefrd3R1TgSAcebajl7c5YLqr9/f0Gpw9AAb69aVNS2/qgCak6P9sScfoAtvco/HV38sp7D641On0AL25T6BikGtrbr/HmxjChMOg67K9X2bZ3ZMqfR6Jjp0rnHhX0yEfR+ncUfF3JP3T1kI7nyYjTBxCu1Rh41XzvGg5qtR/lzV5QdFBBXdePtit2rJU1LRGnD8CrEH6iHl1Jvs/K/3ZEnT4AvboTZXuTyU7dWhtz+gBCCuEn16IrZmViC4vRYCI4fQA3/2fjeHfB4sPEXacf+04fwNYHIOw/sp3FUTMhHL/JCZJeJ8Q7xEtjS0wiVu8cQi42OD4SyoEe88Mo0L3PVOfr3mWq87TFHhADvXsTtu/tNbc1HDwDdaa61vZISoMeTzV6XOqI7v7E2z8cYTVASPUlXLa5NTnH78BAfcL6Tf07DeV9A8YYd68aoCUQS0XQFjSmIIBIKGJnKHZt7ehPnAB4pydWH+/0HaI1mJxjs99j7g/AvkH1G3vMKRcAOoLDE0UaLzqDGn0ho8e2vz/5F39/KHF9a2/sYdfVa45s6OwZm2gHX6f5IZuo7kioPTp63ClUWkf2ANdazNeC1hI7cFpr3APXr6L3DXFgD4PeZr5etdquBHa95pWDYXSP9eC3OL4Jq8d+FJbFBKKndrx7MHwmUl8nMBPC8av29R3ZCCA/sSKQMCsWpidUDpE4PS0rcf0Y4y5YYFDZBEgtXmqyyyw92VSXM+nc2PKCpSTS7c0uWDaifuXlLDTVVZRFtpeXOQtb3Py54tzkt2OTnKTbE89pOG3SJ5Nqa076dKQE8/XOyltlKC/JnGYoFzoyKXfH5oFWpZpDbJyiTIEjFjJ5Um5lwj6syo3NFV2cVZzQZmZacnM45mfmICeY8LwkO9bOaQWJw4KmHuNhnoUukRK38Ra0ODf5kMjMBBHGogCVebHroShPRIq7PMqKxub2l15m3JAgQlpJ8iIxUp6AGHcK7VNGJjYjTXaZbg/iIAVVcZJxnq6QaUfINorxDAdxqnlOtTS3xGw3KcE1m+FGyJw4c1MtLMaCVMfIfuMWFgkpX3Fkm2OF3Krx7sFxwYRw/A7LlWdF/7Rffx3Y4l4cU1KwnxWzsZ17FWTHOYiSDdtN5pDDDwKbO4/SU2/HmTMTW1op+Sd8nvRJZ5rsiud+gqyy0xBEGUGyU1B1DZklMacmLauKGct+gCu1DFFyIdvSKJp8MZPmfW5E/Vq66Afk5ixEECRkycX8OV8hxR2ZA2m3pXLmkl+TnzWPVFcR86fdyMzKy0a0nc8u/QcO0fiyNyfvVCqzzGqkhyPDlsods28lVYp4AZIgcUPpJSzOMqqE3lR5BleWrKLAkckJmVP55ZwbDeItv5p3BXn22Nu2Q5C4a9HHDPPpLimZw/mFVdH3aBGBj1csYll2TNX1q9OX8ZHCKTjF2EO81JXG7xaYz+3hyHY4uH3BUoqdbmRBINNm59uz5jMnM6Yymud08rmpUw3v9QUOB3csSi69xgeNKAj8dHEai3Nt5DlFLip38Imq5OeJfmK1g7RBgrIuO1y7ykbaIDEUt0vg3JPt5GcLpKcKLJ8vUzVpbCaT50yVKF8p48gQcOcJTDvXjiN1BHknRYGMax3YKkXEdAHXMgn3SSPrs1jkwHZpPkKBHSHXhu3CXKTKmOMnn1qEtCQX0m2Ik1OxXTNpRLko5dNnIEzLj3jesoi0ajJShVmBV5pegrR6HjhkEAWE/EzsV540LvkvLY4PHrn52H8BtksCL3/1lPHuhsWHiY8/Ca6RqaB/oFz4JyuP3wfEhBF3sSavW1hYWHz4scRdksN6PlpYWFgcPxztM3LC6KcGH3kGDrSY6gendFAVJaLqGRo0N2XePBwfOTuurb9DbWxOmrDyTOwrjSMxuq6j7XgVrW4rQv4kpAXnINiMkv1qdw2hbY+AqmCfeylSnnmYWgt66N98N4GGdxAdaaTNvRZXZfJf9AZ69lL91v8j7G/HnTmNKSffjs1pDE9tq3uBvRt+hqYGAIGcklOYveKnCHF56loa19DW/DopqWVUTr0am90YT+YdaGTn7r/T3buL1JRSZlV9guysWaY+BUN97Kh5EI+vmYrCU6ksWp30fgF4Q908uvNntHn3U5m5gItmfBPHCBRCh8OrHdv4Z93LKLrKVSWruLjY+BVY1TX+XfMO9zasJaSr2AWJ/5v+Ec4qmmOwC6oKDzduY5+3kyXZZZxXWJVwtKLF7+Whxp0MKGHOL5rGvMyxS1C6o7eXO3bvxqsoXFpWxlVxCd0BXm/r5PX2TkrcLq4sLyYtfoQceLG5k7WdfVSmuri8vAC3bAw9Cmsaj9d3s6vXz4LsFC4oyzIlVR8uf9nl5fWWMPkukVvnp1LsHlmY00BQ5529Cn0+nbnlElUjzL/X06Wxf4+CIMC0mTIZmeYvkF3NClvWhFEC4EiB+WfYyYzLL9i5R6G3VsOVLVA4X0aym4+PZ69K7yYF1a/jLhfJXmpDHsHI4Gih1XtRN3WDQ0JanouYmXyo5yF0XwjlvVr0Pj/SjEKkKkul0GJ8CQTDzPj+i+PdjcPitons/PE5490Niw8bj94M2x4c714MjT0VvrIdXOMz5ep4Y8KM+A0nnUPw13eAahaHEFevxrY0Iikeeupe9L3bTDbSaRciLzoxWlbWPoL6zkOxNqYvx3Z+LBxUG+jEe9/VEPJGKmQHKVfdi5RVbmi3/alPEWozbi9r9fdJmTb8m3vQ28y2py4nklDz0OayWHBZTADF23uAjS9ea1o3q3AF807+bbTcUPsU2zf+NLY8Zx7LV98VLYfCHp57+TJCodi8SkGQOXP13WSkTzW0/fRbN9HRuyNaPmnB95lWei7JoOkat715Ht5QTAylOK2KLy5LrNB6NLzZuZNv7vi3oe5rUy/m8pKV0fId+17ikab3Tev+64SPU5UWS/fxne0v8GpHdbT8qUlLubHyBMM6PiXM1WsfpysUEayQBIG/LDqH2RmJc0seDX3BIBe88QaDpT++VFXFleWx6/F/zW3ctiP2wWN2Rhp3Ll1gaOehulb+uKchWl6em8EvFhnnxf58WxP/a+qNlq+ZlMNnq5JPhfLzLV6eb4yJjrgkePqsbOQkc8hpus6fXwrS1he7l129ws7s0uScP0+/xvNPBVEPin3abHDOxU7cg9In+L0ab9xvFkpZdbmD1OyIk9i6RaHuzZj6ZkaZyIyLjE5U/w6F1ueMCp22TIHKGx0IY5Bi4khojQOE/rUvdotJlXF8YSbCCOcbBf/xNnprTOjFdtF8pDmJ573GY434JYc14jc8Km99dry7MCxS7BI7fvSR8e6GxYeF126D134+3r04MqIdvtdxZDuL4yOdQ7FtmHnPEjh9ANq770b/1vftSGijrn/DWN7xmrGNfevQQzHFOeXAazGnD0AJoux7ybBOuLfe5PQB+PY8k7APQ9FT/wpgVPNTgj0EPDGZ9Ootv028butaQ7mp1rjtnq6tDHhiipgtrW8bnD4AXVeobzSmIejxVBucPoB9DU8fdj8S0dC3w+D0ATR79tA/KJXEaPFY8zumukebjHXPtpjPF8BdNbG0EANKiNcGOX2R9cyqq+u6m6JOH0TUQZ9vPZBUn4fLQw0NxOs9PlZvVDr9X5NR0XZHn4dary/Oxnjc13b20R2MOSiKpvNis/H6+F9j74j6/Hqc0qRfhffak1eSbO7RDU4fwKba5FM11NeoUacPIByGhjrjPaV+R+J2W/bH7Dp2GW36GjRCXmP/+rab71XhXh1/0/jIbqtbe4y3GK+Ctt8zora0tn6D0wegbmkcwtrCwmIwAyErpYnFKPL2H8e7B8NDC0HnxEi5MtGZEI5f89Hm9nAOUn6Il/Y7iOByx5XTjQZ2FwxKqi64MhO0YawTHamQQGlSTLDu4ZCdie1lR6yPDnfiEZd4xVC7wziULggS8mAxE0fibTnsxvUctnSEuH1z2pMfpk+xm1N1CIg4pOSSnA+HbLtZ5TLLbhSWSbMlDm8rGHSs7aKEWzKG/WYm+DiRaXMOq240KHSa202PC+PMtBvLkgBpNjnOxlh2iCJOSTSsk26TDrvOcHHJ5pGtXFfyI0xuu7kuxZH8qJnDaV7HEXdYXUOEYtpcsXrZZbQRpMjHzMFIrsTtDFU/1gjuBOcwZWSjfYLLZhYYTnSSLCwsLCzGFmf6kW2OFZJ8N7YYGRPC8Rs2JYlDieRLLo7+LZ51RWKbs4318qqrQT74siIIyCdeiyDFXo7kyacgFcdSHoh5VdiqjOGbkiubtAUfN9QJtlTSF954xF0ZTHb5GdhcRscus+Rkg8M2deHXEQTzy9uUBV8xlmfehM0WuxFMrvo4jkHOYEHeUgrzjfPeUlMrqay4wFDnduYyd8p10bLDlsGCacntF0Cuu5zZeaca6k4svxaHPPqy7jdWnIFbijl2siDxhcnnG2y+MtWsuikh8NnJsXmZNlHiM1OWIR58u3WKMp+ZbE5nsSCzgJNzY0qfZa50Li0dG7ni80pKKHDE9k0SBL42Y4bB5obJ5aQPcvSurSwjx2F8If/ElBLcBx09AbhparFhjp8gCHymqoBD0Yh2UeDmqpHNW/z8TOM5np0pMT0jeScyO1Vk+dRYH1MdcOKM5NupnCyRnRPzWHLzRcoqjM5PSZUcvS0cwu6CkqpB6q1LZQZ/FyhdKiPHzfHLWSEjxH1jSJ8j4cgbn1uytCTXkL5BrEpHrEg9zBpDI6S7kJbFUpvgtiGvmnK0XbSwOCoK0ybGx4czZ47+VACL45jL/zXePRgeRQsgJbl0VxYjY8LM8duwYQPB2+8yLRss7gIQ2rcP/elnQFEgPx/btdcg2o03fMXTi/rQ38HbC5XTsJ1zFaLdPGKi+/vRmvYg5lUgZJhfbnVdR23ZApqCVLwQQUz8hTzcU0OwaQOiKwtn+UpEW/LCJbqu0VnzAp6WteRMuYCMQnN4r67rHNjyB7qaXsPhLmHGkm/jTDU7w0p4gK6O90lJLSU1fZJpOUBX9za6ureTnlZJft4SRDHxi3SPpxqPr4minEWm3H7JUNOzmX3d65ibfxpFadOOvMIICahhnm/bSFANc17RYlJl80hdd2iAe2rfZX1PDSdkVfLlaacbUj4cotnfz35vF/Mzi8g4zEjejr4OvEqIE7KKkMdYrvh/TU10BINcXlZGSgLhFp+isKmnj2KXk0mpic+XJ6ywpcdDZaqLUnfi/Wrzh9nb72d2pptsx8g1ojr8Kk/XB6nKkFhVOHIxEYgkbO/z60zKE7EnGE0cDrqu096qIQiQVyAmFOzRdZ3arWE6G3SKpomUTJMR4uYlKkEdT7OGK0vAmUAgBkAL6QzUqqg+HWeRhLNgfL/D6aqOVutBcEiIpUf/4UXr8KD3+hErshGSGBW25vglhzXHb/j84/X9/Pi5PR/Y9kTiJ2kc3va+Ty5lRYJcmBYWR0WgD+46C7p2D2EgELkCxUgqHns66ArYXOBtP2ijgeyOpFwIjWwaQGRTEkguUA9G8kl2uOhvMPfCkbd5nHHcqHom5NQTTFVycQlhWQZNg7JSBNm8i4LdiVBYgt7rRHCmgJT4MAiudKSpS4bcvK5raH3NEdvuaqRcs8Oi6zq6EiDsaUbvq8M1afXw9i2+L4IIuorsykWUbOi6Fqkz2AjYHTmkZM7A4cxFURKHyMq2FGy2dHq7d+BOLUvo1AmCndb2tfgDnWRlzcKRICSzpWsjnoFWMtMq8Ad7R+z4BRQvgiBwcsVHccqJRxm84T6afLVUplbhkIZ2sloDnXSGepiZNiWhs6ahkW5zs9PXwM7+BpZmTzfZZNtTKHRlMEstYUl2ZcJ2AIpd6RTHhwQPIqSpPNm0B1EQuKRkxoiVL4dLVzBIWUoKZxYVYRvCwXTLMqvyDp/TJ80mc2L+4cN2C1w2ClzJJ1uPx6/CSYV2ph1hpK+mV8MpQ1Fq4v1SNZ2QqlOcOXKnD0BVYMCrkZ6R2OmDyO9s0nw7uWUaApicPgDZIZA16fChkqJdIG364fdbD+korRpSvoiYIBQ1atevofVqiCXSiMVhBElAmjI6YUFaax/YZKRpY6dia2GRLCum5eB8EQJDTKM75KgJwKFP4hIQb24TITwMj+6QiQzEzw4e7BS6ZDhtRgELK7KxsBh1nBlwxT/hsU9BfxsoftB1EGVAi/wNoARBC0OgE7BF3qPRAQmkFFA8gACCHVILIu0ED9Yd+sHoysF2iTiJkisSPacGITgAejhin1IAsgMqVsJMo/K+xdgyYUb8hqXq+cYbsHadabn95k8jZEQcl/COjWjP/ddkI139WeTSxKNfiVC7axh48GORH8mhNkoX4z7/1whyZORCDfTS/sznUXuMgh6559+Js2jB8LcV9rHl8fPQBjlytpRiZp39d2zOyINCVYK8/fhp6Lrx8ZJbejqzV/7MUPf2mhvo742IkQiijZWn/ov0zJjT+vo7X6S94z3DOksX/YCKslgo6+OvX0uPx7hfsyqvZPmcrw17vwD2dq3l/q3fJqj6sEturp37U6pyVxps3ml7kb/s+QlhLUiqnM435v6aqgxzgve/1j7I3fWPo6FT7irij/O+R74j5uRs7NnPLVv/jjLoG2yxM5v7Fn8V58HYvP6wn/Pe/gMqsd9Fls3NY8s/g0MavqOz19PNJ9Y/g3awHVkQeGDZJRS7zfMMR4NHGxr4w549KLpO7sHk7ZNTRxaq90Gg6To/2ezlleaImMu8bJnbl6Sb5v35wjo/fzfI/p7IcTy5TOIzi4wj+J0ejX+/HqLPryMKcNY8mVXTk3dKW5oV3ngpHH0GZucKnHGuAzHOsdNUnfdfCNHVGLmO8spFFpxlN9kdLaEalf7/htCDgA3SL7XjmGF2JsNvBlBe9IMGQqaI/cZUxNyRzc87WvSgQuiB9egHVV/FucXYL5yfVBvWiF9yWCN+w+OiP77Flsa+IxuOM/++YQmrZ1gfTCxGkbsvhppXx7sXh+emF6HcPGXGwsxxoeo5bBI4fQChZ/8X/Vt78dGENuqTyaUPCLzyU4PTB6A2biC8N6Z+6d3+X5PTB9D10reS2lbD+78zOH0A4YFm2nbH8rLsee/HJqcPoLNxDUo4pj7a3vp21OkD0LUw2zb+JFr2+ztMTh/Ahs23oWmR9g80vWhy+gB21j5EV/9eU/3heGbPHQTViLJkSPXx9J5fG5Zrusrd++8grEUUIL1KP/cd+IOpnWZ/O/8+6PQB1PtbuKfhCYPNbw48ZXD6AJoD3TzbGntp+s6OJwxOH0BP2MddNW8ltV8/3vlmtC8Aiq7z093JtTFcBhSFP+/di3LQY+kMBvn7gbFRDx0tNnSGo04fwNZuxZDa4RBrapWo0wfwRoPK7i7j9/dXdij0+SM2mg4vb1PwhZL/oLXhnZjTB9DdqdNUbx4aaD2gRp0+gI56jfba0Vfj9L4Qjjh9AGHwxqV/ANAHNJSX/NGhA71XQ3klMOp9GS7qpoao0wegbWtGresat/5YWBxiIjh9AF98cNN4d8Hiw0R3zbHv9AH897oj21iMChPC8St1HeV8k/5B0uJDpHwglNzLkjaQ+GVG87TFNuVtS2ijh30J64ciMCjdwmBCAzF5/gFP3ZDrhwK90b89fWa53GAwlk7BH0icRkHTgqhq5Bj1eqoT2gAM+BPv81D0BtoOWw6pQfrDvYa6zqAxLQFAe6gbPc5ha43bl7agsZ1DtAR7YjaBxLHrDf7uhPVDMTiNQ7SP/uTO+3DpDYUIakbHo81/lEq4Y0y73+wotfvNv80uv9mB6/TFpUaIKysaeAPJO37BBLeAAa+5HX+CuoB39B0/rd+4Hc2jo2vGOt2rm+LQ9L7xSQkBoPcnuO76xs8RtbCYaPitdA4Wo0l/83j3YHgMek+1GFsmhOPX6B8YnmECMQsAcfGguYB5QySanjQjcf1Qm6pKkGBVkLBNWR0tuqackXBdZ9mKhPVDUTjrYwnrsytiCpST534moY0oOXGnlUbLZZMuJf60F5eeFf07K3O6KU0DQE72fGy2SOjgzMrLMeu1R9I5FOUkN/o8r8B4jOYVGlU1nbKbhTmrDHUr883Km3PSplLkME6KPzPfuN6ZeQsS9uGMvFgo2rVlied0XlWa3H6dU2hWMbxojBQ9S9xuZqYb52adXph8QvUPkhX5dgZnbhAFOKXILO6yvEQyXGluGeYXGK/PuWXGcmGGQH568re2krL4ObNQWmH+LRRMkhg87VOUIL9y9EMrHbONbTpmSab5hEK+iBAnCiPNPfq5lyNFmllkvDU4ZMQpllKbhcVwWTHl8HOwLSySonQJkZmqxzizLh7vHhw3TPg5foNVPbVQiPDvfo8hXmvWLBznnxct6ppG6O47oKs9ZlMyCcc1n026X/63fkd41zOgKYg503Auvxm51Cg44695lZ61v0fzRkap7AXzyb/wzqS31bLzXpq3/R1dDSM7sihb/BVyKoxO04HNf6Rx7384NMvW4S5k3il/xp1WYrDrbFvHjs2/RAl5KSo7i1kLvmpY3u+pZc0bN6EoEYc7L3cxq5beHnX8ABra3mbtjjsIhHpw2DIozFnIvKkfIzO1Mqn9CqtBXq+7l7reLZRnzGV15cewxYm3+BQvj9f9m1rvHuZkLeH80muREgjSNPvbubvhcdqD3ZyVv4pzCk42LA9pCn+veZFHmt8hqIVJk138X9UVnJw722D3u/1reKRxIyo6LtHGl6aexkXFC5LaL03X+cXud3ixrQaAi4qn8+XpS5NqIxl6QiHurq6m3udjVV4el5aWDilOcqywp0/hoWo/QVXn4goni/MSy61valN5pVbBKQtcMFWmPMPs1K0/oLCzSSUnVeCUmTbSRpAPT9N0NrwboqlBw+4QWLzcRkFR4gdmd4tK/XYFBIGKORJZhaP/YNVVHd/bCuE6DVuxiPskGcFu3i+9XyP8WgC9W0WabUdecnTqqEeLur8DdVM92CTk5ZMRC5MTjLHm+CWHNcdvePQOBFnw45fHuxuHZW5xGk9+4aRRny9scZzTdQD+shKUYzT6onQF3PS/iBiMxRE52mfkhHH8rAebhYWFxYcfy/FLDuv5aGFhYXH8cNykc0iUww+Az1+D46B6oRoOo/zmt7FlohhR9EyLKSnqikLo2Qdg37aYnc2O7Qs/RJSMX+31/g6UN+9H72lGnLQIafllhiTuSstW/M99G93fDbITx4m34Jh9kaGNQNN7eDbfg66GSJ19Je4hwj9D/Q20v38nYU8jaeWnkDP346a8gB37Hqez+mlkRybFcz9JSs4sw/K2uheo3vI7wsE+RMlBRv4JTJn/Rdxp5YmP3RD4fK1s3fknOro2ga6RnTWbOTM/Q0Z6LHxRUQO8v+evNHeuJyd9Ootnfh6XY2QhKneu/zR1fVsAKEmbyeeW/hMxLoVCk7eGH2/5An3hLhySi5unf4cVBeZjubF3B/+uf4yAFuSyorP5SMFJ0WW6rvP/dt3Pqx1b0dBJlZx8a/qlnJG/wNTOfm87d9W8RUfIw1n5s7g6LgT0vw1beLplN33hAGmyg3MLq/ho+QLDKJum6/x81zu82lGLTZC4YdI8riybFb+pUeHPe/fyZGMjgiBwdUUFN0yePCbbAdjZ6+Nf+zvwhFXOLc3kwrLEEuTvdfi4v7oPRde5ojKDUwrNc3Uf2O/jn/v8KBqUp4r8dVUGTjl27re2qfxtcwhvCKpyRL6x3GbKhegN6Ly0LUxzj8aUAonT58jYRpjSYDTwdWrsfS5EsF9HlCC1UKRsuY3UQmO/B6pVutcroEPmCTJp08Y/HEdZ14G6tRshzYa8ugix0JjnUmsfQHmtDr0/iDQ7D2l5yTE/smxhAdDU4+fE21/hWP7UXZLpYM3XTsVpG/97gcWHiH+eA/XvjHcvDs/CG+Ci3413L44LJsyI37DSOfzq1wfzjgzCbsdxy5ejxfDLj6NtftfcSHoWjk9/21AVuvtr6F0N0bK07FLkVVcDoIf9eO46y6Ts6b7sr8hFkTljSn8TrQ9fBdohtU2BvAvuxFFolDfXdY0Dj19J2NMYrctb9Dly58bm9nXXr6H6re/E+mJLYe5FTyDbI06tt2cvG1+63rRbzpQSlp7z8JDJ5RPx4qvX0de/z9iOI4dzz3wC6WDag3e2/YLddTGF1MLsRZy78i/D3sYhntz1S9Y2PWKom59/FlfP+3G0rOkaN755GkHNKBzxt5UvkG7PjJbbg11c/t6XCOmxc/KHuf+PJVlzAfjjgWe5r/F1Ux/uPeErTE0tipaDapjL1v6V7nBsbum3pp8dDfd8unkXt+15zdTOV6adyBWlc6PlOw9s5N667QabPy86m/mZozv/7n9NTfxs505D3S8XLGBF3ugnAvaEVa54bS8+NfY7+9GCMlbHhfM1DIT5+JuNqAdvLwLw5xVFzMqMhfHW9Ie58c1+w3rT0iXuOikTgLCqceOzQQbrmSwoEPnmcmMo4z9eC1LbEevP0ikSFyxKHDb6QbDhb37UkLFOtMHCjzuRD+biC3Vp1N4djCXyEqD8ow6cheMX6qJs6kJ5Kna/wy3huGU2gi3SJ13RCP5xPXhiOyefMwV5cfGo9sMa8UsOa8RveEz9v2dRxk/3aNgsn5TNgzcnpwNgYTEkj34Ktj003r0YHt/tBHn85qhPFI6LdA5FjmGqesY7fQChELo3ls5A27vNbAPQ32Mo6r1tBqcPQDuwMfq32rLV5PQBKAdei/4daHx3kNMHoBOoN0v6B3urDU4fgLfhTUO5t/ENQ1kND+Bpj8k+d7UkThUQGGhioH9oFc54fL5Wk9MHEAh20d27I1qubzP2p7X7fUKD0kYMly1tL5rqdnUZ973JV2ty+gDebn/BUF7Xs8Xg9AG81R07Z692bE3Yh7e7dxnKO/pbDE4fwFtdMTXUNztrErbzVmetofxKu1lp9dnm0U+z8GyzWbXrqaamUd8OwPtdAwanD+Dt9n6T3boOX9Tpg8is03fbjefwsRpz+oZqT0zRbn2LRpyIJXu6jNsOhHWD0wewu3n8VPGCHs3k9EHkVtHfFOvnQI2KIbOIDt4D46vmp+2Jk7v3qWgNsd+B3uIxOH0A2t7k1G4tLMYDXdcnhNMHsKHO+k1ZjCJ7XziyzbHCmh+Odw+OCyaE49cSHKaq51C4BoUrZQ8xChI/IpaSCQ63oUrIjn3ZFjPLEjeTHQuxkzMqTMsT1dlSChEk4yiGPc7OmWZezzkohNOdYDmAKDlwuoc/wuRwZGGzmcUYBEEi1R1TB81IMW7P7cxDll3xqx2RbJd5tCDDUWAo5zjyERKoiE5NM4ZNlidoa3BdmTvxua9wGetLXZlIcdurcMfCWMvdmQnbia8vc5mPY1Xa6Cu2TUqQqH1a2tgkii9PMY+klaeYxUTKUsxf7eLr5uWYI81TBiVwn5plvj1lOo3nxS5Detxll5s2frc1m5tEgrcAODNjC2wJ9s2ePb4hk0KOM64CxOzYuRWyXBH5VcM6yf/mLSw+aCZSOHJ2gnushcWIyRjdiIwxZc7l492D44IJ4fgNm7PMMv/SuecgDJq7ZzvzMkigCCldfKOhLNgcyKd/CuyRFxshuwT5xGujy8X0YmzzrzKsIxbMMaR5cJYsIWXW5XAwPYJr0mm4p55t3rY9lcJl30CUI46mI2sqeQs+ZbApmHEVaQWRkV1BtFE899O4Miqjy3NLVpNVsMzYsGhn6sKvR8NBh4MkOThh/q3IUmyUVRTtzJ/9ZVyDHKRls79CqisSHumwZbBq3v8hJkgDcSQ+vuC3iELsfAiI3LjwtwYbt5zK5ZWfNtTNy1rOtIy5hrr5GTO4uuQ8pIOX9Uk5izm/cHV0+XeqrsQlGh+qK7NmmFQ9853pfGHKqdgPXiez04u5rix2bK+vWMScdKNzOiMtjxsqjIqut85YQYYt9uJclZbDRSXTTcfgaPnCtGkUOGMv7RVuNzdMmjTq2wGYlObkxql5yAdfpE7ISeGyCvMcv6W5Li4sS0Mk4gedVpTCaUXGkfvTSxxUpMRuQQLwg0Uxm/wUkZMGpWqwifD5uBBOURC46AQ7roPVmW6BcxaMX6iIKImULIm7vwhQskTGnRPb15TJIhnzpKiTmDZDIq1qfOf1yCfmI5QdPP6ygHxGMUJm7HgLqXbksybDwTmYQnEq8omJP4BZWBxrfPWMaePdhWFx18cSpxSysBgR1z6U8J33mENyQMmC8e7FccGEmeO3YcMGgr+/CwZFiw1O5XAIXdcJPf44uN3YTz8dIUFuP13XUJpq0Ta9AxnZOE4+d8ht6+EAurcHIbMw4VdDzd+L0vQ+Ul4VUkZJghZA9XeDpiCl5B92P7WwD8XfhT196Jep4EALkuxGdmQkXB7wthAMtGOzZWB35yHbhhkmG4eiBPAH2gERpyPTkMoh2l9dxTPQRIqrAFk6Ogn5ra1r0HSNBUVm5/0Q/vAAG7veZEbmAnKdQ49i9oT6Ceth8ocQm9nUc4DOkId5mZUUODKHbMerBOkL+ylxJbZp9vcjCyIhXaXUlfh8AOzs6yBVtlGeMvS2RoO9fX1IosiUMRrtG0x/SMGnahS6Dv91ujuoouk6uc6hHzzV/Qq1HoXVRXbEBHLOPX6NJq/OnLyhHaOwqtPn08lOFRCPga/7SkDD26bhyBCwOcXo3D6T3YAOOsip49/nQ2g9QQSXhDDEOdODCrovjJg1NqN91hy/5LDm+A2fgaDC1x7axL42D72+EKkOG7lpDsKqhixAU7eXoKLjC4Oqg00Ct11AUXXSXHZ8gTC9wcg7kw44RZBEUBXQBSjIkOkPqEhCpA1FiXzbmZzvosPjp8cPaXbITHEgS9DlCeIPQUm2kxtXTeajyyutVA4WY8PuZ2H3i3BgDQS9MPlEEB1Q/y4ggDMDFD9ITkjNBdkB3TWRhLY5U0Gyg78HRDu4s6G3HmR7JH2apkJ2JdStA8UXmXZVMBNScsDTCf52EOyRdBI2J+RNg/428HaB4oUL/gjTThnvIzRhOG5UPQGD0wcRpc945y984AAcqAZdJ1RTi/2TnzA5f6G9O+DpeyMF2U5o3nLsmYmVCfXWavS+VgSbA1KNNroSQG3cgNZTi+7vQ5h0ImKqMWxQV8P4a14j3LkH15SzcJYYR4UGI9rc2G3uhMs0JUBPw6v0taxFEB0UVF2FO8uYJFxV/LQ3vExP+3tk5i6ibMZHE7bV3bmZAU89uQXLcLkLEtoIgkBvX2SuX3HhiQlt6lpeZXfd42SlTWFR1aexJ3AOh0tZxiz2d79Hfd82yuNG8gB29Gzkyfq7ybLnMScr8RfR3Z5q9nhrWJQ5mzJXYscwrCm831dDR7CXWUM42Hs9bfx+/xr8apjry5cP6fgVu9LZ1NNMU6APpyiTm2Au6saeFlr9XpbnlCZoYfToCYXY1tdHeyDAfL+fZXl5SGPoAKXbZQ6XnS2gaNxX3UtfSOO6qUM7xbt7Ffb3KyzKtSV0+gBq+jTea9boC+qsLJESfoCxSQK5aUe/v5qm09qsEQzqlJRK2B0ja1OQBNQQ+LvAUTm0nZxy5PZ1XSdco6H169inSYhx6+iajrZfQR/QkKpsCO6RBXLoPgXlvQ70gIa0JAdpCMdPcMgIjqEfHbovhLKpHn0ghLSgFCnffKXoqoZ2oAXCCuK0YgS7NaHfYuz56TM7eH5HLIdvl0+lrmfo3GaqCgF/xNHrD5kn7wY0YnN1dajvVUw2ALsHzW/uC0FfyDi/uborwPee2onLLnL54sTTNiwsRkznAXjqy+DriNXtftpo4x2kM9EVt363WffBRGOcamht29C2bVsAAQQx8v/A85bj9wEyYUb8hqPqGX79DbR160zL7V/8AsLBeX6h155F32BWdpRv+jpStnFELvzyXWhbXzpo4MB2+XcRi6sA0INeBh7+BFrvIAEPyYH74j8iF0UcF10J0vroR1H7Yz+o1DlXk7niliPv9CCUkJddL9xI0GMUm6lc9v/InRJJTh8O9rH++asIB2MiNTZHNsvOexxJjoUB7tryG2r3PwiAKDpYfOJvyMkzOqPh8ABr3rgJj7cWgLTUSk4/+Z/YBo0ertlwK3Wtr0bLomjn8tUPkeouIln2dq3lns1fQ9UjD83VlTdw9tTPRpf/t/pOHq//V7QsIPKTRf9kSvrMaN099U/w59r7AZAQ+fHMWzgtb7lhO6qucf67P6b3oHCLAPx23idZmhULv3yqeTM/j5sMfWbeTH44+0JTv2/f8zpPNkfUNJ2izO8XXMCcjJjDeduut3mmJSIK45Jk/rDwbGam5w7/wAyTfR4Pn1u/Hr8aEwdZmpPDrxcuHJe5LUFV4+I19fgOqruIRBQ9Z2Ya55Ddvc/Hv/ZGXogkAX50QhqrCowjiH/ZGOLNxth+zc0T+fbKsUlQrus6r70Yoq0l8ibncMKZ5zlITXLOoBLQ2f5wkGBfZP/duQKzL3cgyiM7F/2PhghujxwDwQGZNziQB6l/Bu/2oO09+MLpFnDcnIaYm1zYqNYRIPS3PaDEnge2KyuRZmYm106nl9A/34Fw7JzJ585BXhj7yKKrGqH/vILefFDEIt2N44YzEFIi14c14pcc1ojf8Djp9pdp6DELSh1rXH5CMb+6YuF4d8Piw0L9WvineYrRMUd6KXx1x5HtLI4PVU/nMLuZyOkDCL31dvTvRE4fgPLQ3wxl3dONtvXlQQZB1PeeiBbDe543On0AapDQ+/dEi/66NwxOH4B3x8NooeTEarrrXjA5fQCNW/4c/bu19lmD0wcQDnbT3vBStBwM9lB34OFoWdOCHNj9b1O7DU0vRp0+AI+3loammPpmMOwxOH2RtkLsqPnvsPdpMK9U/yPq9AG8WXcfASWmEPpM430Gex2NR2pjeR3DmsK/Gx6LllU0/ln/KPE81bIu6vRF2oHfH3jGYHNnzRvE81LHLvrCxuHmtoCXp5pjKRQCmsK99TGV1Wa/J+r0AfhVhf/EpXYYLe6vrTU4fQDvdXWxtbd3TLZ3JB6o7os6fRD5IP7HXUaluoCqc//+2DFVdbhnn89gMxDWeavRuF/bOjTaBsZGnq+jTYs6fQDBAOzbnbzSZsduNer0Afg6dbpHqNipdGpRpw9AD4Lv3dhvRatXYk4fgE9HeSf5l1vl7TaD0wcQXtOSdDvqulqD0wegvLrHUNYOtMScPoB+H+rm4SsPW1iMhIng9AE8stGs0mxhMWIeMqf5OibpbwRv+5HtLI6aieH4JZinlxTBYdzwlbjUDEoI4lK96uFYO7qSODxEH+QgJLTRVfQEaSAOhzbEtjQ1OMjGnO4AImkfYvYhdN34Uqaq5raVI9RpQ/Q/rPgS1h+JsGY8P5quoA5Kg6Hp5pfmwKBtqbpKMK5PgQT74Ambj1FQNa4X1hK/oIc0YwhPUFNMiYADqjJoeYI+q4nDgI6WgJq4z/HO4AfFQALd9GBcCghV0wnHHcBAXHcVLf4XeLCtsTmMKAnaVeI7OQw0xbxOkj/5KHqC1BB6KNa+nqh/I+gz4USpcJJ3sPVwooMY107IbJNwPQsLCwuLo0OZGB88gMgcQIsxZ0I4fr3hYV64U6YkrLafNGiOWsUQqornXG0oClmFCBWDE60LSAtiw+W26WeBwzx3xT73sujfrspTEOzGeW+O8hORnJmJ+zAE2RVnItnMgh3502PStwWV5yCIRgdZEO0UVJwT64+7gPyikww2FZPN8rllJWdit8fmZdntGZSVxERXXI5sstPjj6PAzMrLGAnLS419mFtwBimDErMvzT3VtM755ddF/3ZKDs4vWG1YflmxObThipITscUpj15XZlzvkmJziM3M1ELyHMbjX+7OZElWbN6eAFxaElMHnZSSycJBidoF4JLSKlPbo8HFpaWmDAIVKSkszk48b3WsuWZyBlJch66fkmkop9hEziwxhmxeXGEMBc1wCFRlG29RhSkC5Rljc9sqKBJJS491XBRhyvTkp0HnTpeQBkWs2tyQNWVkip22YhG5dNDBFMC1ONYncZKMUDDoeEggLUk+FFZeYk51Iq0YIvXN4dpZVG5KZyHGzVkSpxVD+qC5zDYZaW5l0tuysEgG5/iK5g6beSVjL85lcRzxkdvHuwfDQ3ZCZvmR7SyOmokzx+/JJ+E//zMtixd3CT7xJOzdGy0L116DvdQorBF8+B9QNyj86JTzcCwxTyzVw0G07a+i97UiTl2KWGrMG6f1NxPa/jhq5z7ElDxsM85FLjE6DupAB33v/Ylwbx3OypNJn3cdgpT8CGbQ20zrrvvob11/UNzlcvKmXmSw8Xsa2LfpDgZ69+LOmELVCbfiTDXmcFHVII21zzDgraOg6GRy8hOHCQ/4WqipewqASRUXkhI3d0/Vwryz7Rc0tr2N25XHiXP/j5zMkTs2e7vWsqfzbQpSp7Co6DzkOCf2weq/8HrrM7ilVD4+7WvMy15q7I+u8VzbG+z11rAkay4n5STeryZfF7/e/yS9YS/XlJ7EmQVmR++B+ve4t34tiq5xRv5Mbpl2ejS1w2ACaphnWnbT5O/nlLxJLMg0Hmu/GuaZ5v00BzycmlfJvMzDq7oeDdt7e3msoYHOYJCFWVlcWlZGhn388kHVeEL8cVcXA4rG9VMyWVVgFr5RNJ0XGoNUe1QW59pYUWDur6LpPLQrzLYOjWlZItfOtuEc4Vy54RAM6FTvUwgGoXKyRGb2yJzMQJ9Gx04VQYK8WTKOo1Dt1II6gfdVtH4Nx2wZW6mxT7pfQ9kQAq+GNN+OWDwyzS61cQDltVYIqUhL8pDnZo2sneZe1Df3owfCSAvKkOaVmOaa6l4/6pYa9LCCNLcSMSf2Ec2a45cc1hy/4bPgB8/RGzh2M7kvLE3n8S+cdGRDC4tkeOt38PL3SRxDcwyQWQ6fXx9R/LQ4Ikf7jJwwjp/1YLOwsLD48GM5fslhPR8tLCwsjh+Om3QOwdvvSrygKBfHxy4BQA+FCP32dyYT8RM3YcvJOWgTIPzUf9Br9w4yEJE/810k98jTERwtTW/8gP6a5wEQ5BQmX3Q/9tRYqgVPx1b2rvn8wfmBAkVzbqJknnG0s6dtA9ve+DL6QaEUh7uQBafeiTMlNlrX272d7e/fzoCnlvyiE5mz6P+wxSV413WVLdt/T039U9jtGcyb9QXKSs6Is9F57f3vUtOyBtDJz5rPR5b/HllK7otNq+cAv1t3raHujEmf5vQpnzBt77att7CtJyLgc0LOyXx97i8MNmFN4df7/8nz7W+S58jmlskfZ1XOIoONTw1y86Y/s3+gBQmRy0tWcsvUmGJnQA3zy70v8krHboqcGXx12hkszqqM247Kt7c/zztd9UAksu2sgmncWrUahzR+P6kmn4/bduxge18f87Oy+PasWRS6ks+1Vj/g5/YdtezuG2B+dhrfnj2JPGfyo4c7egLcsaOL+oEwK/JdfHNOHqk242jVQFjjV9sGeKstRHmKxFfmpDAn2zja+9ieME/sUVB0yHbCN5Y7qBgU7vnazhBrdsQmCIoCnDNfZvm08UkR4OvWqFkTYqBDJ71UZPLpduxxKRg0RaflmRAD+w8qiBYIlFziMOTz0zWdgRfDBDapCG6BlDNknLNHdn3puo7ySg/Ke/1gF7CtzkI+4XAJORKjvNWAsrYRRAH5xDLkpYlzl1pYHGs8t62Zz9636ciG48yPL5zB9SsTT1uxsEgaJQi/ngH+7iPbjicX/RkWJk5BZjG6TIg5foelpTP6Z+gvdyY00f7xz+jf6lsvGp0+AE1Dufs3Y9K94eDr3Bl1+gB0ZYC65z5tsNn3ypcHicLotGz/B0qwz2Cz7a2vRp0+gKCvlZ1rvxcta5rC+2tvxdO3F00L0dr0Cnu2/8nUn+raJ9lX/SCK4sPna2Hdxu/h8xtzsuytf5Kalpc5FDrQ3rOF93b+Pul9//P6T5jqXq75G+0DNYa6x+v+xdaetegH/23oep0XGx8x2DzQ+AxPtL5MQAvS4G/hO7t+Q3/Ya7D54a4H2T8QUStU0fhv01ts7auNLv933bs817adoKZQ6+viOzuewK8aFTb+U7cp6vRx8Ai80LaPe+vfT3r/R5Of7NjB5t5eFF1nY3c3P9+588grJWpnWzXber2EdZ0NXf38amdt0m0oms73N7Wz3xMipOm83urjb3vND56/7/HzakuIsAYHPCrfe9+DosWiEHZ3qTyyW4kKTnYH4JdrgxyKVOgd0AxOH4Cmw7ObFdr6xieka/8LIbxtOroGffUata+bFVq61ylRpw8g2KbT9qLRLvC+in+dih4CrVfH81gYtX9kERrqjgGUN3ojicf6VcJPd6K1J1COOVwb+7tRXq0FvwIDYZQXqtGa+kfUHwuLD5qJ4PQB/L+ndo93Fyw+TNx76bHv9AE8+flI4neLMWdCOH6FzmGOWgxDvVNtrEm8YMCbuP4DoP/Ac6Y6xd9pKGuqWZHS0745Zh8eQFfN++/pjuVF8ftaCfo7DMt7uraa1uns3mIo67pKd48xv0pjx7um9Vq6NprqjkRYS6xGWte7zVDe0r3WZLOx+y2jTb/xgRnQguwdlJYCYGeCtBhvdMX2bVufMf2GRwlSM2A8F+/1GG2i2+9tTVj/QbE9Ln3DSNI5hDSN3f1GddZtvcn/Nlr9Ch3BuFQMCRIlb+8xyl12B3WafLGb/94u84OgOwCegz7LgfahHxT1CdYda9SQjr/L6Jx5Wsz98DeaFVf9TUa7cEPcehoojSPbJ60+7tjrCeqO1EaD2cnT6i3Hz+LYJ5xAadjC4rigdcuRbY4JdOipO7KZxVEzIRy/1kBi58CE48hqdlJpZeIFbrP4xAdF+uSPmOpkV46hLCYIoUzLXxCzt6UgiOZwvLTsWJJzl7sQh9Oo1JeVPce0Tk72XENZECSys2Yb6kryVpjWK8xOPumsLCQ+Z+UZxn7NjRNzAViQvdJoE6c06hDtTEutNNTNTDMK/QCcmB0T7ZmTYQxdS5UcVLqNSdcXZyUOb5s7KHn7eDA7I8NQnpuZmXQbdlFkeprbUDc7M/kQ6EKXTI7DKKM3J9N8Dc/OMoYuZjkEit2x29K0BOIqWU5IO3ipT8kfWjSlLOeDv71JdgFXtrFPaYXmfrhKzBKDzmKjXbyICwLIJSMTiRHLzMc+Ud1h2yg1h4aKZcmHi1pYfNDY5AnxqmNhMfoUzD2yzTGBAFkVRzazOGom/t0wO+aw2T/7mYQm4o03RP+WVp2NUDHNaCCIyB/7ylj0bli482aTVhlLlyDILio+8leDzdRTfzsoXYNA4awbkB3GF/05J/4aYVC6Arsrn5nLfhwti6LMwuW3kZY+FUGQKCg+haq5XzD1Z3LFxUyddAWS5MTlKmDpou/jdhUYbKrKL6Si8FQOabfnZc5h2exbkt73zy75u6nutMqbKEidbKi7tOImZmcemssqsCjnRM4pvdJgc23pBVxQcCp2wUaJs4Afz7yFDJvRafnBzGuY7I7si4jA5cUrWZA5Kbr8hooVnJU/C5sgUe7K5sezL8ItGx3q6ysWsSy7LFoWgDPzp/KxiuQd39HkO7NnMzczExFYkJXFrbNmHXGdRHx37mRmZaQgCbAoO42vz0r+ZiyLAj9cmM+kVBuSACcVuPl0lVkl8pNVbk4ptCMJUJkq8cNFadjEmHMzM1fikulyND1EpgO+scwRVYnMTJE4dZbRiTo0x69wjNI+HImpZ9tJyRdAgPQykcpTzB9kspfJpEyO9c+RL1BwltHOeYKEa6kENhDTBdIusSGNcJ+kOSnIJ2aCQ4BUCdsFuYgJVFQP28a0bORTKsApg1tGPmtyQmfQwuJY5A/XLBjvLgyL7547Nml/LI5TPvYEODLHuxdH5oLfRXIoWYw5lqqnhYWFhcUxg6XqmRzW89HCwsLi+OH4UfXs7oa7HjXVm/L4/fNf0DloTlZZGY5rjMnZg/f9EVpi4hxMnY3j4o+PqF+6rqHsexm1bSdS6SJsk042LFcDffS+82uCrVuR04vJWPI5HAXGMEYt7KNrx/307H0CXQuTXnEahcu+jiBKhu207LiHjv2PI9lSqFj8DdIS5KA7sPl3tNW9gK5r5JaeyrRFX0NMkIPucKhqkG0776Sp9TXstjRmTr+J0uLVSbUxXEKqn/VNT7Ovay1OOYX5hWczM+/EhLZP1P2bdR2vUJlaxY3Tvo5dMoeJPtP6Go82v0CRM4+vTbmJnLgvXa2BHu6uf5WagVZOyJrKtaUnkyIbQ97aA/38et9LdIUGuLpsCWfkzySeTb1N/L1mAxICn52ynJnp5hx999Vt477a7QR0lckpWXxl+hJmZ5jtdvR18Vp7E4VON+cVV+JMoAzaEfDzbHMDGjrnFpdR6DSGYzb6fDzZ2MjG7m40XefMwkKuraw05U8bDfb1+/nh5kbaAiEybDKXV+RwSUU2Dsn4ta7WE+LFZi9pNpHzStNIt5vDG9e1B7nvQACHKPDpGW6mZZj3fX2zyu5ulWlZIsuKpYT7tLdFZXuDij+sU5IlsHiyjVTnyPa9u1OjvlbF7RaYNE3CZjO2s+ONIK3VGqIEUxZLlM2wmfrU36zSvl0l7NfJLBfJnyMj2Ub/XAAo24Io74YQnALy2U6kgolxW9dDYdSttej9PqSZZYhF2ePdJYsPOVNvfRblyGbjxuzCVJ69xZxT2MLiqNj2MLz4PfD3gDLMqVMfJOml8Lm14Ew7sq3FUTNhRvzevuLmIZcfcv6Cf7kTPB6zQWkJjmsjKQOCd/8GOlrMNjMX4jjvmqT7Fnjzt4S2PBjry8rP41h0PQC6EqTl/gvQgkYBhNyP/BZn2fKIja5T8+wnCHYZFRiduXOZdF4shUX1Oz+iu9aYwL7qzL+Sljc/Wt78ymfo6zQql6VkTGHx2fcntU8vvfZxevuMQinz59zC9CnJH58j8dcNN1Pbu9lQd+60L3NShTHFw592fZ8322LKpwXOEn63/DGDzd31j/GX2ti5SJFcvLzy39GX8s5gP9es/xVeNSZqMcVdyD2Lb0EUIk5LWFM5663fEtRirwffmHYWl5TEnOwtvS18dtMT0bIA/GfJVUxKjb24/mHfeh5sMKtq/nnRR5ifGQubXdvVyjc2v8kh6YGFmXn88YTVhnV6QkE+vvZ1ukMR8Z4Mm427l68m1xFxWBsGBrhp7Vr8cYpYZxUW8r25oxvf3+wLcfUb+0z1S3NT+dXiWEjo/v4gn323hdBBhc7yFBv/PLHEEMb5ekuQ778fE44RgX+cnMGktJjj8tieMI/sjp2LC6bKXDPbmKbh3X0K/9tsFInJdAt88WwH9iSTvbe1qLz2YohDt8WcPJEzz4t9YFj3VIDeVuM9s3KeRNXyWNhk136V/c8bFTPTikRmXXbkOcjJEn4ngPLsoAe5AI4vpiMWmJ3sY43gPWvQm7oiBUHAdvXJSJUF1ohfklgjfsNjyrefRT32X3coyXTy9q2nj3c3LD4sbH0YHvvkePfiyIgyfK9rvHsxITjaZ+SECKjNsg0zH1cipw+gsSn2dyKnD2BX8lLPuqoQ2v64oS609eHo34GGd01OH4B3ZywNQaBzp8npi9RvQwtH1BU1TaG79nmTTfNWY27DeKcPYKDvAEpo+KqM3oEmk9MHsPfAA8NuY7g0e/aanD6AdxseMte1rzGU2wJNtPuaDXUPNRmP0YDq5+VB6qMvtW82OH0AB3ytbOuPKUk90bzZ4PQB3NewzlD+e+16Q1kH/llrfPF6vGmPaR8A7q83qqM+1rifwe7apt4ODniNaTpeaWuOOn0AfeEwL7bGrun/tbSYnD6ANW1tprqj5d/72xPWv9fppWEg1sdnGjxRpw+gfiDM+k7jl8Z79xvLGvDgAWPdC9XGc/FijUL8x6q1+83f8Ht9OrubzcqZR2L/boXBzXd1aHR3xo5tvNMHULddNfSpbau5P54WjYGO0VcWVN8yq3Uq65JT6xwPtJbumNMHoOuo7x8Yvw5ZfOiZCE4fQFPvsf/7tZhAvPKj8e7B8NAUaNo83r04LpgQjp8//EFIMY8gDEsQQDI6pcKg8ENBTvyFfzg2kYXiwZ4J0b8HY1b6THw6B4eMHglJTOxky+Loj1bYhmjTliCEUxLM+2CTjOIUcoKQ1hQ5lgrEISXeN8egfU6RzIIXNsHYrjPBdlxx4ZlygvOVaF1HgnMTX5fYRkz492CkMQjzdEpD3zLsg/uUwM4hCoctA7jiRujskrFskzCFVdqGuLxtUvL7LyUYIZSO8PMRRWOfhoqsTjLiengkGtG0j01I6agiJzioieosLCwsLEZOgvepYxb7+KnrH09MCMcvwDC/3JckltlnQSwckunzEtuceHZynSLiUDmW3Di4AsfSWEJyR8lSpPSyuJVk0uZfFy06s6aSWmaO6U+rPBPx4NwzQZQonPWxOAuR0oVGRc78CvM+ZBUuR5KHmQcRcLnyKS48yVQ/e+bQobYjJS+lgvkFZxnqBAROm2RO6n5OqXGe5vT0eWQ5jGkWPlNpDEUtdOSyclCKibPyF1DkMCpLLsuazoxBKR7OKZxDls04f+7zU1bHlVcYnCqbIPLpScuMfZlinn8pCyI3TDJef9dWVOEa5FmcVVhOqduoRHpaQTGVKbG6UncKZxXG+nxBSQn5CVKZXF0x+tLIn5iWTyJ/6vzSTApcMQf64vI0suyx28uCbCcLc4wfKj4702X43OIQ4dopxmv1sirZYHNZldl5Xz3TZvpsU5otML0o+dtb1WwZedAmyipEMrJi7RRNM7c5bYnRoys+QSb+O0XONAlX1ujfbuWz437bNpCXJ5emYTwQ8zIQZwxKrWKXkZdNH3oFC4ujJNUxIV53WFppVj+2sBgxF/5+vHswPBzpkDftyHYWR82EmeO3YcMGgrffZVpmEnd56214551YxVln4Rjs+AHBDa/Da8/GKs6/DseMIRzCYaC27ULt2IVUvBApe5Jhma4peLc/gr/xHexZU0ib/1GkuLxwuq7haXib7p0Pooe9ZM++lozJZieur2U9rTv+jezKpmzhl7HHtQPQ3vAyzfseQdMUiqZcTNGk80e0T/WNL1LX8CxOZx5VU68jPa1yRO0cCV3X2de9jpqeTTjkFGblnUx+SuJtbetez2utTzEjYyFnllya0GaPt4YHG5+lwl3M9aUXIcWNlgXUEM+1vc8eTxPLs6dzcu7s6Py+Q4Q1lXvq3qUl0Md15cuoTDEf567gAP+q3YgsitxUuZh0m/lle1tvO7/b+x79SpBl2SXcOGk+2Q6zE94Z9PNOZwuFzhSWZOcnFC8JqipvdrSioXNSXqFphHFAUXijrY0tvb0ENI0LSko4IXtsxDK8YYVf7WhhV5+fihQ7V1Rkszg3zdRvT1jlrTYfaTaR5Xlu5AQjfC0+hQcPBHDKAtdNcZKWQACmvl9jb5fG1CyRyszEL28dHo29LSqBkE5hpkRVsZhwe8Mh4NdpaoiIuxSWiKb9at6vULNJweaE6ctsZOab+xz0aHTtUwn7dDLKJDLKze2MFmq7gvpOEFIEbCc6EVwT4wVX13W06lZ0jx9pahFCauS3Yc3xSw5rjt/wufrOt1lb2zve3RiSr505lS+ebqVzsBhlOvfDs1+B/mboaQAteOR1PjBEmH0xXPGv8e7IhOFon5Fj7vgJkcRyG4AmXdfPFwRhEvAgkANsBK7XdT10uDaijt+/74e2gWh9vNMHkZeJ0MsvQ08v0rnnIKcmTj4d3r8Tbes6mDoLx7xlCW10VQFPF2TkIQwRuqerCrq3FSGtaMiQynBPHYHmDaTMvBjxMGGXSqAHANk59Be/kK8DUXYg2xPnz1IVPwN91SBIpGZMQkwwzK/rOn5fCw5nDtIQYQCK4qe57R2c9hzycucl3P9gqB9VC+F2mh2jZDnQvYGugQZm5p9CmiOxw9IVaMMlp+CWh04o3hvqp8Hfyoy0ydiGiK2rGWinOdDJ8qwqk2M4mP5wgKAWJs8xcqWpzqCPVv8AczLzDmsXUBV6QkGKXCMPdagfGMCnKKTZbBS7XAkdDV3XaRjwoSJQkeJCTGDTEwzTMBBgblbqmDkrh+gPaezoCTMlXSbfdfhQvy6/jksG9xDqmANBnX6/TqZbwDWG4Y6qohP06bjShCGPj6bqeFs13HkCsn3sHTHdq4EIgnvobemqjt6nIGTKCCN0ij8IjifHbzSfjxZHRlU1TvvVGpp7QrgcEApHIoz9YaJxRSkS2CXoC0XmHWfYwS6JaOgIOoRUHZsEAwqggNMu4LRF6h2yTJ9fIcMpogkSKXYRp10koEC/L4g/pJGX7kDVNDq8kY2KYqQPZ80u5LbLFmCzQp4txoIDr8Km+0F2g6cFNBVC/aCEoOQE6KmB9t2QUQbO9IhN4TxIK4B9L4IgQ+5UQASbHTQdBtrBnQutWyNqoaXLI+14mmHuVdDyPng7ILsSemshvRxCXrBnQn8tzLkK6t+EC38HqWbFc4vETATH76vAYiD94IPtIeAxXdcfFAThTmCLrut/OVwbw1X1DO/ahfb0M8aFBQU4Ph4Lk9S8fYTv/KmpDdsnvoGYFXs51+q2En7uD+Drg4wCbBd+AzGv3LCO0rQJ/wv/D93XiZBWiPucnyPlzzDYtDx0FWpfTDwkY+U3SJt9mcFG1zVa3r2Nvv2RUciMKedRtPLbBmdLUwJUv/3/6G16E0GUKZj5UUrnf9a4rZqn2bvhZ6BH5kQKoo2Zy39CXunqqM2Ap56N736DAU8tNns6c0/4LgXFxlDTvQf+y5btd0TLomjj9JP/SWZGLBRrw+4/s/3AfWi6QnnByaxe9BPkEcSSd/ubueOdK1H1mCrj/IKzuXpubEKyT/Hy6+3fYkfvBmyigysrP8UF5deb2vrZ3r/yVGtEBMYmyNw262ucmHNCrB01yMc2/IamQHdkvxC4ffbHOTHXnOj8r9VvcF/DOhRd48Scqfx41oVDzhEciv/b+iqvd0bShrglG/9YfB7lKRkmuxda6/j17vcZUBWmpWZy+/xVFMSlazgcflXlk+vWUTcQ+yhS7HLxiwULqBz04aPR5+fLG7fSHoi8R2bZbdyxaC5T02LO5i931vJ0YwcAdlHg94tnMCtzaEf7aPjzzgEeqokJGczIkPjN8gzTPD9/WOe360Ns69CwiXBJlczF02PnQtd1nno/zIbqyKubAJw0Q+LMucklKB8O7bUq218PEQ5CSqbAwrPtpMQlVe/cq3DgpXBE9QcoXSZTsiS5a2e46KpO+JEB1G1hEEBa5sB+vvnaUesChB5uA4+KkCFhv6oAseTYDAk9zhy/UXk+Wo7fkfnWI+/z3w1DiLsdQ/z80jlcvXT0w/QtjlMCHvjFZNAO+/1o/MmbCZ9fO969mBAc06qegiCUAucBfz9YFoDTgEOylncDF4/W9kxOH0BbG3pfTCUx/MQ9CdcN//dv0b91XSP84p0Rpw+grw3lNfMwdODV29B9kZyBuqcV/+u/MCz3NW0wOH0Afe/+2tSOt+FN+vY9HXHYdI2+/U/jqX/dYNNx4El6m96MbEtTaN1xNwPdMfVNJeRh34afR52+iF2YPet/hKbGnKrd237PgKc2ss+hfrZt/BmaFluuqkG2bP+tYduaFmbthu/F+tK7k63770bTI+qF9W1vsLf+KdN+DYf/bPmWwekD2NL2Ap2+hmj52Yb72dEbebEJa0Hur/4Trf5Gwzq7PdVRpw8grCv8cPcfDWqLDzS8EXX6ADR0frj7QeLZ42nl7vp3UQ4ey7e69vNEy5ak9mtHX0fU6QPwqWF+uPNNk92AEuaXuzcyoEaO5T5vL387sD2pbd1TXW1w+gCa/X7+sHevoe6Pe6qjTh9ATyjMb3bvj5Zb/cGo0wcQ0nR+tK06qb4Ml76gZnD6AHb3qTxZZ1a0e6FaYdtBRcywBg/tUmj2xK7zA21a1OmDiL/1xm6Vlt7RFYXSVJ3tb0ScPoCBXp09a43Xrq7r1LwSc/oAGt9TUEJj84FN3RJC3Xpwexqo7wZRD4RNduGnO8ATOUZ6n0romU6TjcUHywf9fDzemQhOH8CtjyV3/7ewOCxPfv7Yd/oAOnZFRh8txpyxjkH6LfBNiCrW5wC9uq4f0jtvBBIqsgiC8GlBEDYIgrAhWzm6lya9O/ayT88QLzy+QakgwiHwGO307iZjWVPRehsMdVp3raEcbEzw9UI3v4wG+2pNdaG4ukACm0BfTexvXwuxwxpDDQ8QDvVGy16PsZ1wqJdQMLY8EOwCzH30+WMPzV6vuS+93hpT3XDoCTQnrK/vjT38mnzG7enotPiMDnWNz+gIAnjUAQKDYtn3eJtMNgOqOda91mfOJVM3kFx+mW195rQHrQFzWo32gB+/ahQvqvOZU4Acjj1DpDGJdwZrB3wmm8F1e/sHTMu7g2YnYjSoG0gs2FTnNdc3ec2//+ZBdR2exPeHjv7RdfxCAQjH+aUDvcZta0rkvwEdQkP08WjRO8zHS2831um6jt4Z56B2jM15tUiK3zIKz8eOjo5EJhYWFhbQsnm8ezB8+szvaBajz5g5foIgnA+067q+cSTr67r+N13XF+u6vrh7uEmY7YlDu4RBap/i9CESWpdNjdnbnQilsw2LxUmLjG2KEnLFCkOdPOlEQzltrlGJEkCwmedwpZasNKZrEERSS1cZbDJKjEqbouQgrXBJtJySPgW7M8fUtjttEg5XLIQ1v8jYTnpmFc5By1PcxcgJ5tAV5C2N/l2SuwQpLhVDWcGJ8asMixm5idebU3Ba9O9FOUabFDmNGRkLDHVLs+Yhxl3OU93luAalvDi7wHgOAcpd5rl3izMrcMTND1yVMyXxDgzB2YWTTUqTi7OKTXYVKWmUuozHe1Wu2e5wnFNUlLB+VZ5x307KN18fJ+XF6pblZpoUO2dljo288pwsmURT9Vbkm0MiFxUaz6tLhhk5sbqphSLxU+0kESYnEF05GpwpAum5xg3llRu3IdkEHOlGG9EGruyxmVMnVsXd8yQQpxuPoSAIiNON4Z9S1fBDiS1Gn9F8PublHX7+sMXEwmWbGOJMFhOEJRMgefshciYd2cbiqBnLO8wq4EJBEGqJTFY/DfgdkCkI0cRopcDRufg3XxH9U/7MzcS/AYrnn4cwyCGUz7oM8uNerFPSsV92o6HKdt6XEWedjJBThrTwXORTbzBt2nnG97DNvAAxezK2uZfhWv0tw3LZnUva4ps5lCNQsKVQcOXD5nayp1G6+jZc+fNw5c+j5JSf4cw2Sptnlqykctl3cGfPIq1gMdNW/wa7KyaqIogS81f/mdSsGQiChCDIpOcuYO7JvzW0M332Z5k0/TpS06dQVHomi1YYw1MBTj/5HzjshwRWBHJzFrHshNicO7czj7OW/oainMXkZszixHnfoSx/pamd4XDZrO9SmbkgWpax87H5v8I+aL7gyYXn8vGpX6UytYr52Sv4v3m/xyUbHZIceya/nnMr+fYcHKKduWnT+N287xr3K28e15etxiZICAiUu3K5c6FxniRAjiOVO+ZdyeLMCmakFfLtqo+wKneqye5wZNld/GD2SWTZnDhEiZXZJXxvttnJFQWBXy04kdV5JUxJzeDGSbO4vmJGghaH5syiIq6vrMQlSUiCQLosc1V5OZ+bZpRG/tTUSi4pKyJVlkiRJM4pyudLVTGH1iGJ3L5wGrkOG3ZRYH5WKrcvHBt5ZVEQ+NXyNDLtAgLgFOELM12cXGSeJ7qiROaGuTYqMwTm5oncusJB6iDxlrw0ketW2clJFbBJUJAucMPJdlKdo+9sLTjLTuEUidQsgcp5MtOXmgWEZl1qx50rIEgRhepZl9jHTCRHqpSxXZmCUCYhVsrYr0tFzDE7vPaL85AWpSHk25AWp2G7wHIWxpkP5vloEWXdracd2WicEYDXv3HqeHfD4sPEqi9BpTlF1zHHRX8d7x4cN3wg6RwEQVgNfP3g5PWHgUcHTV7fquv6nw+3vjV53cLCwuL44HgSdwHr+WhhYWFhMXyO9hmZWO9+bPkW8KAgCD8BNgH/GM5KiXL4gTGlg65phP74JwgMmojjcuH4ojHReXD9m/D607GK1Exsn/7WYVMtjBR/7ev0rvsjuuInZdq5pC/57Ii+/vc2vUPngSeR7KkUzrwOV4Z5SNzTs4f3X/o4g5UllnzkUdzppSbbwxEKe9i99276+vdTmL+cqZOvTJjOQdd19tQ/QX3r62SkVjBv6sdxDZGK4XBsbH6G/+37AyHVR2HKVG5Y+BtS7JnR5QHFx117b2NtxyuouopTdHLDtK+zusiYo7A92M09DY/TEujgtNzlnFe42rStAcXPt3f8h73eZianFHDbrOvJsBtHDx+oX88/6t5C0VROyZ3GD2ZdaDpn3SEfd9e9T6Ovj1PyJnFhsVkZ9Pf71vN86wFUTaMyJZNrymezOn/s1Nr+U13NPbW1qLrO8txcvjdnDg5pfKTBuwIK91b30eILc0phCueWmlNi6LrO19b1s7lLQRDgjGI7t84fWQqJ6naV/20KMxDSmV4kcd4CG/bhhogPomafwvYtYTQNpkyXmT1fTro/alin5X2F7gMqugbppSIlS2zYU0Y26qd0afjfUtD8Os4FMo4Zltz7h5gRPR8tjsyB9n5Ov8MssHWssfn/nUFmSvIK2RYWQ/Lf62HXyAT4PhDsaXBrfSS3icWYM2ESuA8nnUPw73+H7h6zQVERjuuvA0Cr30/4ob+ZbQpKcFz/5VHp7yFCXftof8yYdiBt4U1kLP50Uu30t21k75ovcMihkx0ZzLngUWR7bG6Yrqm88UjicMtTrlyX1PbeeOeLtHW8Fy3Pqvoks2eYcybuqH6AdTt/Gy3nZsziwpOSS8K5rW0N92/7P0NdpqOQb530ZLT8861fYXP3O6Z1f7jgr1QdDBPVdI1rN36NWl8sMuo70z/DBYXG8J6r1/+KOl9MeKXImc1jy26Nltd11fCVbQ8Z1jm/cB7/N+McQ90N6x9mrzcmAPS1aSdxWemcaPlP+zZwf8MOU59vn3caJ+aWmeqPluebm/nJDuP2Vubm8ouFC0d9W0dC13VueruJak9MQORrs3O4sNyYe/Jb6/pY12lUQrlmkoObZyWXPqK9X+OPLwQHC2lSVSRy3YnJvTw1N6q88bJRVWz+CTIz5yaXimH/iyG69hoFVlw5AnOvdiTtROohna7fB9AH6e5kfNSOfeqH1/k73kb8jhZrxG94VN767Hh3YdjU/vy88e6CxYeFJ78ImxKr2R9TpObD1/eNdy8mBMd0OofRYmpK5vAMEzl9AC0xRcrwxrcS27SN/lSKgd1Pmup8e5N/+PTUvczgUTwl2Ed/q9GZ62h6bcj1Q8G+IZfFEwz2Gpw+gPrGFxPaHmgy1nf27aR/oCGh7VBsbn3BVNcbbEU9KI0YVAMJnT6AZxrvj/6911trcPoAXmh/21BWdNXg9AG0BLrxq7GX/bvr3zVtZ037bkO5dqDH4PQBvNhmvGG91JY4DcLLbSNTPz0SjzaYj/u7neMj2V/tDRucPoA1LWbF0I1dZhXapxvNKqtHYkejSvznq70tGqqW3Eet/XvM/anel1h9dCh0Xad7v3kdf5eOvyv5j2yhGs3g9AEEdiTXJwsLCwuL45Qdj413D4aH16yEbjE2TAjHb/9A7+g1lj2EqMEYhHnKCUIsRXduAsvDY3Ob+2x35RvK7vTKofuRQEl0SFvZhS1O1dMdt61DpMTVS6IDx6AQzeGQ4UjUtoAoRM6HTbThkhL3v8AZO7659iykuMs5Py7sVBYkZCFOhRER+yAFz3JXlmk76TbjyFGW3YUtLvQ132nsY6bdlbDPeY6xUVMscJqTcafI4xHJDdl2yaQOmuc0/75cCX5y2fbkb0kZbvMomtMOkpjc6FpqmtnelaDtwyEIArYE6wgiCeuPhJhuXkdK0E8LCwsLCwsTCd5pLI5vJoTjN1yEcz6SeMFVV0b/tC89FUxC+yCdccmo9ydl5sVIaYPSMEl2sk781tArDEH+9MtxZcVUPnMmn09qnjEtRWrGFNxp5pQDrtQKRHH4DoAkOZg/58scEpaz2zOYO+vzCW0XVd2MyxFxZAVB4oQZn8VhM8/lOhynVF6P25ZhrKu4PhoSJwoSn5x+q2m9VDmdKypjIbO5jiw+UXE54sFzW+jI5abyy0zr3VR+uqF8XdkpSIOcuC9NPR2nGAvtE4AfzrzAsE6GzcnNk5chHexjniOFT1QuMdh8e8ZK5DjnsMKdwdVlxjQho8VXqqqwx8XH3zrLPO/wgyDLIXHTtKzozSXPKfHxqeaHz63zjB8YBOC7C5IL8wSYWyZRlBn7TQvABYuSC88EmDXXhmOQ/yxJcMKy5NupONlG3PcFSpbKI3L8bEUizhNijUn5Aq5l4+PQW1hMZHJSJsbv5oSyzPHugsWHiUvuHO8eDI9Tv3tkG4tRYcLM8duwYYNZ4KUgHccNVxmq1EAA5Z57obcX0tKQP/0ppDiBC13XCb37Mmx4HbLykC//FJJr7PJa+evfRQt0455yJoKUONfgkdB1nYGuHcj2NJzpQwuEdLWuZ+c7/we6yqyVPyWnaMWQtocjEOjC460nK3MmsmweTTqEqobo6N1BmrvENAI4XFRNYXfnWzR79rCw8DxyU8wjpf2hXl5veYZ67wEW5q5kZcGZCdtqDXTSGuxkTtpU5CEc3tZAD693bueknFkUu8y57QAeb95EV3CA68uX45ASt9Me8NIc6Gd2egG2BCPGQVXh+dYDOEWZEncaM9NzDU7maKPpOk81NdEbDHJpeTnptuSdltGk3a/Q6leYmenANsTom0/R+OuuAdJtItdNc+OIHypMgtoOlS6vxswSGbd9ZO3ouk5Tg4qqQGmFhDTC/igBnYEOFV0XcGUJONKO7rwrXRq6H+QSYcxSQxwrWHP8ksOa4zd8ntrUwFf+u5VjLVjaLoIsifz308uZW2aN0FiMMmE/vPxD2HgPaCFw50LID0oINN9BIwEcmaAEAA1Kl0PbDgj0giCBJEci40QZQj7IngyBHvAfXC4Akg0CfZH1pRSQbaCGQQ2BHgbJDboC4sH3YGUAUovhM69DqpViaLgcF3P8hqSt31wnCKBpkb99PjSv12Si9nXCtvcgFIJQ2JT8OVnUjr0o9evQ1XDC5a7yFaRMP++ITl+wtwZv07toSsC0TBAEJHsaPQ1v0NeyjkQOu65r9LStxeHMJLtoJY4ECd0BvP217NvxN3q7dw7ZF5+/g+rax9m28y94PHVD2kmSncKchSN2+gD8Sj+iILOs9LKETh9AvXcfO/s2UuguYVle4jxHdQNNPNWyhn2eWvZ4a4fcnqZr9If9dAQTXD8HWZU9hZlphYb5f4PpDwfY3tfKcy17+Gv1OoKqeX6YXZQodafTGfThlmxj6vQBeMJhdvT2UjMwQEgd/1ebQ+GdO3uDCa9XgFafxqpCx2Gdvv6gxtP7wqxrUtAO86GqMFMk1SkSCI38Y5YgCEgSePp0QsHE7WiqTmejSn+nNmQ7slPAkS6iayA5jt5Rk3NEbKXiUTl9ukdB3TOA7jVfqwB6SEXZ2UP49RaUDZ3oofG/hiwsRpMUp42hf7XjR0gDWRLITbPUPC3GAB3oqYs4bpoC3hYI9Q5y+gAECPaAGoz8r3s94vShgR6MOGmhfgh0g80NnTsj7ciuiH3Ye9D+IOoA6Hpk4/rBZ4nqi2xfU0DxR5aFPbDPrPVgMXZMmBG/4ah6qi0tKPf+x7RcOP107CcsAiD83mtob/zPZCNfeTNSuTlU8kj4X/4R4d2R9oT0YlIuvRMxNXknqG397+je+QAAkiuHyo/8BXt6eXR509Z/0LI9NuLpzprBjLPuQpQiozpq2MfbT56Jrhlf6oqmXMH0E74eLe/b+Xf274q1U1JxPvMW/z/DOpu2/pr9NUZly1lVn2L2jE8mvV9HYmfHGzyw7TsoWghJkLli9veZX3iWwea2LbewpScmuiILNv684mnS7bEvo/+oe5i76h42rLcqexG/nP1NxEEO10ONb/GbAzFZ49Nz5/GT2dcZ1nu2ZRs/3/McKjoOUea2OZewPHtydPmGnka+vuVZQnrsFUJE4IFlV1PmzgQgrKl8buPz7PTEBFauKpvJl6YtTebwDJt1nZ18bdMmQ93358zhzKKiMdnekQiqGl9b38q2nohYy+xMB79ZWohDip2L32738kRdZHmeU+T3K9IpchtHTje3KvxyXTgq3pLnFrj9VAfOuFQNjd0ad78RJBCOfHg8a57MiVXJj3i++kKAtpbYPXH5STYqp8RGfAMDOu89FcTvidgUTZWYd5r5g07z+2Ea3on8FiUHzLjQQWrB+H1nU3d4CT3aDioggf3yAqRZsXmpWquf0N37ITDI2ZMF7J+cjliQeL7qWGGN+CWHNeI3PC7785tsrB/6Y9+xwk8uns11yyvHuxsWHxbadsJfRhb59YGSNQW+/P5492JCcFyM+A33G7fy+BMJ6/U1a6J/a28+l3jdZ+5Lslegtu+OOn0Aen8zoc0PJt1OyNNM987Yeqq/i85tMfldJeShZcc/Dev4enbT2/BatFy3658mpw+g5cDDhEORh52u6xzY82/D8qa6Z1HCMdlAXdfZX2N0oAB27f0nobAnmd0aFs/t+wOKFhlVU3WF/+37vWF5b7DT4PQBKHqYe/f/blBZ5d/1j5vafrv7fd7r2Wqo+2ut8cvSms6teJTYVy9V1/hT9asc0okMagp/qX7dsM5fDqwzOH0AGjq37X4tWn6jo8Hg9AE81LCL9oBZ3XI0+MWuXaa6Xyeo+6B4rXUg6vQB7OgNGpQ967xq1OkD6AhoPHjAb2rnX1vDBsXODp/Om/Xm63zN9jCBgwPuOrBmu0IgnNxHLU+/ZnD6ADavN47i121Xok4fQMt+lb5247WgBHUa18X6qAahcV3iaIAPivCL3UTj21QIv9hlWK680Wp0+gAUHWVNCxYWHwYmgtMH8P0nzWmALCxGzH+vP7LNsUDPAQibo90sRp8J4fiVHGaOmYHgMKTghxrhDCZ/wel+c/qIRHVHQg32QpwgveLvji0Pe2ND5YMIB2M2AW/zkO0roUPhrhq6Fv8CqqMogx0/1dSXQ/XhsDls9mjxhozHayDUawgL7A8nTkXRE445VYqmEtYTh6/1hI0P+5Bp/6E/HHM4FE3DE3fz6Qn5jOWw2UEB6Bpkl8hGB3rH6MY2oJj3P6iNX1BTb8i87d5g7BruS7C8J0GI5kACf6knwc98IC4sU9EgmKSv5Rswbz8cd1hDfrNNKGCsU0O66ecaTrDeB4k+oB6hPET4p3d8HVYLi9FASzK1y3iiTpyuWkwEAsm/k44bYd+RbSyOmgnh+DUmmPOWCGHxECOfBQWD/i5JaCIsTJz8/HBIpScgpBUObgVbXKLv4eDMmYEjc7KhLnPqudG/HSlFuLNnGpYLop2ssthct/KZNyVs25Vaiiu1OLKOIJGRZVR6dLoKcQ6anyeKMilu8zHKypxFinv0wwYXFZ1rKC8sOscwj6k8dQou0ZzO4cLSWHimU7IzK4GiaYacxqrsRcb2M4zHOduWSskggReHJHN6vvFYn1s4J648nUR8rDy2rVPyyrHHSTtWuNOZlpodv9qocG5xsaluVd74TZY+pdCNa9CcPacksLoodh5nZcqUphhvP2eXmue3nFRmPIYCcGKpWUhnYaVRgGdyvpgwzcPhKCiSkOOiQ0vitlU83Vh2pghkFxv3w5Emkl5irMubMb6KgtJ8o1qqtCAtbnni61JanHz6GQuLYw1RFJAniCbSovLM8e6CxYeJVV8e7x4MExHcY/N+ZGFk4szx+8zXoMs84nRoft8hgk88CXv3xipS3Dg+H0tHoOs6oXt+Cx2DQpimzMJxyQ0j6pvmaSO0+QF0fw+2mechl41sDpfi76Z75wOEB9pIrzyDtPKTjctDXho3/YH+1vU4UoooX/xVXJlGZ6et7iX2rP/hwVE9gcyC5cxe8WNke+wlT1VDbN3wI3q7tpCWMZX5S36IzZ5uaCcc9vH2e1+nq3srgiBRWnw6C+d+FZstean9I6FqCusaH6O2dzNlGbNZUXYlsmh8++4OdPCzrV+i2VeHQ3Jy07RvclKhMXVHUAvx0713sr5nK5IgsTxrPh8rv4Ryl9FZ1XSNn+55mA29+yl35fHDGdeQ7TC+BAdVhYeaNrDH08oJmRVcVLwAcZAzqus6T7bs4qH6rTQH+rGLEh+rWMR1FQsN7VR7e/j9vvU0+T0syCzgc1MXk2Uf5uj1CPj1rl0809SEDpySl8cP588fs20NhwP9IR6r70fXdS6pSGdautGx6wpoPFTjpyugcUaJg+X55rlymq7z6G6FtxtVUmzw8bk2puckzrm5uU5hT7NGXrrAyukyTlvyb3oDHo21b4XweqCkXGTxcnOfuppUmvao2J1QMU/GlWr+fqYEdVo3K/h7dLImieRWja/jp6s66nv9aA0BxDIn0tJ0hDgxHXVHD+F32qEnBG4ZeVU+8sLEAlFjiTXHLzmsOX7Dw+MPs+jHLxI+FtVdDjIpx8Wr3zhtvLth8WHjuVth3V/GuxdDI7vglu2Qan1oHA5H+4ycMI6f9WCzsLCw+PBjOX7JYT0fLSwsLI4fjvYZOTEymoI5h98hzliG44R5ACitbaj33GMykb/21WguP9XTi/LXn5ltPv9DJFdy6nX+l39EeN9LgIhtziW4TroloZ3ibaP33TsId+7BUbyYzBW3INpHf/Rs9/qf0FbzdLRsc2Sz4LS/4U4rS6qdltZ3ePu9b6DrCiAwu+pmZs240WTX1buHlzd8HV+wixRnAWct/Q2ZaZVJ9/vpPXfwTsNDgI4k2Pns4r9RkjHziOvFo+kaX91+Gxt6t2MXbXyi/HI+WnZhdHlQC/OHA8/wfNv7KLpKVWoJt06/nEkpBYZ2NvXU8f1dT9MT8lHkyuRXcy+j3J38yMe/a7Zwb912gpqCTRA5t2gqX56+FPugnH/31u7m7tpdhDWVE7IKuG3eShxS4hGtw/Gfmhr+un9/dHbmjLQ0bl+4kBxHcvLgYU3jR9uqeae9F0kQuLAsjy9UlRtsDngC/Gl3K02+ECflp3NzVT62uOTxnrDKH3Z1s6U7QFWGnS/OzCHPOXa3m3+9HqC6PbL3ggCXL5WZVz42eQz72jW2vBIi4NWxO2H2yTbyymP7pqk6De8q9FSrODIEKlbZcOeaRwU1RafzzTDefRr2bIG81TYccXbBAwqeJ8PoAyBmCKRfbsdWPPoR+rqmE36+CW1zF2ggTk3DdkkFgiP5axFAWVeDuqkBHDLyydOQplg5mizGl/3t/Zxxx5vj3Y0j8swXVzKnxMrlZzGK/HYe9A6dlmv8EeCz66Cgarw7clwwIeb4HZaX10X/TOT0ASi/iylFKn/7eWKbf9ye1GaDmx6IKHqqYVCDhLc8SOjAqwltu9d8l0Dt66jeVnx7n6H37V8nta3h0Nex2eD0QUT8Zcurn02qHUUJ8Na6rx50+gB0duy5kwFfq8n2uXWfZyDQjq6reP3NPLf2c0n3u6ZnE+80/JdDgjKqHuLODZ86/EpD8PN9d7G2ZwuKruJTA/yh5j/UDDREl99V8yKPNr/LgBokqCls7a/j69v+hTZIoTOghvnK1ofpDA2gotPo7+ELI1BqfbOjnrtqNhPQFHQgpGs80byXf9Vsidps7e3kzgPb8KsKiq6zrruVX+7emPS2qj0e7hzk9AHs9nj43tatQ64zFH/d18jrbT2EdZ2ApvFQXRsvtcSEdFRd59aN9WzoGqDFH+ahui7uPtBhaufX27t4oclLq1/h9VYfP9lithkt1u4PRZ0+iOg3PbxOocMz+jFdqqKz/tkg/n4dXYOgDza9ECYwSBimeYNC62aFYL9Of4PGnmdC6AnEJbreUejdqKL06/hqNZofDxmEjTSfTv/9YXQPoIHWo9N3TxBdGf0oDXVtB9r6TgjroOpoe/oJP9c4srZ2taC8vBu9awC9uY/ww++jeyy1NovxZSI4fQDn/+Gd8e6CxYeJp79yjDt9ADrcOQFSTnxImBCO38KMgiMbHY7Biof6EC+DgeTUhML715jrdptTRWhhH6H2bcZNNa1NalvDoaP5rYT1oUAHoUBXwmWJ6OnbRSJVz9r6Zw3lQKjXlN7BH+xCTaCaeTg2t5oTdyp6GCXJdgDe69liqnum7fVBy/ealjcHu2n0x47Pbk8roThJxs6Ql85gcoqm67qaEtd3x9RX17Q1mJa/192W1HYAXmlLvM6W3t7DJjxPxDsdvaa6V1tjqmD13iBtAeO5ea/TnKJifadR1XRzd4DwGCnrrT+QONF4ddvoO379nRpq3KWp69DdMkixtN7Yn5BXx99t3ndfndEu3KcTHmQXrtOIzzatB0FpHQPHb59Z6l7bN7L0LVq1MY0JqoZW153Y2MLCwsJi7Nj+2Hj3YHjoKoTGJt2VhZEJ4fht6kv+ZThpkgyvkwrMoYhysVlMQ5BdSOmlhjpb9rTk+jYMMnJmJayXZBc2e+aw20lPrUxYX5i/zFC229IQ40RYZMmFJCYXXjcpa2GCWsEk8DKsttylprolmXOjf09JNauSpkpO8h2Z0XKFO8eUN9Il2si0uZPqy9S0xOpU01JjITzzM83ho5Up6aa6IzEvK3FYUKnLZRClGQ7T0sz7OTszpsZZ6LKTIhtvG1PTzOGkU9KMoijlKTZs4tjI6k3KT3wbK8wc/e2lZIokOqRp2bE+xId1ijZwpJtXig/rFB0gD7KTCxJsSAQpZ/T3Syg0iw6JhSNL3C7km69hIT8tgaWFhYWFxZgSp0p+TJPke5bFyJgQjt9wEVafknjBR6+N2Zx3bUIT6fLkwgudq76MmFUZLYsFc7AvMLctCALZp3wXKTWS9sGWPYXMlV9PalvDIbdkNY6U+DQMAjOW/QhBHL5T63BkMX2qMeFnXs5icrKNNw9RkFg551sIB1MWiILMSQu+l3S/5xecRVGq0RG+sGpkx+cHVV8g1x5zgk7JWcry7Jgz/rlJ5zAjNeYcpkpOvjfjKpxSzMnMsrv5/OTViAfdP5sg8b2Z5yOLyf1Uzi+axvJs4/mYlprNpyfHUj6cml/GypyYM5pjd/K92cmrwi7NyWFpttHRdEkS3587d4g1huaWGRUUuWJO2+yMFK6oiKUscckit84pIdMeOe/zstx8cpp5RP6rs3OoTI0c1yKXzK1zx06t67wFdlxx3wkWTxKpyB3Z/LTDYXcKzDrJhnDochBgyiLJ4PiVLrORdnAenuyCyafbkexmZy33JBvOg2kfJDcUnmNHHKREKmWLuE+ViX6JkCD1fBuia/QdP9sphQjFgxy9dBvyeeYPKcNBWliKOKso0m+bhHxaFaLl+FmMM18/a+p4d2FYfPFUc2oiC4sR87EnQZwAch7n/IqEX1UtRp0JpeoZ3LsXHo+F7sWncoCD6RrWrYOGRpgyBceiRCNKENz4FrTUw9RZOGYsGHHfNG8HiBLiEfKP6LqGFuhFco1tnpKAv4fOhjVk5C8iNb0iKadvMJoWpqNzE5kZM3E4hn5p03SVPm8dmamVCMLIvyMMBPto9uxmcvZipBH2+RDN/nbS5BTSbOb8fwC94QFUXSPD5kYWEm8rrKm0BHopcWUhHcV+ecJB+kJBUm12ModI5eAJh/AqYYpcifs7/G2F2efxUOh0UuRyGfIhJktHIIQsCGQ5Eo+8KpqOV1HJtB/+gdITVMmwi0mPPI6Ern6FHp9Oea6MfYyTdmmqTsCn43AJSENsK+zXkewgSofvi+rTEZ0gDDEiqis6qkdHShdMKRhGG20gDKqOmG5OY5EseiAMkohgS+73bKl6Joel6pkcX7p/A9saukFT8Yc13HaJ7DQ3/pCCXRRo7ffhstuYlp/O3nYvDlsYXbWTk2qjoSdAaZYLf1hlYXkW25p76fcG6fGHyUqx4bDJeP1+irLTyHY76PaGsIsCdT0BMlwCKQ4n6S6B9r4gPQMKsgRZqS4kNCblpfPTyxeM9+Gx+LDSvAXq3oGBLjjwBmSVQ8EccLhADULN25BSCCnZIDnB2wxF86F0Cay9Czwt4EoHWxpkFoDfA0EvVKyA9j0Q7APJBsULwdsKtesgowiKFkTKfc0g6JA7LaKN0bEXHOlQNBsWXQ9Jflw/njmu0jkkUvY05fG7735oGjS/6sRVOFYak7MHt62HFx6OVcxdiuPsy0fUN13XUGrfRuutR65chTRoFBBA8bbj2Xw3oe592HKqSJ93DXJasamNnt2P0l/zArIrh+zZH8WdP8+0rYCnifoNv0QJ9JA/6zpyK840tqOpdDa9RkvN02hqiOKpl5FfdnrS+6SqAXbs/jvNLW8gyynMmH49pcXm3EJ7659my75/IUo2ls/+OiV5S5Le1iF2tr/OxpZnKUiZzCmVH8MhJz/kr2gK9zY8xeMtL5Fty+D7M77ApBTjqMX2vjoeb1mLQ7RxVemJVLjzTe1s623iV/texKeGOLdgDleWLSZFNoYz9ob83NewmRZ/P+cVzmBFboWpnd5QgD/t38CBgV5WZBdzdfkc0mzGF+pGn5e3OpspcqZwYl4x0hAOkqJpvN3ZRovfx0l5hZS4zU6iruu829lJ3cAAy3NzmZQ6MuVYVdd5p6OXZl+QlXmZlKUkn3tQ13Xe7fDTMBBmWa6LyrSROxIhVWdNrcKeLo3ZeRKryyVscQ7QnhaFV3co2GW4YJGdvPSRPUT8fo2tGxVURWfOAhvpmeZ2/F6N9hoNuwsKJkkJHTs1pNO1X0VXIXuqhC3BKJ2u6nj3ayhendSpIraMkT/4dL+Gui0cCQWdY0dwjp2DqHX6UN5qABHkk8oRs0YWEjoUluOXHJbjN3zO/+1rbG89ducRzS9J5ckvDhG5ZGExUt79C7z4ncg8umMOEeZeARf/GaQJMDJ5DHDcOH5vX3HzkMsPOX/BP/4JfAlEWubPx3H2WQCE3/gf2nuvmW1KJuG4JjkFTAD/mp8S3nVQTVOUcJ/3K+SKiDpRuLuatsc/DoOFSgSJ/Iv+jj0vNkew7sUv4mtZb2i3YNnXyZ4Rc0Z9vdXs/N9HGSy8kjf9KioWfyVa3vnud+hoeNm4W9OuZurCrzBcNE3h2RcvIhA0CjRUTbmOeXO+GC2/sfnH7G98xmBz4rzvML38QpLlf3v/wJv1/4mW0+y5fGPVo9ik5ByOGzbeyu6BakPdA4vuYNLB8M4nW9bx872PRpeJCPxm7idYmj09Wvd25wG+sf0RQxtF9nTuXfoJ3HLEeekMDnDNugcZUENRmxsrTuBTk2Nhmp5wiIvefoigFrvRZtuc3Lf8YtJtESdyc08Ht2x6g/BBwaHT8kv58dzEylbf2bKe1zsiyqp2UeS3i1YwL9M4evzLnTt58uBHD0kQ+Nn8+azKS15G/4dbD7CmNSLGYRMEfnXCdBZmJzf38JfbO3mmwXOwL/DTRQWsyE/emVc1nW+/FqBxkM7IlEyBH53siI5ovr0nxPNbjQ+0z5xupyQ7uZGmYEDjyYeCaIMEVc4630H2oLl4nm6NdU8GowIvWUUiS863G0ZX1bDO9oeCBHoiv1WbG+Zc5cSeYnTGmh4NMlAT2ZggQ9lVDpxFyTt/+oBG8E/96H0H01nkiDg+n47gGH3nT2vsJ/TvLbHbkAD2TyxELBq99DSW45ccluM3POZ//zn6gsdw9vaDpDhEdvzwnPHuhsWHhadvgY3/Gu9eHJnUQvj6nvHuxYTgaJ+RE2Js1cUwX+ASOX0AW2Jqj9r61xPbNNUk2SvQBjoJ7xrk/GgqwU33RYueHf81On0Auop3eyw9gOLvMjl9AJ1bjT/Upi1/IV5ts2Pvw+gHHQu/5/+zd97hcVRXG//NzDatVlr1LlmyJfeOGxgwvSZ0UoAACem9EtJI770T0r8EQgikQOjNNNvg3pssS7J6b9tn5n5/rLy7szOytLKN7Xjf5zHo3jlz7522M++957znkIn0AbQdeNhUdyS0d7xqIn0A9Y1xMhRRfSbSB7B+z69S6guirqLRdA5xDId72Nk9xnUaA/tHGk2kD+Db9b+J/f2HJuP50RH89dBqQ92P658xtdEeHmJ1T/wH6b/tewykD+C+5i1oCYqx9zfvMJA+gL5IkGc64/fZ35r3xUgfwPNdLbT4zeqhzb6RGOkDCOs6f286YLDpD4d5NGGlWxOC+xsbTW2NhzZ/KEb6ACJC8ECjOZXHkdAf0nj8UJypaQL+1jCY8lgAtnXrBtIHcGBAsLcv4bztNM9iPrUtdVXYHVtUA+kD2LLBeJ2bdqgGVc/+dp2BJPXQ/gYtRvoAIn7o3q0abIJdeoz0AQgV+jcZbSYKdXM4RvoARK+Otj18hD0mD/WFJuPPkAD15ebj0lcaaRxLnAqkD8B3iowzjVMEG/98okcwMYx0QNuWEz2K0wKnBPGTj5Ma4FFD6JhSHyR+7I+ROkIk1Iux0ksk14+5RC9G/zvWym1qK7pjjiehnTFXiSexeiyEsBz72OOwhj7GceqGc2220ZLqxkp/kFhvOV6E4fCT251oO1b7WdUlH2/0PI7d10RhNaZUszDoFq2MdX3GHc8YuyWOycpkMpkjrPoy1Vm1m1RnOeaJtDPZ772J9HeMYPUMWeUoTCONNNJI42TAKfT7rE9u8jON1HBKED/fRG8Gp1lWHoDZ8VQH0oIV1jZFyYqY40P2FGGrS4izk2QcC98eK3rm3Agm8RApWj8Ku7uQjEJzPF/+nFsM5bIFZlfX/GlvRhpVa3JnVZFXerbJpqT6yokcSryf0rNxOLym+urKN8f+dtg9VJeaYwcXTX93Sn0BKLKNZeVXG+rcdi+zC1OLc5jhqaEmw6xC+Olp74r9fUvleabtb688x1D+yDRzLGO+PZPzCmfEyleUzMSVpJJ1Q/lcg/LnzVPmYEsShcmyObiouCZWvrGyzhDTt7KglCmZZiGdGk8WK/LjsYiKJHFj5VSDTZ7TySWlcYVQCXjrFHPc4Xgod7s4uzAnoS+4cUpqeTTznTYuKovHIErAW6rN99REML9IpjjJQ7QyS2JmfvzcnjPD7BFwybzU04HMXWgziYrNX2xsp3K2jUTtIW+RRE6J8TrnTVUM6RtsLiiYaRyjq1gmozK+n6RAzuLJiRrZFjggwY1UypFR5qZ+/BPq69wqU539HHNdGmmcbHAfn0fimMN1nIWp0jjNMHdy+hVvODLyoCLt4f9G4JSJ8ZuwuMvvfg99CcmC583FebnRXz702mp4+fF4RfV0nDekTloAhK6i1j8/Ku5yNkrRTMN2dfAQgxvuJTJwEHteLdkLb8OeW2Nqo2f7XxhqfAabK4/8ubfgKTcTVF9/Pc3rv4saGqRo+o0Uz7jRsF3XInQ2PUHHwUfQ9QilU6+lbNo1KR9TJDLClh0/o7NrHYqSwYzam5habSRnQuhsP3AfOxseQJYVls7+KFPLLkq5r8PY2PYYm9ufoCizmounvZcMe+r57EJ6mF833M+TXS+Tbfdw94wPMTd7usHm9f59/LN1HU7Zxk2Vq5iRZSb8a3sO8KP6ZwnpES4smsXtU87CazcKWHSHfPyhcQOdwWEuK5nBJcXm3IydAR8/3v8aTb5BluaV8s6aBeQ6jO0cGBnkxa5WyjIyubC4EvsYylYRXefZjlY6ggFWFZUw1WM+P5oQrO7spNHnY2VBATO9kyNbqq7zfEcfbYEQZxflUmuR2288aEKwut1Hsy/CmUVuZnrHmJSZAAIRweMHVPb16cwukLl0qs30cbS1OcLqXRoOG1y12EF53uTmtEaGdbZsiKCpMG+R3RDfdxi+QZ2OAxpOt0RprWKp6qkGBT17NXRNUDDdhsNjttFVwfBuLSruMl3BmX8U4i7DOuqWMJICykIHkvv4zelpbcNoLzeDLKGcW4VSfOzi+yAd45cq0jF+E8eKbz5Nx3DqbuBvFCpznLx81+Tfo2mkYYlnvgKv/pTJu5UcZ0y7CN52H9hTF5I7HXHaiLscfrElkj+rdA4AocZG8AeQq6dgd1t/tIa6W6G3D7l6KnbX5GX0hRYBSQY9gmQb+6YVQkeERpBd1oRGV0NoET/2DOtk3IcRCQ4ihI5jDDtNUwkMHUKxZ5DhKbG0iY5HQwjdlIQ9ecy6rqIoR1ZkVLUQiuyYdPoATdcYCLTjtGXicY59/JquEtKCuO1jf2gGtTCyJKFIylGlYVB1jb6QD7fdgecI13U8BNToR0aGbezzHNY1FEkeU9FzotCFQBUCxziyyEFNw6WMvbqkCYE2gXbUURc/21G6Yk+knbAmcBznVAapQh8d91iu6LoqUEM6NpeErIx9LoUmQBo7ncOExxPSkRQJ6RRfMUgTv9SQJn6p4b+bmtl6qAenTcYmKTQP+FgyJZemXh+ypBDRBP1DfjIcMLUsD6FrTMn3sHp3F1ML3WxuHqIwy4HDIVORlUHrUABvpgOHBF0+FQmdoaEwXq+D3uEwXpcdpKjDnWyDMm8mwaCGKgvUkIbTodDQ7eetZ1ZzxpTUxbjSSGNC8PVBw8uQNzWadmGkHcJBmLIsmj9voBU6d0Px7KibSngIMnIhMz+aesGRBf2NoGng8oIahJyKqLuKrkbDkVxe6N4P2WVRVx8tCLIdQgPAqJdUcBicWdHAdntW1K2oZE46h18KONp35CmjnWq12ne47jABjGzfjv7Ek7HtOhCSZRyf+DjS6IdupLMF/S8/S7JRcHziWykRF6GrBFd/f1TcRQchUMoWkXHJ15A9xh/voc1/YmjjvSB0ZKeXgjf/BkdC2ofGpz5EoGMjAJLiYMoVvyMjz7hSFQkOsP2R69DVqICNJNuZecnvyUyw2/7yp+lrf9mw35yV36eg/FxDXdOBh9m/6x7UiJ/yKVcwZ9FnkZNcFxubH2fbzp8RjgxRWX4xSxZ+HkUxrtqEwoO8uPnLtHSvIzOjmLPmfZbKImPqjPHwz13fZn3bv2NlWVK4ad63mFN0nsHu/gO/5L+H/oqOTqaSxWfn/YjpOXEX2e1D+/ja3l9yKNAOQJaSyUemvoOrSs2um+PhU9seZG1fXIQl35HJ/UvvIMs+cdl6XQg+uOlJtg92ATDfW8QvF19myGcX0XW+t2cjT3U04bHZef+0eVxVPnWsJo+Ip9vb+fm+fQxFIpxXVMTn58zBmUTuDvkCfG3HHvYMjTDV4+ZLc2dSm2Wc9HistZt79rUwompcVJLHZ+ZUWxLAe/d18lBTLxISb63O51115rQYE8Fvdvv4Z2MQWYK3TcvgtjrjRE2nT+eXG8PU9wvKsyQ+uNhBjUWKhTcaBzZFOLhVRehQNcfG9OW22O+Hr1tn739DRBJU4/NqZeouM6969rwcoX+jChLkLrFRsDJ1fzS9XyP8x2FE7ygRnWrD8Q4PkkXS+DTSOF3x25f2883H91lu++e2XuudtvQfxxEZ8eCW6Lvi529dyJsXpR56kkYalogE4JvlwMmYyiEBZ34ELv3GiR7FaYET/wV1DJFI+uKVOuGH4sqW+n2/tLDRCD/5D3P9ERDZ9QiRXf+JznKMrppqbZsJvvpTg50a6Gdowz0xsRY9NEjv05+JbR88+EyM9AEILcyhZz5m6m//6k/ESB+A0CPsXx1P0zAy2GgifQA713zOIMjgG25m15bvEwkPIYRKS+MjHDr4H8M+gUAXG7Z8g1C4HyE0mlueZH/D35ObZuPe39DSvRYQ+AIdvLj5blQtaHm+rDAU7DaQPoiqfP59x93oCWI2+we388ih/0MfdVPwacP8YOedMeEWXeh8ec/PYqQPYFjz8Z39v6Et2DXh8QC83LPfQPoAesM+7t71aErt/LlxW4z0AWwb7OL/GrcZbP7VcoDH2xvRhGAwEub7ezbSGjCreo6H3lCIb+3cSX84jCYEz3V28kBTk8nu+7v3s2co2n7DiJ9v7TRKJ3cEQvxgVyODERVNCJ5q7+Wfzebzt7Z7mL829BDUBAFN508HutnQk/q4X+0M87eGICEdAhr8cV+Azb1GN6w/bI1QP6qQ2Tos+NWm46NWmQr62zXqN0TVPXUNGrepdDXGXWjqnzaSPoC+ep3hduOLd6RBo+81FaGCiEDfWhV/U+ov5/C//THSB6A3qEReDKTcThpp/C9jLNJ3suEjf99yooeQxv8S7nsrJz3pA1j7cwidvDk2/5dwShC/MpdZ8CIltMcJAfoYD8DB3Sk1qXVZ22tdewzlcNcOs81IXB7f17rOvD1onmUMDpkl09VgbyydQ3eLOQ0BAEJFDQ/FioMDu0lWeRoaMB7LwOA+RJKKaP+A+Xh7BpOONTLMkK/FehwWaOjfZFkf0UMMh+IzsAeG95hshiL9+NSozv+QOmJJ8HQE+0YaJzwegI39ZsIE0ODrTqmdzQPmFAibkur2DPcZyjqwb3ggpX4A6oeHUZNctvcMDZnsDpO+w9g/7DMohu4f9qMleX7vHTL/EO8dNJOKPUOpE429A2bRpuS6gwPGmITWYUE4eZBvMAa7zf0PdY9OQmgCi8cXgIFm47GEOszxFkGLuvEgWs3nURw6BV70aaSRRhppHF+0WX9nnZToNH8vp3HscUoQv7bg8PhGR8K0afG/x4q1mrfMun4M2MrPmFC9q3Qxyac5Udwlu+ZikmHPNMfmZebPMtU5PBVIoxKDpUniK4chyU7szrjIR27+QqQkpdG8QuOY8/Lmmdw6CwvMx1uab6zLcBaQ46m2HIcVphdYJyt32TLJdsbdZWfnLDLZFDpLybJHjyvHns00d6XJxiHZmZck7jIeVhVa28/3mhVDj4TzCs2Kmsl1i3ON7pF2SWaeNz+lfgBmeb1kJLl1Ls7LM9ktzjWKvSzIyTbEFc71enAkxZkttkjcvijPHBO72KJuPCzMNz+LiwqMdbOTxFVqc6UTHuuXV2b+2cwrj9bJioSnxPpnNb/WWJ+o6hmrq0pd2VOeZj6Pct0pImGYRhppGJB20E7jmKL2FBILKl98okdwWuCUIH5HxPK5sT/lt7/dvN3txvGmeEoD23s+a2GThfOcy831R4B9xmU4l70HKSMvGghrd2OfcRmulR8x2MmOTHLP+xKS3Q1I2LxVFFz+k9h2T/kKvLVv4vDPveLMoery35CMulU/xO6Oy+orzhxmXPjzWNmVWUT59JuT9pJZdIExNjLDXcyi5d/Gkz0VZ0YhtbPeQ1nlZQYbp8PLWcu+hze7Dpcznxm1tzKt+jrTmBZNv4MZVdfgcuRSlDuPi5Z+3xQreCS47dlcXms8X04lk3ct+rkh3rLKU8sddZ/FpbiRkCh2VfC5BUaX2m/O/iRneOfilB04ZTvV7gq+PftT5DtyJjwegEU5VVxfZvzxqcss5O5Zb0qpnesqZnJxUQ2KJKFIEhcX13BdhVHx9crSam6vnkWB08U0j5dvzj+TAufE4wgPI9tu51sLFlCXlUW+w8FNU6ZwXaWZCN85u45zi/LJtttYkZ/LF+fOMGzPddr5+oJapnkyyHfaeUdNKVeWF5jaWZCXySdnl1KaYafc7eAzc0qZnZO68ufiAjsfneOmJEOm3C1z5/xMZniN98+7FjhYVirjscO8QpkPnXFkoaE3AtkFMnNX2XFnS2RkScw8y05+eZywTbvEjkFXSYLSxQrufCOpc1cqFF1ox+6VsOdIFF1iJ6M09Z9kx9Vu5Bol+muugLLYge2syauoppHG/yLue/epoRf0nw+mFiefRhpHxA1/gCOI5p00eNPPoqIzaRx3nHKqnmmkkUYaafzvIq3qmRrS78c00kgjjdMHp4+q59MvwOZ6U31iSgchBOFf/BICCfFGJcU4b73V2NYffwS9CfFWS1bhPC+1ROcTxfCOBxna9HuEFsGeX4dn1jW4ay8zKYgOt7xKz5bfIYRG/txb8daYl+cPbf4l3fsfQgidvCmXUr3szlgCd4De9nXsWnMnuhYCyUbxlMuYfsZdyJOYRQmFB6lv+AeBYBdV5ZdQVGi+x/zBXtZs/zYDI01UFp3N0lkfSmnF7zA0XeWxfT9hf+86ij21XD/7C2TYU4/r7An188uD97F75ABzs+r4QM1NhhU/VWh8e+/DPNu1BU3oTM0s5huzb6HKbVRhff+mv7BtqA2AbMXFF2ZezjlJLqBDkSAPteygKzTCxcV1nJFrVmHrDPr49u5X6Qz6uLRkKrfXLEj5mFJBTzDIwy0tDEciXF5WxpykPH6qrvOflg72DY+wOC+HS0vNSpy7BkZ4oq2HbLuNa6uKKHCOvcL2fPsgr/eMMDXLxdWVuTiTUhboQvBEywjb+oPMzXVyRUWWwbW0w6/x/e0jdAV0Lil38o4661VDf0Tw9EGVLp9gWZnCwmKzO+TT2yNsaVSRJFg0ReGcmXac9tScplRVsHt7hNZDOi6XxOwFNoos+upu1jiwKYJ/SODOlphzroOshLyBuq5T/2SYgSaBJEPFmTKl8ye3AhfcqeJ7IYIIgb1cxr3Shr1yconeJ4LI1j6059pAEygL8rBdXDbpNC1ppHEyQQhB7ecfN8Uxn0yQgf3fvBzlCOlf0kgjZfz3U7DhD5y0efzchfCxreCcfGq1NCaOU2bF79Ub3zfm9sPkL/TLX4HPQhVoag3OG26I2tz7LRgaMJkoKy/Bduax9YX27XuC/he/aqrPPuM9ZC++I27X9jrNz3zUYFN27jcM5K9p/Q/o3v+QsZ3SM5l+/o8BCAW6Wfeo2R0xu2ABiy64N6VxC6HzzOp3MDh0mGhLnLPix5QUx2PydF3l/mcuJxyJi4hUFK3kkmU/SqkvgN9v+gj1fa/Hx+ws5HPn/DelNkJ6mGtf+xB9kcFYXZEjn38u+zm2UTL64S33snHQOHlgQ+bJlV8hczRX37s2/Ik9I52m9n+x4O0szq0CooTmnRv+wf6RqACNBHx//hWclW+M4bv4xfvwa3HhjRsrZvHx6anFkk4UIU3j5jVr6AhGVVUVSeJXS5cayN+3du7jibb4sb172hRum1oVK+8cGOHD6/fEBF9KXA7+snKeidABPNjYwy/2xNs6vySbry40upf+ek8fDxyMX48bpmTzkdnRGEZVF7zp6T6CCRokN1S7+PAc8w//V14Osa8v/sL6yBI7Z5bHJxgefj3MliQ1zJpCmXedlxrZWv1MkI5W4+/h+Zc6KC6NE622epXtzxuVRyUZLrjNic0ePU87/hHAl3QLVZ1jo3RBahMwob0aQw8kqZhK4L3NgWPKsSd/6tY+1H8bRaTkBbk4rjHHqx5PpFf8UkN6xW9imPq5x9BP/s8dABq/c3wmotM4DfH4Z+H1e070KMaH4oAvpSaid7riaN+Rp8S0Uo3bOum5CVakD6AhQZ7fgvQBaBteSm1QE8DQJnPuQQDfHmP6hN5d95ts+nYa63obzERoqH0tuhb9CD2w5aem7QBDPVvR1ImnWADo7d+RQPoABA1NxjG3924ykD6Alq41aLrxo3g86EKjvm+9ccyhbjpHGlJqZ33/dgPpA+gK97JxcBcQTcieTPoAVHSe6doSK1uRPoA/Na2J/b17qCtG+iCqkfpom1H19OXuZgPpA3iq48CEjmUyWN/bGyN9EE3C/kRbW6wc0nSebjcqnz7aalQZfbytx6Dy2REMs6HXrA4K8Mgho3Tl6o4hhiNG8vXoIeO+/22JizS93BE2kD6Ap1pDpn5ahnQD6QN4vtG4464Ws4LlwW6d3pGJz276fcJE+gAa9hvbbtlt7kvo0LwzXp9M+gA6tpqVN8cd0ysWz5KA0Jbjo9iprrVQxt0xcFz6SiONNxqnCulLI41jik1/PtEjmBi0MATeuLyZpzNOCeLX5rf++DymsB970QjJ7rGudxjdGBULARLFabSRR1ekjA3ZYqqezoyxEmjLBnfQicBh4WbpcBjJt9PCRpHtyFJqKxESMopkHp/TltqSv2cM+yxb1H1QliQUyfp2z7HH9x3LqS3bHj//Hot7xWMzri7lO8xui07l+HlWe+zm1SSPLd6fIkkm5c/E7QBZNvO1y7JbX8/kepcimxRBk22ybPHzn+c0n2mXRVduu2S6JplJp99i2EgSOG0Td1G02aL7JMOR1Jd9jEVEpzthZ4t2JhOzLrmsxy9Z/BQcC0gZFvdnCucwjTTSSCONkwzKiRdEmzCsvnPTOOY4JYifeR1gDMwYQ7r/4oSUCTOt46yUy9+a0pgmgrwLzG6eSAreJUa31cKFdyAlpk+QbRSd8WGDTeUZnyAZZfPejTRKZmrmvR+ry1kx46aU4+6ys2qoroy7mjgcOcyYZlQMLciZRWHufEPdgrp3xcYzUUiSxKpqYwzm9PwzyXEVj7GHNRZ6Z7I0Z56h7qy8xczOqgVAlmRurbzAtF+ZK49zCubEyjdVLjXZ2CSZj06L7zvFncubSuMKnTl2FzdXLTTsM9tbQJ3HmFLhg9OsU4AcCyzIyeGsgrgCZ5HLxfUJyp42WeI9tVNinMQmRcuJuK6qmCJX/CVxVmEO83OtYy3vqC0yEL3bawtNLqHvnp7L4cwLMvCeGXFlsQX5DmqyjIztAzPN5D0vQ+KyqXE7tw2uSUpVcNFc8/29croNzxjEyQoOp8Ts+cZ2HA6YMcdYN3WRneTHyZkJZXXxMZbMNzPR6lWpv3w9l9tNj7TkgYzlx2cCwX5JmYm02i4qOy59pZHGG42SrFND6TbbefxieNM4DXH1z8e3ORmQUwP21FXN00gdp0yM34YNGwh91+w6mSjuAhDavx/+9e9YWXrn7TgKjeIdkQO70R+7HyIRyCvAdsN7UbIm6E6aIrTgEANrfoiuhsioPgdX2VJsHvPqnB7x07fnIYSukjfrRhSH+YM7NNxK88Yfo+sRyhd+GE9enWG70DV2rbubwe7NuL01TJ37QbITSE2q6O3bTiDYRXHhcuxjrF4ebH+Brr6t1FZcSb63ztJmImgZ2s3m9ieozVvKrMJzJtWGEILX+reyYWAHy3LnsyyJmALsHm7hnoYnGdECXFWyjKtKl5nEK7YNtPClnf8mIgSXFs3ivVPPJcNm/nDfMdhBV8jH8rxKMi22AzzRfoD9I31cXz6TcnfqgjWpQAjBlv5+hlWV5fn5OBXzB0Szz8++4REW5HgpdJk/hIKaxvreIbJsCgtys44o7NEbirClz8+0LCfVHuuZunZ/hF0DIWblOClzm5e9njoUpH5Y49opLsoyx/7gaRjQ6fIJ5hbKeBzmMXUP6azZH8GuSCycYqMsd3JzWgN9Oi3NKu5MmcpqBbuFQEw4KOhsUOnv1MkpkqmcbTOLNbVrNK+NYM+QqF5lx+Ge3Hj0kI5/jYbuE9hrJFx1NiSL4z9WEAGVyOp28GvYVpUgF7zxM7DpGL/UkI7xmzh+8ORufrE6tTCCNxK3LK3gG9cfXxGwNE5D9DfD394OQ62QWQyDzaBr0QB1LUg0YCURkkWdDDYH6DLo/mg5FbEY2RltUpai/eoayLZom2d/As7+2FEc4OmF00bV0xK3X2WqctTWEp4+HXp6oKAAe8IqyGHYp80ilJMPXe0gKUiuo5tl0IfaEFoEJdcsgqC4snGWL0MdacdddTayy2vRAkiKE0/ZcmyZJZakD0B2ePAULyKrYIGJ9AFIskJJ9RW4s2qQJAmb07ovIQQjQwewO3JwZZjPT9RGZ3j4EL5AK0UF1veXpkfIcORSVXwuXo85b1wqCGsBZhaspDZv8uInkiSx0DubHHs2U9zWKxWzsir4RO1VrB+oZ052lSWxmZ9TwYdrz+fASDfzvJW4xvDT89pd5DrcY5K+iK5hkyTKXJmMaGFLGwCfGmFTXxcV7ixqPJOfgNg7PMzanh7OLy62JH0AVZluqjLHzrnnUhTOKZpYzp+hsIZbkch1jP0zUuiyUZmpk2W3Jj6XVrq4dJx+VF2nY0Sn2mtN+gAUGdx2CKk67qPwbMn0gCdLprBYtiR9AA6XRG6pjCNDIr9csbyHPCUyVWfa0VVQxmhH6IJQt8DulVDGcutUJJwzFJAFskM6rqQPou6e9pXFiKB2VKRP13X0PR3IhVnIhcd3wiONNCaKG5dW8LuXG0zxxUeCAhyfqFojbMDbVxzdezSNNCyRUwmLb4PObZA3Hdo2grcKhtuiJHCwPUoIvWXQ3wQjnVAwFWpWQePLYMuAmnNh75Mw0gY5U6NtuAshtwZ694AjGyJ+cOeCpxSCgzDUAiPdgALZhRD2R2P58qZG/4WHowSwavmJPkOnFU6ZFb+JqHpGdu9Bf/RR03bpxhtw1NQAEGpthL/9ytzIJTfgnJ8a6RBCEHz260T2Pg6AUrUC9xXfRRqN99LCAdr/cgkkCJ54V3yCrHlGt9LwUAvNz3yMyEgrkuygeOnHyJ15vcGmfedfaN36y1jZlV3D3Df9LVbWtRDr/nsVkdCAYb/CiouZfdY3YuVQqJ8Nr3yMoYG9SJLC1Bm3MX2O8dwOj7Tw1PNvRYi4IMWCOR9neu3bY+Wegd08+dpHCEeigh02JYOLl/6Q0oLU3Bl94UF+tu5mhsJRNSe33ctHl/8Vr2usmMWxsWVwN5/d+QMG1WE8ipuvz/o4Z+YtjG0XQvDJ7b9nXf++WN3crEp+veiD2EZjE8OaymWv/pSgHj92Fwr3r3gPJaOkXdU1Pr/zaV7paQTgwqJpfGX2RYYYwl2D3Xxg0xOoCc/XtMwc7jnjCty2OJF8tqOZr+16PSaqsiinkJ8sOhebPPEVIiEE71y3jvqRkVjdFLebP595ZkrtTBQhTeeT6xvZPhBNmyIBH5tVwnVT8g12jSNh7lzfQWdQwyFLfHJOPpdXpEYCdnZrfGdtOCbBvrxM5mNLjSuV/1ofZlOS4Mviaolrl6ZGXJoaVNa+FH9Wa2cqLFlhZJG6Ltj4eIi+tuiAJAnmX2inZGqc/IaGdXY9HCI8ejkkBaZf4SAnQYkz1KvT+lAYdVgg2aDoIjveJJfVSKvOwP0h8MfrHDNksm90ICnHhwBGnmxFe70bBEgVbhw3T0OyCr48AvTWAcJ/WcfhiybXFuJ468QnJ9MrfqkhveI3MVz985fY2jo8vuEJRkWOk1fuOrYK42mcxuith18sjaqQncwomAEffn18uzROD1XPiUJ/7DHLevHwP+OFB35tvfPTD1nXHwFa82sx0hctryOyJ17uX323gfQBDL72U/SI31DXveVeIiOt0bHqYTo3/AwtHH9BaWqQ1m3GcQeHDtLX9Fys3LTrzybSB9Dd8gzhYFwp6eC++xga2BvtS2gc2PNHfMNGCfeNW75pIH0AW3ca/cRf3/XTGOkDULUAa3f+wNT/eHi+4Xcx0gfgjwzy+H5rhdLx8KP6PzKoRsc0ovn5fv3vDNs3DNQbSB/AjuFDrO7eHit/Y8/jBtIHEETje/ueipWf7ToQI30AzyWVAb65+1UD6QM44BvgP23x/lVd57t7NhqUNDcPdPNc16EJHG0ca3p6DKQPoMnv55mOjjH2ODo80ToQI30Q9d74xZ5Ok6rnb/f20zk6tR7WBT/b1UtQS+3lc++WiCHv1mttOp0Jap0jQd1E+gA2NQpCamp9bVhnfFbr92iEQ8Zr2NWox0gfgBCw86UIIkEysHW9GiN9AEKDgy8Y2+55OYI6HN1HqND9fAQ9Yuxr5OmIgfQBhPfqhHYen/UHvd2P9lp3zMNHtPijJDBFRB7dRuJF0+u70TvfAIGuNNI4Ak4F0gfQMjBhVYM00hgfD91x8pM+gJ690GNWXk/j2OOUIH5TMqxdFk3Qx7i5E+uP4QqnPtRqUReX0FcHmk3bETp6kmRteNjYjtBCqP6eWFkLDVo+uP7+vbG/Rwb2jDnOUCAu0x7wJY9ZEPC3G2p8SeXRURhKw37zsQ/720x146HL12iq6/GnRnwOozVo1NHvCHajJZy3tmCf9X6BeH1jwnlPRHsgniqiLWD+iG1NqusJ+U020X3jHx9+TTWlfIj2NUZakjFwYNj6g6YpiQweK7T5zW6rqhD0BI3kpi1gLPs1wWA4tRfQcNj8vDYNxdvoGxn7eR4OjLnJEhELb1y/zzhe/5B5/GoYEi9jaMg8pvCIING7IjJgtNHDoAWS6vqtz5XWf3y8NES/+QRY1Y3bjs/84ap3pIlfGmmkkcYbjsHJfU+dELRvPdEjOC1wShC/poSP7iPCOwZBzE9wQcsdw4XQNXbc01iwVa+ERDVOScY2dVWsmDnv7aZ9ZHchtuxyQ132FKPapDNnKg5vdazsyCzG7jLH4hXWxd1BK2featoeHZIdT048HrCk3NiXw5lHboExmLyq4hJTOxlJKpvVpWaFzBqLuvGwtOJqU92Ssjen3A7ABQUrDOVVBcsM7pdn5s1EttDaPzdBAOcdlStM2wEuL5kbty+sMbRrl2TOKag22J9daB2rcV5hPA402+5gTrZR+VMCziksJxVcUWYdz3jZGPVHi3OLzXGIFW4H1R6jC+aqYqNK50yvg2KrlAFHwJwC40+UTYYlCQnVK/NlrLwebTIUZKX285abb2zIZgdvkkhMkUXi9JxiCVtC7F1erdkmd5psiAXMmm60cZZI2LONfTlnWbhYyuCceXxU/+SpHlNODXl2TurtTCtMqpCQ55QexcjSSCONNNKYFOabv0NPWsy55kSP4LTAKR/jl6jqKYQg/ItfQiBhqt/txvnhDxn2Cf3kC6AmrEbICvaPfQ15Esm21PZthDffh1BDOObfiL16pWF77yvfJ7DnXyB0FG8VRVf+EiXT+GEkhKB/998Zbn4Re3YFhQvejT3TSLQigV72Pv9hgkPNyDYX1UvvIq/6YoNN8+4/c3DHb0FEj83uzGP+qp/jyak12LU0/pfW5sdxuvKpnfkuPNk1pvGs3/wNmg49Dggy3eVceO7vcTpzYjaaHmHzvt9R3/IYQghqyi5kycwPYlNSF4R4qemvvNx0P0LoLK+4jounvTflNgCCWpg/Nj/MlsHdzMmu5Y6qG8m0GYV7NvUf4Ct7HqAvMozX5uZz02/g7ILZBpuf7H+Oh1s3oiGwSTI3lJ/BR2uNpPb1vkP8/dA2FEni7ZULWZRrJFmqrvP1Xa+wursJTejk2F18rG4pF5dMNdgNRkJ8Z9cGNg90k2N38rHpCzmzIPWP5Fc6O/nqzp0ENA2XLPO5OXO4sKQk5XYm3t8Q9+zrZCCsMScng0/OLqM4w/j8aELw94ODrO3yU+1xcHttDvmu1Iifpuv8dH2EnT06XqfE+xfbmZ5nJCftAxr/93KYkdH89Rl2eO8FTgqyUyN+kYjOK89H6O3RycyUOOs8B94ccxvdh1T2rFEJBwV5pTJzVzmwJ+UlbN8SoWOLiq5Bbo3ClLPtKAnkUOiC/g0qvgYdR75E/ll2bJnGNoQm8L+sEtytQVig5Mm4z7LhmHb85N71jgDqy50QVFEW5aPMnZjQTyKEEET+vRX9QDdkOLBfORelOn/8HUeRjvFLDekYv4mhtc/Hyu+tPtHDGBfPfvJsaosm6OWURhoTwQM3w57HMCt1niSQbPCW/4NZV45vm8ZRvyNPGeKXfrGlkUYaafzvI038UkP6/ZhGGmmkcfrgtEnnYJXDD8D+mTuQR5UL9UCQyM+TklVOmYLjLTca3KxCP/gshpkPZwaOD92NJBtn0tVtz6CtfQjUMHLtMmwXvhvJltqqoG/Pfxje8SB6sB8lqxzv4nfhqjzTZNe/958MNjyF3V1IwcJ340xw9QRo3fZbOnb/BaFrZObPYcZFvzIlZvcNHmD/xu8x3LcbIQlyChYzY9mXcCakbOjr2ULD3r+gayGmTLuR4vJVJCMcGWbNa5+lp28rkiRTWX4pSxbeZejPH+zhuY130T90gCx3Kecv/hY5WdWmtsZDn7+VZxrupWlgGwBV3rlcNO09FLirUmqnK9THJ7Z/i0Z/C3bZznunvIWbKo0uo34txM/qH+HJri1oQqM2s5Qfz7+DnIQchaqu8ZntD7FxoBkJiXPz67hr5mVk2oxujPc3beGBlq2EdY1VhTV8vO5sMpJWjP1qhD8c3MLWwS7meYu4o2YhmUn3z9qedh48tB9ZkripagZn5KWuZgrQHQzy2wMHaPb5WFlYyE3V1ShJaQa+s3Mfz3Z0E9F17LLEsvxcPjdnOln2+JgaRwL8qaGNnmCYi0vzubpycuN5sWOE723vwa8KijIUvrekhCkeo0Jmm1/jj/v8tPt1VpU6uKHaZZkaoTeg84/dKu0jgiWlMlfW2pAT7CKaYPUulYNdGmW5MhfMteOeZNoDv1/n+SdC+EZAscHSs2xMqTFeM10THNis0tuikZ0vU7vEjiPDnMev/qkwYR8oDqhZZSd/uvF59R/S6HgyjBYAd4VM6VUOZFvSqp8QBF7TCO3SUHIlMs+zoUwyR+GxgN40iLrmEGgCZWkZyoyJr+SlkcaJREPnIBf8+JUTPYxx8fKdq6jMs86bm0YaKUMIuPd8aN98okcyNmwZ8O5nISGkJo3jh1NmxW8i6RxCP/wRaGbFO2nJGTguiLrqhX7+ZQhZqD7kFuK84zOxonZwM+q/vm0wkeddiP3isceRDH/90/S9cHdSrUzRdX/GkR+Puxuo/y/tr8ZTLtgyCpl2/cPISvRDeaD1Vepf/JShlaziJcy48Bfx8aoB1v33KtSwUUTBnT2VpZdF0z4E/J289NSN6Pph8QWJFefdS26+MdH5cy/dQV//DkNdbc3bWDT/E7Hyg89dy0ggLuZit3m4+ZKnTGR0wN/KU9u/TvvANkpz5nPpvC+R447GsOlC50drbqQ30GLYJ8dVyqfPeghFnvi8xJvXvp/uiFG85adzv8jyvPixfWX333iqy/jjV5lRwIPL7oyVP7n1H6zrNyb4Pb9gOt+ce22s/J+2XXx374sGm8uKp3P37AsNdV/d+TJPd8bbuqComq/PjRPtfcMDvHv9szFVT5sk8ZcVl1I1iUTv71y3jv0JIi/vnjaN26fG3Up/ua+BB5rMgjyLcr38bEn0HIU0nbe9so3eUNwN+vNza7iszDrX41hoGA7zzleMfbkViScuqY6VNSF4x+oB2vxxAZOPzHZzfY3RNVcIwV0vhDg0HP+detssG1dNj5OxRzaGWd8Qf+6nl8i84xxzcvqJ4N8PBAgGjXWXX+M0uHzuWROmaUe8v7wymaVvivcX9gk2/zloym278HYnTs/oJFVYUP8Lo427WqbiBuO4/a+p+J6MXw85VyLvw04k+fjm87OCGAgS+tWGuGKnBI53LkAun3zuSSukV/xSQ3rFb2Kovsta9ftkRON30i5vaRwj/P0dsPuREz2K8SEp8GVrAb40jDgt0jkUOzPHNwJL0gcgdu6KF6xIH0C/UbZc27vGZKLvf21i4xhFoHG1Ra1OsOllQ81wk9FODXQT6I4Tr669D5paGekyqh8Ndm8xkT4A/1ADIX9U1bO749UE0gcg6GwzEhhdj5hIH0BL27OxvwOhPgPpA4ioI/QO7k3ejae2f53W/s3oQqO1fzNPbf96bFvHSL2J9AEMBNtpHd5tqh8LbYEuE+kD+Gf704byCwlpGw7jUMCo4rnVQgFrdY8xBcTqrgNmm+4GU92L3U1HLL/S3WpI5aAKwZoeK0XVI6MtEDCQPoDVnZ1JZWu10s39g4RHVW93DY4YSB/Ai539VrsdEa92mRVN/Zqg1Rdvu2FIM5A+gJc6zAqSHT5hIH0Ar7cbn/Ndrcby/g6diJb6hJauCxPpA2hpMiqvdjYax93XphNJSPsw2KyZSB9A1/b4OH0HzTaBQ+adwruNx6b3C9TOEzNZp9X3GdI0IEDb03tCxpJGGmmkkcYEsP/p8W1OBggNusZWp0/j2OGUIH6dodTk7U3wTmBGOsnNU8o1C2xI2YWmuiMhWb0zXl9hKDuyjGUkGYcnLhaSkTvd1IbiNK4KuTzWfcmKC7szGijuzqwwbXdnGveTJBt2u3nFKTMzPh6HPQtZdiRZSHjcZjGR9lEXTquy11mMIpldZ2VJIcc1cYGTXEc2isWtXJs5xVAuzzC7pblkY/9ee4bJpsRpDLSvcOeYbEozzOesPKnOXDa785RnTHCSIwG5DgcZivH+rXAbVWqLXNYrYDl2G/ZRt8nSDKfpLJa7U185K3ebV2olINcZH2Nhhow9qbNyt1m0xOuUcCZVF2cad8zzGMvZGRK2SfyyybKEhacp2V7jANzZRiNHBiR6+Tq91qtxmUXxeke+2Ua2EBZWcpPsFFDGaP94Q8o1PxtSnrkujTTSSCONkwTuU8gd32v+Rk3j2OOUIH4ThbTyLMt6+5veFC9cc5v1vlcb0yHYFl0O+QmS/HYnthTcPAE882/BXjDTUJdRcz4ZU40Kkfnz3oEzb5TcyTYKF70fuydOosrmvhObM1FdT2Lqyq8b2nBnVVE1+w4wpCuQqFv8WeTRlBP5RUupqL46ZlNYchblU4wuJZIksXThF0m8NRTZyRkLPpdQtrN89scNfc2begsZTvMPTGnO/DHLmQ4vV07/mIH8KZKNy2o/TLZz4u6FGYqLT0y73VBX7MjnHZXGVBGfqbvWQPQk4KPTjHGAX5p5JUrCcdkkmc/NvMxgc9uUxZS54iQuQ7bx2enmWMlPTV9Ojj167rNtTj493Zgq4sLiSlYlpG64pKSKlQWpp2DIUBQ+OXMmrtFY17KMDN5ba1Ry/fzs6WQoSakRJInPzZkei6sryXDy7tpybKPluiw3N1enrjB6bnEms7zGiYG3VmfjTmBjOQ6ZD8xyx8jfFI/CbdPNJMJtl7h1nh3HKPcqzpR4yywjsbxioR3PqJisyw5vPsNuGSs4EcxfZCR5OXkS5VXG8zZjhZ3DTgiKHWaf7UBOcL3MLlPIn27cJ7NIIm9afNzOAgXPjAQbGUovS55MAfd5NpSC0bYV8FxsR3afGOInT81BWRhXG5br8lDmTS4GNI003mhMK0g9ZdOJwKLydHxfGscQt/zrRI9gYphzPTjT9/4bgVMmxm/Dhg1mgZeP34rTaVyR0MNhIvfdD0NDcPbZOBYvMn0ECiEI//EHMNAPM+bhuPytSLI1B9a6DkJgBLliFpIyOS2cSP9BdDWI4vRiyx77wz40cBDFlYvNlWO5fbBjPeGRdgqmXoE0RvxbONjHyMB+hK7iLVyAzW5+kAL+TnQ9QqZn7NkVVQ3S1v4idnsWJcXLkSTzakw4MkJbz3qKcufjdlnPKh0pxu8w/JFBBoPdSEhkOQvIdExOynpE9fNc9zpq3OXM986wtAnpEXYONtMVGuScgtlk2szpJzRd54WePbhlJ2fkVuG0SPMhhGDvSDcBVWWOtxiHbD4/ACFNo9k/SJXbi1OxtmkL+JAliZJJ5JJMxEgkQmcwSLXHYxJ2OYy13b3oQmCTZRbkenFZjGkgHGEgrFLtObrVnIPDIbb0BVlVnEneGGkchsI6PSGdGo9yRLLmiwh6A4KKLMkg7HIYqi7oGRLkeSQctqMjRqGQTlODRmGxTG6e9TXTdYGvX5CRLWGzW/cXHhEMNKl4ihXcBda/L+EBnXC3TuZUBckqISHRe03rFshZEnLGiSF9hvEMhhCajnycVvvSMX6pIR3jN3G09Q1z3g9eIqyDA9BG/yVC4tiI3itEp08j49gd7s9th5fuvICCrPQqehrHGELAKz+B1s2gRyAjDwaaoXQhNL4ItZfCobUw1AmokFkIBTNgqBXCPtA1cHkBAa5c8PeC6o+2M9wKdg9k5ICvF7QIBIdADUHpvKi6mc0FGdkQGIC2rRDohYxcKJoDmXlw7qfBm1r+4tMZp42qpyV+8n+QkMcPQG1vh+7ReL3nn0etrMReZHTRDG9ZB32jNrs3Ey4sxbnsPMsulKIay/pEROpfQG1Zj33mldhK5hi26aFh/AefByHImvsWy/2FFmGkdS1qcABJVnAXzcORbVa11DWVzn3/oGv/P5my7LN48mcZt+sq/Z0b6G17GbennOx8a4UkXQ8z0LcDEGR6zInGhdDo6duCEBqhcD+9fTsoyF9gspNlG/5AF68e+hZVxauYMeUqk02Ou5y3Lr/HchyH0TK4i5eb7sem2Ll02gfHJH59oS52DWxiSmYdlZ5ppu0em5urx0kiv6n/AC/37uKSooWWpA9AR9Ab9PH37g281tfAe6eea1L11ITOMx31NPr7uaN6CbO9xaZ2hiIhXuttpTTDMybpAyibgHtnQFP556FGhtUIN1bWkO80jl0IwfMdHazt7WVxXh5vLi+3JHVn5OfyWk8/guhqphVyHHZyHKnntExGTZaTmqwju4pmO2SyHeM7HmTaJTLHIFgAsgS9Izqbm3TqimVqSyb306brgs52Hd+IIPsI8w+yLJFl4a55GFpY0H9QZbBFRw0LMvLsloIsjhwZh0WuwMMQuiDSoCMioOSNQQw1gb4/+nkp19nHJJATgd4fQhzyIZVnIudbXzvJ62S8HvSWfsRgALmmAMltXslMI40Tgd+/3ER4NJTWHFEcxbGaCrcilUfqzx+BHz29l29dv/AYjSCNNEYRHICG1dD4Mgid6F0nw6HXorF1nbuiq20FdeDrgdaN0PI6IIHNGc2zFwkQvaMV4HDcuwL2TNCCoOvRF7HTGyV/CNj/+KidBA5P1EYdDd0K9EDfAXC4oWIZLDqFEs2f4jhlVvwmpOr5wmpYv960Xb78cuzzoiQo9OC90FxvbqSoAuetH015bL5HP4HWtDZWdiy9A9fy6HgifQ10/uu26AwLgGyj+No/Yc+Lu+Fp4REaH38P4cGDhnZLz/o8OXVxIlX/8ucYOPSCwaZs/vsom/vOaDtqkI3P3EpgOEFARLJxxkV/xJMQI9jS9BjbN3yDqLKEzPwlX6J8yhWx7bqu8uKaD9PTa1S/rK56E0sXfSlWDoT6+eeLbyMUHojV5WbVcu2q+45wtsz469a72NltPK431X2SlVPeaqjb3LuGH+64E3U0Of1NUz/MVVXvSKmvL+++n6e7tsTKbys/m4/VGsmqTw3x1td+S18kHleqIPH35e+lLCMHgJCmcvkrfySox0U/3lu9lNtr4hMw+4b7+MjmJxlRo+O9pnw6n5lhTuMxEXQHA9y8djV+LdqfDPzyjLOYlxtdZRVCcMuaNTT546Iq2TYb/3fmmRS44gRxOBLh/a9vpdkfFTia7c3i50vm4xhjtftUgaYL7n0+RFt//LdsdrnM289KLT5R0wTPPBZkIEEnqLxK5pwLUmsnNKyz/YEQWoKOks0Ni25zIadAyoQmGPhzGHVU9EXJk8i5w2lw9RQhQejeYURH9BNTKlFwvi8LaRLpLLTt/UT+1RT7ErVdVYltUerxIZEndqJtao4WnDYctyxHLpm48md6xS81pFf8JoYV33yGjuGx6N7Jg/xMGxu/dOmJHkYa/yvo2Q+/OAV+TmtWwW2ngProSYDTQtVz7LWSJFiQPgD9qafiBSvSB9BlVpccD3qg30D6AMKb/hr7e3DDb+KkD0BXGVxvXP0abHjSRPoAujbF7YLDLSbSB9C2/XcIEf0o7G55zkj6AITKwR3G/vbt/DVxOUF9tBxHR9daE+kDaGz+L8MjzfF2mv9jIH0A/cP1dA9MXI2zy9doIn0ATx34panuocbfxkgfwMONvyesWUgwjgFVaDyTQPoAHmpba7J7unOXgfQBaAj+2BhXeX2gZauB9AH8sWmTofzXpu0x0gfwn9Z9tAdGJjzeRNzfdCBG+iB69X62P65Uu6mvz0D6AIZUlYdbjPf0E21dMdIHsGtwmJe7Tn1VxvoO3UD6AHa16nQOWkhrHgGtzZqB9EXrdPp7U2unc7tmIH0Q9Yrp2TOR+f84wvv0GOkD0PoEwc3G+07bFo6RPgDRoaFtm9zHrfp8u2G5Q30+dYVZMRiIkz6AkIq6xqyCm0YabySEEKcE6QPo9anjG6WRxkTx5F0negQTw8EXoy6laRx3nBLEL2uSsXUx6Kl9uE0YEYvUEAmEQA+Z0yvo4ZEjlmP1ER+HV2P1yBiqpkKLET91jHYiYaPMv5rUVnI5EhmbnEQSbMOqtV0oPHH5/+AYbai6OSrCn2Qb1kOoYuIvSE3oJhceTZjvi5HkL/ZRDKnxa91vkRIkuS2fajwGAfi18aI9rDEUMe+X2P6gan0e/En1Pgs7q7pTDcGItddCaIz6sWBxmkfrU2tHC1nbq8HU2hEW7YjQ+DaM0f+4/QWTXrrJ5Ym0EbK4n6zq0kjjDYR+8js2pZHG8UHQ/B160iJN/N4QnBLEb0Cb4IdDqbUCoTQ3Ie7OOUbgtC31mCY5uwzJY0xhoEyJKzd65t9i2scz7yZDOXvqJch2s6hHzvSrY2IX7rwZOCyEWLLLV8YSphdWXohsMx9b1YybjeWaawzlyqnXGsplJefgslDUzPXOJDcnrlBaW3EFUtLtY7dlUlFkraxqhcrsOeRnmGMMFxRfYqq7qMw4zrOKLsZtm7gClFO2U+M2xuEt8Fab+ymahWIR+3ZT5fLY3zdXLTLFOJ2Vb4zJvKq8zlCem13INE8uk8GNVTWm/t4+JR7juLKgIKboeRgycEWZUUjo4tIig7Jnjt3OuUWpJWc/GTGjTCEjKYws3wMV+an9vFVUKdiTfgY8WRIFRam1UzjbRvIFk2QompPaBJZjhoKUGP5pB+d8o/+DbZ4DXAmduSSUuZOLqVPOyE8qp35vyEVZSBU5xnYWmZ/xNNJ4I6HI0rhxqScLTpVxpnGK4JxPnegRTAyZRWBLx4O/ETh1Yvx+eQ+sNrsgOpPEXUJ//j9ITF49fTrOa4yy/qGf3Q3hBDdBxYbzE9+a1Nj0sJ/g899E6z2AbcqZuFZ+1KBOGGhew9Cm3wOQveidZEw529RGaLCJ/n3/JjLYhGR34ylbhrf2TUgJBEQNj3Bw3TcYbH0FJIn8KZdSvfxzSAlqkoGRFhq2/ozB3h04nLlUz30/BeXnGPoSQqe16XEGereRU7CA8qrLDf0A+AOdHDj4T4ZHmpAkhRxvHdNqrseRlN+vb6ieNdu/y+BIE3nZdaxa9FXcrtQ+FgORIR7d+yN2dr+ILMksLbuGy+o+hGxBvl7rfp6tfeuY4qnjwtJrsMmpkfWwHuHbex9m9/AhzsiZxqfrrrVUkmz293H3rkdo8vXitWfwhZlXsDSv2mCze6iTr+x6jsFIkAuLavn09HNMbW3sa+f57kZKXR6uLZ9B5lH8qG0b6OWe/XsI6hpvrarh0lLjx3RXIMA3d+3iwPAwFW43n5w5k+nZ5riqxhE/j7Z2YJclrqkopSTDWuDmVMOgX/DMjjAdA4LqQpkL5thxTyLOzTeis22TymC/TmGxzNyFdpyuSbTTpdP0aoRAn44rR6LmfDvuMRRCjwRtUCewQYOIwLXYhs2ChOo9Gtr6EEigLHUi56feD0Td4fRt/ejNPqQKN8rCvEmlxRChCNrG5qi4y8wSlJrUfhPSMX6pIR3jNzFouqD2848fM/GW4wEFqP/2FZNOR5NGGpbY9Sg8eBvjyw0dK03bFFE4G97/kjEhbhpj4mjfkceN+EmS5AJeApxE1UMfEkJ8WZKkGuABIB/YCLxDCHFE5/v0iy2NNNJI4/TA6UL8jtU7Mv1+TCONNNI4fXAyp3MIARcIIUYkSbIDr0iS9ATwSeDHQogHJEm6B7gD+PWRGgLMOfwOY2o5zhujqpThAw2Ihx82bs/MxPHe9yCN+nCFW5oQD5jFQ5QP3Y0tI7Xkkb5HPo7WvC5eIcm4b/0XtqyoS6Guhuh8+Ba0oUPR7bId74qPkTXnhtguQui0vHAXI4deitW5S5dSdfHPDLN+B179Mv1NcZEah6eS2rO/gTsvnq9O11X2rf8mXc1PIYQgK282c1Z+B2eGMZ3FeGhpe4GNW75NODIIQI53Ohec8zsUJa5uOOJv54VNX6B7YCcAdlsWFy35DqUFqd2L/YE27t/+BVqH9iBJMvOKL+D6WV/ErhiVFP/Z+Hv+1fQnVBGh2jOdry76LY4Em0Z/Kx/d9nW6wn1kKhl8acaHOK9gmaGNvcMtvH/LPQT16DdUmSuXPy/+BB57fNWr2dfLO9b/kUjCzNg1JQu5c2bqKms7Brv48b7XaQ0Ms6pwCp+YvgxXUrxqRNf5+f6tPNPRTJErg4/WLeSMPHNS7E19Pfx83046QwEuKC7jo9PnmHIH/vHAAf7d0kKGonDHtGlcnOT6/HR7J9/asS92ZNM9mfx4yTyyk/0bx8G2fh8/291BeyDCecXZfHRWCU7FvBL1z8ZB7tnbT1gXlLlt/HBpCaXueF9tfo0fbvexZ0BlQZ6NT83zkO8ytjMSFvx+a4TtXRpVXpl3zbdTkW2x6iUEz2xX2dyo4nZKXDLPzswy4/mpb9Z4bWuEUEQwp9bGsnm2Sc2sh/w6rz8Sxj8kUGwwc6WNihnGc9izV6XldRU9IiieZ6N8qfU5Ht6n0fNKBD0o8M6zkX92fExCE4w8FSG0Q0POlvBcasdRM7nVvPEgdIH6bBva1j6kTDu2i8tQ6swrxkIXqM8fRNvaieR2YLuoBqUuz2Cjtw0SeWonos+HXFeM/bLZSA7zq0bb14q6ehsiEEZZUINt1bzTbaXjmL4j0zgyHljXyF3/3nmihzEufveORVw0Z+x8v72/Ch4AAOPOSURBVGmkkRI0Ff5yLTS+NL7tiYLdDR/fDpmnfujJqYDjFuMnojisyGEf/SeAC4CHRuv/DFxzVB01tMb7TCZ9AD4fkf8+FrexIH0A2m9Sc/UM7fyPkfQBCB3/ffE0BL3PfSFO+gD0CINrfkCoa0esqm/3gwbSB+BvX0/frr/FyiM92w2kDyA8coj9L34akRAM27L3PjqbHkcIDdAZ7tvB3te/ltJx+QOdrF3/+RjpAxgY3Me6DV8y2L24+Ssx0gcQUYd5ev2n0PXUhBwe2HE3LUO7EOjoQmVrx9O80PhHg027r5kHG+8lIsIIBAdH9vLTXV802Hxs+zfoCkclGX1agC/u/jFBzThJ/pGt98ZIH0BbsJ/P7fo/g817N/3VQPoA/t2xhZ5gaoqcYV3jrm0vsGe4l2E1zH/b9/PHg1tNdn9r3svDLfUMqWHqRwa5a9urJmGYgKby+W0b2D8yxFAkwr9bmri/0aiU+FxHB79vaKA3HKYlEODrO3ZwyBcX4xmORPhGAukD2Dfi40e7x1C5HQMhTefzmw6xbyjIcETj0ZZ+/trQY7JrGgnz0919hHSBAFr9Kp/d0Gmw+ebmETb2RPCpgjVdEX643XyO/297hNfaNPwq7OnV+dkG64WPDQ0ar+xV8YWge0jw97VhRhLEVIZGdJ5+NczAsCAQhA07VPY1Ti6QfNMTUdIH0XfqzpdU1Ehc3CfQr3Pg2QihQUHEDy2vqfTWm/uKDOm0/zdMpE+g+aHvNZWhHXG7wBqV4HoNEQCtUzD09zD6JIVbxoO2vgdtbTf4NUR3kMiDBxF+87OsbWxHW9sKfhXR4yfy0G6EL35NhK4Tfmgjom0Qgir69lbU1ftM7YhhP5F/rUX0DoM/hLZ2D9o2s7rx/zLesHdkGgCnBOkDePdfzCEtaaQxabzyo5Ob9AFE/HDv+Sd6FKcNjqu4iyRJiiRJW4Au4BngADAgREyOsQUoH6+dud7Uc0klQjQ3j2+UorqhuvfJMTbEYwfDndstTcLt8R/2kZZXLW2Gm1bH/u7aZ0FogUigm7C/I1Ye6Da/MAa6t1iPcwz09m0nnu4hjr7++EtTCEFnv7ldTQsy7G811Y8FXeg0D5rP0cF+43Gs63nOZHNgOGk8IWNaAlVoNPiN133YIv3DnmFjyoOhMVJEvNCz17J+LDT5BumPGNvaPNBpsts6YCRNfk1l3/CAoa5+eMiQGiLalvF4t/Qb1VR1YNtAvJ09QyOWnvsb+wYsasdGw0iIoYiRxGzpM6vObus3n8cmXwR91LVc1QU7B4zP3NY+8zO4OymVQsuwYMiC/DR2G+1UHQ4l7NvRo5Ps1d7aNTm135GBpIYE9LXF64bbdVOYxHCrmfgF23TToxZoiVeEm4wbRQjUjuOjUKw3JZFuVaC3+i3sBpPsdPTWuHKw6PfDsFF6VG9OypEB6K29JrVlvbk7xVGf+jhW78g0jgxVO07K3mmkcbJj/zMnegQTw9DEvx3TODocV+InhNCEEAuBCmAZMPPIe8QhSdJ7JUnaIEnShhfq9xzVOKTSkvGN5NRcqJSac8bYEHfpsufXWZrYC2fH/naXnGFp4y5dGvs7v+YySxubMwd7glJldt5sk01W3izrcY6BqHKn2d3Kmx1XkZQkifxsc7uy7MCTYa2sagVZkin1TDfVV2Qbj2NxnlkQpzLTOJ48u9fYNjJTMozfSxmS2d2u2m10q3SPIRhzVt40y/qxUOnOJitJzGVWtnkCY2aWUenTIctM8xiPpcaTRYZivD9nZecYy17jPsl1tVmZpu0As70TT6wNMCXTgTvJrXOm16wmO9NrTnpekmFDHnXls8kStdnGY5rhNbsDTssx3otFboksC42c8jyjnSxBWW68rijP/FNXnKLq52FkZJufj5ySeJ3HQoAls9hc5yyRTY+aqyRuZy9P2seGpbjLsYBcnqQsLINcYr6ucllWUoWEXBJ3kZe8GeA2XiC5NMfUjlSSC0lunXJpnsnufx2TfUcmvh+7u08/wpwqbBau6GmkcVqgeuWJHsHEkJlaSFIak8cb8msohBgAXgDOBHIkSTr8hVcBWNJ8IcS9QoglQoglhYUTuyGkSy42V9rt2K+6Kl5+081mG0C+7RMT6uMwXItuQi6cYa6/4fexv/Mv+jayK/FjRiJr0btwlcXJXsHcW3AVzjO04cito3DBO2Nlb+kKsoqNsXOKI4dpZ38rls4BoHLmreSVnBkfi6eSmcvuTum4PJkVLFn4eWQ5/vHmzihlxZJvGuzOXXQ3WQnESpYdrFr4VRQlNeXKt879KnkJ7dTmLePCqXcYbKZk1XFp2Vti6SOKXGV8bLbRNff7c+7Eo0Q/Xu2Sjc/WvofMpPQW3513O0rCLe+1ufn23FsNNj9Z8FYT7V2ZN41yd05Kx+VSbHx1zrmUujzISJxTUMm7axaZ7G6pnslFxZUokkSRM4Mvz1lOtt14Dj02O3fPWUyR04UMnF9Uyq3VxkmFy0pLuaGyEocsk22384mZM5nqiX+Q5zocfLiu2nBspU4nn5lVm9JxuW0KX15QQYnLjgycW5zF7bXm57Mu28k7pnmRRzvMcch8a7GRZH9+gSdG/ubk2Pj0fDM5vXWeg9kF0WtWniXx4SUOyziw5bU2FlcrKBJ4nHDtUjted0LqimyZ85bZcTlBkWFuncKsqZOLl1t0qQPHaFioJEHdMhsOZ7wvd4HMlHPsKE6QFChZoFAww9yXI0em+BI7SkbUzjtfwbsgbudeacM5VwEJ5GyJ7OscyBnHJwZOWV6IvCA3+kbw2LBfXYWUZZ4EUZaVoSwojjJrjx37m6cjZcdJvmRTsF+7ECk3+izKtYXYzjdP7sg5HmxXLAF39IIoC2pQFqU2ufK/hFTfkZN5P57u+MC51Sd6CBPCl6+c8Px4GmmMj1WfhaI549udSMg2eNcYXnRpHHMcT1XPQiAihBiQJCkDeBr4LnAb8HBC4Po2IcSvjtRWompZoshLciqHwwi1d4AEtvx8lDGEK0J9PeD3Q3Y2zqTVk1Sgaypq2I+kq9gzrWestUgAkJBtDlPqhHg7EbRIEMXuQh5D0lbTNERkBMnuRjmC7K3QVXQhjmgzHoQQaFoE0LHZxpb813UVXVePaDMRaKOxgYo8tt6QEIKIHsKhjN1XUA3iGmcsgUgISZZwHYGkjoSDBLUw+a6soxacUHUdm3zkORZV11Ekady+xmtLEwIZxmxHCEEgomFXJOzK0QmFqLrAJh95vLoQRHRhKf6SSjsTsYGoZLssHfn4hQB5Am2NB1XVsdnGPi4hBAiQxulrPDuhCzjCMR1LTLSvidgJTUcaZ6UleuwCKeGePo1UPY/JOzKt6pkatjd109QXoHvQR0lOJpKio0ZA0SMMRSDDrjAUCKPqOjUFWUiywoAviM8fwpHhIkPS0SWZvkAYpyxRnutGkkCSBMMBDU0TeD0OukbCOCTwhVQEgt5eP9On5KHpOt0jIbIUGZ8mqC12MxKCyvxM6koml+s1jTTGhRqB8AggQWgInB6IRCAjO1ov2aKxdroarc8tg3AgOrvpyITAICDA5YXB1mi94gBHBjizYbAd3DkQ9kMkCM5M0CIw3A05pdE6SQFPIagB8A9GPeRcmeBKzfPodMfJrOpZCvxZkiSF6Dzyg0KI/0qStAt4QJKkbwCbgd8fqZHD0DQN9Qd/MNSFvvtbcx6///wH9kbFBFRFgauuQqkzrmqE7v8VtDXGyuHFK3FcYMz1N1FIWgj2PYkeHkGffgmy15xoXZYV/PVPow63klG9CkeBcUZPC/voWPddfO3rURxe8uffSs60Kww2I93baFr/fdTQABk5tRRMexO5lecbiGQkOMDWlz6Cb/AAis1N3eLPUDwldTXKkZFm1q7/Iv5AO7m5c1gw5yMGV0+AUHiIDXt+xcBII9PKL2XmlGvHaG1iGA73sqX9CRTZweLSK8l0xN0UVT3CK51P0hlsZVnBedRkjT0j2hnu45nWV8mxZ3NF8SrcFiSxIzzArxoeJyI03lN9CXOyjcnXv7TjP6zu2YuOoNyVw53TL2NJ3hSDTV/YzxMde9EFXF4ynQKnebXqmY6D/LlxK4OREPO8hXxi+goKXW6TnU+N8Hh7IyNqhIuLq6hwj60uOxbpG4lEeKK9HZ+qcnFJCeVucz+qLni+s5smn58zC/KYmzO5H1tdCF7oGKJhOMjSAg8L88zHPhDSeLJ1hBZ/BLsMc3JcnF+aiZJAFLoCGt/fNkKLT2d5kZ13z3DjsRuPLxARvNKisbdXx2WDM0oVFhUbCWsoInj9gMrWZg1/SFCZJ3PVGXYyXeZzJUlSsoehAYeaVOr3qASDUFQiM3eBOY+fEILdayJ0NWp48iQWXuTAljRuf59O6/oIWgiK5ijkTTP/1ApN0PJQiGCHwFEoUXG9E8Vp7Cu4TSWwSUXJlcm82IbiNh+TUAXaljBiQEeZbUcus1DQ7AihvtgPYYGyPBvbdGvXXzEYRt/eD04FZUEuksvYltY+jPbKIYSqoywrwzbNPNklhEDf3YHeOYwyrQC5ymyjD4ygrt6OCISxLalFqTstw9iO6TsyjfFRfddj4xsdT7xy5Dim2SUeHv/4qjdoMGmcNmhaC397OwRHtQAkBYQ0mrYvFX2LxDx/Vjn/pGjYVOHsKLkcaDQ3YXNDZj4Md0QJ47X3wvSLUjygNI4Gp04C9xvfN+b2w+Qv9Nf7oK3NtN12zdUo06PuRqF7vw1D/SYbqXYOjmtuS2lcQlPx/f029L5RhUV7Bpk3/B4lf6rBrufJTxE8NCriIikUXPoDXJVxl8x9D1yGFhow7JM35xaKl3wYgOGuzex99gOm/oum30DVkk9HxyJ0Xn7oHETSQzxtwceomHHThI8pHB7iP09cgvGBljjv7F9TmB91VVS1IH9/7mpC4fiYZ1Rdw8r5n5twP4noD7Tz89duJaAOAZDrKuVjK+7DaYt+nH5v+6fY1PsKADIKn5n3Axbln2VqZ89wA+/b+iVCelQIZaZnKn9Y9C1DMviWQA9vff376AnH95uFH2S+txqAm1/7HQcDRuEUgO/MvY5zC6LulYORIO94/UF6wlFRk1x7Bn9Z9hbyHHGy9efGbdzbYBSpccoKj53zVjISVmJVXef215/hoC967BmKwr1LLmRqUpzfkRDWdd61bh2NoyqeGYrCb5cto9pjJJBf276HZzqi8UAS8JV5M7mgJHU3se/vaOPRlvgzdNfcMq6oiM9UD0c03vVKK11Bo6DJ5eUe7pof7c+v6lz1dD9qwm1W5JK57/wc7KMrX7oQfPHFEI2Dxt+ot8yycc306DnUdMGvnw3RmWRjV+Cuq1w4bBNfJdu2KcKubcbnx+mEK6934UhIBr/2X0GGuuP9KXa46J1xt+KRDp2dD4cMj1DFCoXyJcYV5v0/C2DIzqZA3cdcsZU/3wth/C/Fz6HkgvxPupDsxmMK/XEYvX503DI4bvOg1MbvMa0pSPiPbYbx2K/Ix7bceI/pPUHCv90H4agQhlTgxPG+GUijq5paQz+R+3YY9rFdUYvtDGNcb+SxHWhb4mrGtjfNw7YgPiGm948Q/u2TkCC4oVy6CPvi6PN1uqz4HSukV/wmhhNO+iaIkiwn676Q/hBO4xih8RX405UnehRHxi3/gtoLTvQoThkc7TvylIh4zrGbhSIsYUH6ANQXVscLFqQPQNSnLvWsHno9TvoAIgEiO/9tsIkMNMdJH4DQGNn5YKw40va6ifQB9O/5R+zv1q33WPbfXf9vtFEV0c7GJ0ykD6Bx5x9MdUfCjj2/wTyLI6hveChWOtT5qoH0Aew79Ci6mKQ8fvtjMdIH0B9sZ2fXiwC0+5tjpA9AR+PJ1gdNbQA83P50jPQB7BlpYPPgboPN7xufNZA+gN82Ph1tWwhL0gfw+4PxMTzbVR8jfQD9kQBPdew32D94aJepjZCu8c8Wo1DR632dMdIHENA0HmltsBzDWHi9pydG+g638WircWa5LxTm2Y64CIQA/tGcuoqWT9V4vNX4DD3YaDxnL3b4TaQP4KnWEYbC0foHDgQMpA+gK6izvjt+/Xb36CbSB/DEgfh9frBbN5E+gIgGO1omPpMphGDvLrN9KAQtTfFj0XVhIH0Q9Wbpa4/bdGyPmB6h9s3G8xHq1zCl5NbAn6DkGXjNuI8IQmiPsU7v0uKkD0AHda1RVVNdN2AaT+SVAZKhbeqNkT4A0RNCr4/fm9pr5vtFffWQoSyCEbStRqVc7fVGY3lzvYH0AWhrjk7AK400/lfQkaSKm0YaR4Vnv3qiRzA+Hv/UiR7BaYVTgvhp6lFKMY8TXzVZSFZKoEkxapJVzFpCnTRGHF7U++cIbYzaHJ77l8eKV0tVrVSybidRREa2GI+EjGShBjqxPs3tyaPjttpms6iL1puPNbnObnE+bKMrgkcafaKLpc0iTjPZBVMeI5bTnjQexcLvcLx4wGQoFvbm8Ugkh5BZ9T0eJEBOOlPJsXdjLbJFY++if9vHiGdTEqrHCg8z2BzhEFI9vrFC8ca4lMZ9E2ysYvWS2xirTUO9lU3y7TsRG4uTZBlPOF6d1QVJ3keSzGNKtrG6v49BzGUaaaSRRhpJkFMT3DshOBXG+D+EU4L4DYvI+EaANHWqZb0tUe2z0DrdgDRvWcrjUiqWoJTEFTklZzaOedcZ+84uw12bEGenOMiaF1cWzSxehC3TnG4if/7tsb8rFn0YK1pSPPPtyKNCJoWVFyFbxLNNm//hiR4OAHNmvddAOkcHzfRpb4uPp+gsMjOMY5479e1jCteMhzPK3ky2M+5yWJw5jTmF0TiHoowyzi6Kp7OwSw7eVGmtzPqWsstjyp4AZ3jnMD/bqLz6nupLDGRQRuJDU6PxlJIkMS+rzLLtD049L/b3RUW1VGbE3eRKXVlcWmxU2Xxn9XxTG5mKnavLjeNZkldsyFOZbXNwTXlq6oZL8/KYlR2P18ux27m6whhrmuOwc3VF/N5XJImbqytT6geiqp43VMdjtmTglqlGd9FzSzKpyjRPaFw7JZsse/Tcv3WqC2fS7TIlU2ZJYXy/GXkysyxSLlw7I24zpVCmqsD8bGQ4YHbFxCc9JElizgLzhII7EyqrEu4XWSIvKc2C3QU5CXGHpQtsJD9CFcuN58PhVVCSwjAlO2RUJaiDnmPcR/aAM0kdVC5QUOYl2NnAttL4O2A/K8dEBm3nm0UklCX54E6YcCpzI9fG7yvbmRUmgmY/zxj7KjltKEurEyrAttJ4P9sW10Z9cRPrVhmVjdNI43TFtELr+Ns00pgULvvm+DYnGlf//ESP4LTCKRPjt2HDBoOi52GYxF1efRVeXRMtZGRgu/EGlBIjSQk9/RBse320JCFdeA2ORWcyGQgtjNrwIiI4hG3a+chuK7EDnWDzmqi4S9XZ2LKNQgZCV+nafC/DzS9iz8gnf8G78JQa3XeDw4do3vBDwoEePPnzyKu+iOxiYw5ATQuxe+2X6O98Hbszl5nL7yan0JxCYDyEwkO8vvErDI8cpKhwObNnvBN3RrHBRtWC7Gi4n76h/dRVXEllsTnXXioIRIbY3vU8NtnB3KILDMqdutDZ3LuGrmAri/PPpjhjbCGInlA/q3tfJ9eezar8pdgsVif7QsPc2/g0EaHyrikXU55hvGa/bXiJB1rWownBzKwS7px+GVM9BQYbnxpmdXcDAsH5hdPItJlnrLb0d/KHg1voDQdYmlvKe6YtsrQL6xovdbUyrEY4r6icXEfqCqlhXefFzk58qsqq4mJyHeZ+hBCs7xugyedneX4uVZlmAZiJYmPvCAeGQyzNz6Qmyzxev6rzUoePzqCKAszMcbGkwJheYySi86vdfg4MqZxf6uC66gwcSatTqi7Y0K5zoF/HaYOFxQq1ubLJZschjW3NKkN+wdQimYvmOVKK7zuM7k6NA/tUAn4oKZOpm2nDZje307gtQutejZwSiVkrHSaV0PCIoH1LBDUYFXfJKjWTUCEEnU+F8R3UyaiUKbnMgZw05vBBjcAGFSVfIvMcuym+D6IKm/reCGJAR55pR84196UPqqhrBiCkoyzNRim3vseET0XbPYDkVJBneWPxfbF2BoKo61ogoqMsKUMptRYi0hp7EV1DyDUFyIVZpu3CH0JduxvhC6IsnY6SkMMvHeOXGtIxfhPH/C8/xtBJ7El57cISfvw269y+aaQxafQegPtuhL6DUbcSuxOwgySiKpyxxRUZOOxhJ42WR8MLJAVkO2hhQERX6fRI3F52gtCiM6FTzwd/H7Ssj6qEIkb/SeAphpwp0LUr+vdb/wLF5hzUaYyNo31HnlrEb8tWeOr1WP2Y6RzWrIGmZpgzB+d865nk0FMPw96tUD0T51UTFz+ZDPRgVLZWto/9oa2FhlBDgzg8pWO6dupaCF//PlyeCuwua9nnSHiEod4d2J05eLzTLFNDaFoQVQ3gdB5ZOnpkpIWIHiA7swpFsY6zDEdGAHDYx1aiHA+60Oj1t+ALD1KUOQW3w2tp51dHGAj1UpRRbknoJoru0BAD4WFKM/LwJOX6g+gH+as9+8m2ZTAnpxxljJXMiK4xFAmR75w8gQIIaCpdAT+l7kwcR3DNHQiHGIqEqco0f0gD+CIR9o+MMDM7G9dRpGoIqBoRIci2H53ory4EfSENIQS5TptlOgZVFzSPaJRnKjiP4LfZH9CJ6FCUOca10AQDvmgqh5xMCcWiL00ThMLgHicXnq4LBgcE2V4J5QhjGu7VcWWB3WGhtCkEw+06sk1HcShk5Iy9Gh4e0JEUsGdZt6N2CJQCkO3H30FDHwwBErL3xLnepIlfakgTv4lDVTXe/NPn2dsdpjADegOQaYOIDk4bBMLgyYBAEOx2qMrPpGXAh0I0/FXWYEiNfgrbAI8DNAEZdgkdgaaDGoZhHTKlUfd2G3jddgYDUZVf5Oi3t6aBww55Hjud/RGmFrp55OOrkI9TaEoapzlaN0VTK6h+KFkInVuj/+/dB/UvQdUymHoOtGyMEsK+g2D3QGZBNDVD514IDkSD2isWgb8fas6B/maI+MDXDT37oXIZuHOj221OyC6Hlk0w3Ar9h6B8EUw5C7p2Q94UiASgYknKYUmnM04b4jcRVc/wgQOIh/9p2i6/773YvVEyEWpugActxFLOuxrnkpXHZsCjEFqEvtVfJdDwHCgOshfeSvZiY3Jyoau0vvgFhpujYiaS4qL8vG+SVWEcS/vO/6N1azyVk6dwIdMv/IUh3m7Xui/R3fy0Yb+6Mz5L2bS4+2lT/T/Yu/NXaKqfwuIzWbj8m9jsRteSYKiPZ1bfSjA4qgApySye/zmmVl8VH7cQrNv5Q/Y0Rc/3jKprOHPuZ1LONdY0sI0/bP4YYc0fq5tdcC7vWPh9g909e77B6o5HAbDLDj4y6+ssKzwvpb40ofP+zb9ix3BzrO7a0hV8pu7a2LgfbdvGt/c9EdsuAd+ecx3nFhpdOZ/vOsD39r7IkBpiTnYx35l72aQI4K/qt3F/014EYJMk7px5BleW1RhsdCG4a+vrrOnpAiDbZufXS1cyJYEAfnfXLoOgy01TpvDB6ebE2ePhzw1t/KWhjYguOK84ly/Mm4pjEh8i+wZDfGFjJ12h6Gyh1y5z98Iiw6rfM60hvrt1BFVE5xXfNzODt04znkMhBF9+OUR9f/R3qtgt8d3zHTgSVqI2NkR4ZJOKPvpT5lDgppUOpiW4X+5vUnlxfYRQGEoKZC4/x2FJABvrVV57NYIQ0XC1hUttzJhtnDwZ6tF4/dEw2ugkaeVshdlnx4nScIfKroeNAi8OD8x7uxNbgn+r6hc03xdCHRWncRZLVL7NiTy6qheqVxl6IBL9ypTAfaGNzJWTz815JOi6TuTXexE90eUQqdgVVfR8A3IHJiNN/FJDmvhNDB/4ywae2Nl5oocxLs6ry+dPd6w40cNI438Fg63w88UwKgR4UkKS4W33w4zLT/RITgmcFqqeE4UV6QPQ//DHeMGK9AGs/s8xH49v7yMEGp4FBGghhjb+lnCPUb1u8MDjMdIHILQgbS9/BaHF4xojwQFat/7asN9I9xZ6GuLy1KFAr4n0AdRv/iFiNDl6wNfOrq0/QlOjJKu7cy0H6/9m2mfT1u/HSB9EXVU3bv0OofBgrO5Q16vsbvwHQmgIobGn6WEOdb48kdNiwAPbv2ggfQC7el5if+9rsfLWvnUx0gcQ0cP8as9XCGup+ew83LrGQPoA/tW+jrV98WvyvX1PGbYL4Ku7HzXU+dUI39rzAkNqtP+dQ53ce/A1UsW+4X7uGyV9AKoQfG/PRoYjRrnH1Z1tMdIHMKRG+PrOeKqI9kDApOJ5f1MTLX7jeR0P+4f8/L6+lbAuEMALnf38t6V73P2s8IMdPTHSBzAY0fnOtm600YmmkCb4/raRmLKnDvxmT4CBkFHI6akGNUb6ADr9gj/viKtY+kLCQPoAwhr847Uw+mhf4Yjg+deipA+go0fnte3muGFNFby+Jkr6AISALetVwiHj5NjW5yIkPJ4c2qXhH4wf677HzKqe4RE4uNrYZ9fz4RjpAwh1Cvo3xI9t+F+RmJcNAvzPqQjt+EzUac+1x0gfgOgMor508n8kp5HGRHEqkD6A1futlaXTSGNSuO/Gk5v0AQgdHnoXnAILUf8LOCWI39yc1HONGRCZmDjMsUYkMdXDGHXBfrONHh5GDfbFyqHhQ5hTLIA/gbAM91mnoxC6SiQclWQfGT5I3H87ipFBc/+DQ/tNdaAxMhKXbu8frjdZ9FnUHQmqHmEgZP0ybhrYFvu7ecTcblAL0B/uSam/bYONlvUHfB2xvzXMCrIBPUJIi3+QtweH8GvGe+rASF/ybuPiwMigqU4VgtaAz1C3Z8hsd8gft9nWb52ipGFkJKXxNIyYiWLDSCClNmL7DSfnKoDukMZwJHp+e0N6YuYAIHpntviM6Qr29pmvR9NgvK53RDeQvsPwhSA4OoShEYGalKmhb8C8UyAg0JO6EwJGho22QZ9538GEFA9jvWMDvcb9wl3mdoLtCekUkk+9AG3gKBWOx4Dear72otVnYZlGGmmkkcYpg4Hm8W1OBkT8EE6/c94InBLEb8fABFcdxopryk2IZZuk8uRkkJikHQDZjrNsqaHKU24WlXFkVWLPjIupuPNmIMlmF6/cilWxv/NKrF1DbPYsHK6ocEJO/nxsNqNbZ0GJuf+y0lWmOpvNQ4437jpYXrgCo9KoREVhagI5NtlOVfZcy23ziuMJbBfkmY+twFlCkctagXMsXF5iHTS/PC+utJlpkRajxJmNU4m71FZn5lLqMsbZrcivSmksAGfkFplSI2TZ7NQmJW8/t9isRLskNz4Zck5RkUnzVQYWJt73E8DivGwcSbFxywsmnkjesF+h2e11htdBjiP6jJZmyOQ4jH05FajzGuMKz6syxxkuL4s/52U5Mi6LUMQSL7id0fbzvBIet7GvqlLz70CmR8KZFMpqs4E317ivtzA5NwMUJih/ZuRau0fmTjXu56kzjyFrZrwdJS+pHTvY8o9PHIQyz3yvyAvMQlVppJFGGmmcQqg550SPYGLILgfn5LUi0pg4Tgnid0Rcd0HsT9uHPmjeLkk43h2Pq7N/9OuWzSjv+/wxH1rGlHPIWflpbLnTcBTPo+CS72PzFBlsPOUrKF7+aRSnF0l24CqYQ+VFPzLYyIqDGRf8AmVU9ESS7ZTNfz/eshVGm2VfMRBEu7OABefH4wLtdg9Lzv4JeYWLycyqZvrcD1Ix5c2mcc+b9QEqyi4cTesg4XaXcd7KX6EkkKIC70zOW/x18r0zyffOYNWir1KQMyvlc3TLgu8xxbsglgPQJjm5euadFHvicW5Vnlo+MuvreO152CQ71Z7pfH7Bz1OOP1qZP4vbqy7AIdmQgCxbBt+YdTPTPXEC+fszbsOdkFOmwJHJLxcaxX8USeb786/gzLwqKjO83Fy1kNunLE752Itcbr63YCWFzgzskswUdxY/X3yeKQffXG8uH6ubg8dmwy7JLMsr5AtzFsa2u202vjpvHq7R/dyKwg8WLSLbnlo8WKHLwbcX1TE3x0ONJ4OPz6zinKLUyONh3DmvgAtLM8m0SWQoEmcWZvC1RfF7X5Ikfroimwq3jE2CYpfMD5dlmwReFhQrXFOn4FTALsO5lTJvrosfl02ReOd5TvI90WkISYKqfImbz44zOFmWeNN5DqpKZbxZEotn21g8xyIXpSRx/mUOPNnRdtyZcP6lDpPAy6JL7XiLpKg4mgsWXGjHlkBiZ1/vxJmd2DDk1clUrjBOKuSvtJM1S0ayRVM55C5VyJ4dH5f3dgdKYTQvnpwFOe84foIrtjMKoukcbBLYZZQVhdjmTO7ap5HGyYj73738RA9hQvjLO9PhrWkcQ7zl/6DEnF7qpEJ2ObzrqfHt0jgmOGXEXdLB62mkkUYa//tIi7ukhvT7MY000kjj9MHRviOPTq/9DUToB7+NCx0kIDGlgxCC8L2/hcGEmKj8fJx3vCtW1HWNyI8+Z2zElYnzw182ta13N6JtehyEQFl4KXJJrclG6ztIeMsDoIWwz70WW+kCk01ksJmR7X9DD/vInHk1rjKjy2Ggdw/9u/8BQO6sG8nIn2lqI+zvZt/zHyU43IwkOyibdwels28x2PgGG9jw9G0gosFNkuxg+ZX/wplRYGpvPPT27WTz9u8TDPVRXrKK+XM+YljxA2jv3cS6HT8krI5QV3Eli2e8N+V+ALpHGnlo99cZCHYyI38lV8/8DEqCWqmmq/y5/sds6HmJXGcB75vxBao85msxoeMKD3PfodV0hga5qHAB5xca032EdZWf17/AM127EEKwqnA6H629EI/NOp3FkfB4Wz2/OrCRgKayMKeYb807z+AyCtF79h+H6vlXazTW8rryadxQWZvyaub+4WH+0dyMEILrKiuZ5TW7aKq6zm8PNPJ8Rw9ZNhsfnF7Dknzzqs5fGtp4pKUbt6LwiVlVLMzLNmzvCIR54GAvA2GVy8pzWGGRpw2iyp4PN0XjS6+fks10r/kc7h+M8Pn1w/SGBJl2ibsXeVhamPrK1v52jf9sDOMPQ0mOxFuWO8gZI/XD0UBTBa//J8TQaLyeOweWXunClWm8Xr5unT2PhFCDYHPBzKscZBYa3TSFJujfqBJo08kol8ldbENKWl0MH9QIbtaQHJBxpg2bRUL7CY17jw9t2whkKdhX5iBlm3/6tYPDaJv7kBwyyplFyPnW97x2sB/16QZESMO2sBjbuVMs7dJI42RCMBRh5pfNAmgnG3Z++SIyM1J/36SRxpg4tAEeuAl8nYAEjsyo4pglFKIR9xJ4K6B4Lgw0RdM+aMl6GYffVwKQo+kbhIjm9xOjctSJ+hSKK5oqQgCKA2QbTL8Urvk1pNOYvGE4ZVb8JpLOIfSb38DgkNmgthbndddGbX5wp3UjuYU47/hMrCiGewj/6RMQGVW6U+zY3/F95Ly4W6Du72PkvrdCaDhaIdvIvPEPKIXxWDg9PELH329ED44KcEgyhW++B2dxdOk9PNxGwyM3IUYVISTFydSr7sORXWEY3uZ/XIQWMT6oFYs+Rsmst0f70cK8/LCVL7fMqrestT7mMTDia+XJ525EiDjTLi87n7OWfidWHva38dDz1yMSxFDm197GkpkW7rZHQFgL8I0XLyWixxUFZxWcy60J6Rx+svPzrOt+Lla2SXbuOetxPHYjIRkPutC5ecOPaPTHFTK/NusmLi5aGCt/Yee/eKF7n2G/+dnl3LPYSLLHw3Odjdy980VDXZ0njz8tM7rW/vngbu5t2GGoe9+0udxaPXG32c5gkFvWrCGgRa+XQ5b504oVVGUa4zm/u3Mf/22Li+lIwG+WLWSWN07c7j/Yzj37Www2/zx3AfmuKBkLaTo3vbyf7qAa2/79JVNYVmD0zW/zR7j95VZCo8orTlniT+eUU+aOu2l2BTTe9vyASU7nkYtzybbIjTcWeoY1fvqkUUzGaYPPXuXCfoQ8fJPBK/8I4us3/mbanHDBO1xIo/GRmqqz4R6z4uzSD7iQE8bT+XSYwW3xZ8y7QKH44jjpjRzSGPhjOPbelNyQ91EXsjO1Y9J2+wg/kHDd82w4P1xpIJn6IR/hP+6Pv6PdCs6PzEZyGcmq3hcg/KsNxnf5OZXYz6tOaUxHQnrFLzWkV/wmhuq7Hhvf6CRB43euPNFDSON/Bf4++N5UrAQCTxpMuxDeYa3Kn4YZp0U6h6KJrrZYkT6A+gmoTfYbBWS0/a/HSR+AFkHfZyRQauMrcdIHoKtE9j9jsAkeWhsnfQBCx18fn3UcbnohRvoAhBZiqOl5YxtDzSbSB9BdH39Q+jrWjXFgOuHE/ieA1rbnDaQPoK39RRInCfY1P2IgfQD7D6X+Yq3vfd1A+gD29r5qKG/oeclQVkWETT2vpNzX7uEWA+kDeLJzk6H8YrdZ0XTbUCvdidd5Ani0bZ+pbv9IH5ownrPH2g+a7B5va0yprxe7umKkDyCs6zzfaVZLfabDeOwCeKbdWPdoa7fJ5uFD8ba29PlipO/w9qfbBsxj6vDFSB9ASBes7jAqdr3SEbbQUIW/HUhNSXTtfrMrQEiFg13HVgFTU4WJ9AGoIRhI6Ktnj3W/PXuN0qJDO43jHtplLAe3a4Z3tfBD2OJYx4O61Xjvij4V/ZBRelTb3m/8LvBr6PXm31Ntc4fp+0HbcmrI5KeRRhppnHbYfB8nNekDaHxpfJs0jhlOCeLXpaaWr82ESSwhS5k549ZJ7nyzTVKdYmGjZMTV8mwZZuU8m9vommlzWCsr2jPibTvdxZY2ADZ7aonFXS7zmG22TIP7ocddYrJxjjHOI8HjNPflVIwrVW6bWekp15V6io88R1ZMRCaxLhGZFpMMdkkhU0nN9abAIpm7TZJQklRl8x0ZJrt8pyulvvIdZtfIgmR5SsBrIfZyeCXvMHLsZhfAcnd8PHlO8/Z8i7o8p1l9Mrkuz2X9XE7xpKZcmZtpvQKWZZGg/Wggy2CSTx2FM0E11DXGY+D0Go9XSRq3Lakse8ydyVmpH5PksRCySTrH1jbm+0WycNeV3McnqXwaaaSRRhpHidxTwBU/xW/UNI4OpwTxmyik5daqXfL118cLJZXW+15wtXGf2mVIVfH4L6lsBvLMsw02tqoV2KpXxvcpnIFjttGVz1m6mIypF8b3yZ1K5uz4eLKqL8RdvChWdhcvIrv6QkMbNpeXnPJzk0asUHXGJ+Pt5M7A4TanN3BnT0dOkbRUlF1Idta0hBqJRfM+Y7CpLb+CLHd53EJSWDnvsyn1A1DlnUtNzqKEGok3zfiEweb22k8ZCFtt1mzm5qS+yl3qyuXmyniqikKHl1urzjfYfKruouTdeN/Uc3HbUos7e2fNAlyy8WP69mpz/OcHaufhSJiYcMoyH6hNTYHr3KIizsiLTyDM83q5uMRMzD8xc5qBtxS7nFxVbkwV8enZ1dgSCH5ZhpPLy+ITEXXZGVxZkRMrl7sd3DjFTN7PL/GwMC9OGBfkuji/xEjozy52MCUpDs9rl7isMjXiu7zWhidpl1nlEqU5x/bnTZIl6paYSWlZnYw7O96Xt9KGM4n8Ob3gLTfuW3ieHWm0SrJFy4nIWGKLqnoebmOOgmNK6ukcbGd7kRLSZCjLs5ELjPezsqQAqTB+EuU5OcjV5gkXZWEJ5CT8nsgStismF2+bRhpvJPLdp4akgfN/6qssjROOmW+CvLoTPYoj46KvnegRnFY4ZWL8NmzYQOi7vzVtSxR3AVD7+tAe/icMDEBWFrbbb0NxGb8KQwf3wcO/ixZsduT3fBZ7pnW8mN5eD0JDKp0+puCG1rUHoQZRSucjjZEnMNy7DxEewVG8AEk2f7wFuqNxXhmF1nntAIa7t9G55+9k5E6nZOZbUGzm1aKOxqdp2PIjhBDULf0iRRWTz+HS3rmW4eFGqiovxeW0zunV1L6akUA7dZVX4bBnWtpMBAf6NtAyuItFpVeQ7TKL0QyG+3ip43GmeKYzP2/ZpPsBaPJ30RkaZKG3Bods/hjoC43waMc2BHBp8RxKx1rCGQdhXeOJtnoO+ge5vnwmlWPcYz41wkvdbUjAOYVlZNomt4Kyc3AQXQjmer1j3qsD4QjPdXRR5HKysjAf2cIupGn851A3xRkOVhVbX/eG4SADYY35uW5s8tirUDv7oy6Fc3LHJnPrOkM80hxiRZGNq6ZMbuZPCMG2Zo1DvRqLqm2U5x2ffHcA/iGNHS+GEcCss+xk51t/UPbsj9CzR6NwpkJ+nfU1VX2CUJeOq1hGcZvPo9AFkWYd2SVhK5n8F6FQBXpzEClLQR5DPEfoAtHsA5eMXDL2dRBCoO3uRQyHsC0qQXIc23OdjvFLDekYv4njvjUH+MIje070MMbEpy6cxkcuNou7pZHGUWP347Dul+DOgznXw97/woHV4C6GUB8EBqF0Psy4DFo3gcMNc6+HjFwIjUDjy3DwFRjpgswCyJsaFWgJ9EN4GApnQFYpaEEIDEFvPXgKAQma10YFZS78Gux7LOoW4ymM2i26Bbyp5WQ+3XHaqHpawuJ7QwggEIj+YbMhWbi3Sdk5CMUeVShyZoA6dtyMXDr+bLbkKUL0HoCwf8wElI786Zb1h+EqmIOvdS39e/9Jds0lKA5zO0JTcbiLyCqYZ0n6AOwOD57c2cg2Fx5vjaXNRODzt6HrYbI8VaP5/KxRWriMjXvuoaHtaWZOuXZSfbUO7eNA/0ZKPNNwjUEevY48VhZfwqaeV9nZv5HZOYtTVr4EGIz46QwNMsNTZkn6ALLtGYR1DYdko8hprVg5EThkhavKp/NSdzNbBjsocmXiVJKUHYXgwMgAqq6zILdgTNIX0jR2DvZTluGmJMP6o3yOhZJnMnIcdq6vKj+ijVNReEu1ecUwEW6bzEBYQxMC2xj+j+3+CCFdMCdn7BXnFp9GZ0BnYZ6NFUWTV7Lr9wn6RnSKvDKF2WMTJCEEnT06drtE/hgrgvV7IwwPCuYutGG3EJlxZyvULnEw3CdwZFi3EQkIbA6J7HIZ2Tb2fWrLlLDVjP18SbKEo/roiZVkk1CmWv9mJPYlHLKlerLBTpKwzT6yUrDe54PhIFJFLpJyhOsxEkDvGUIuzUNypl1G0zi+OLOuEKe8h9CxDf89ZijOTs3bIY00JoxZV0BuJWx9EJrXQMVyGGiNkrfCURLn9ICuwXX3RpPU7nkcdv8XQkOQXwdFs6Kuo5IU1cBQFFj41ug+ja9C9x7IqQKhQslcmHoutG0DoUf1MDb/CarOhMplsPq7oAbBnQ9L3plW9XwDccqs+E1I1fOZZ2DzFtN22+23oxRFY8JCjz8AuzaZbOSzLsZ+1sUpjy2y9ykCz30jKl9rd+O+8nvYKlIj4roapOHRdxAZOhStkGQqL/wxnvKo66oQOrufugN/3+7YPu68Wcy69PeGFcbXn3gbgWGjWEjlzNuZOv8DKY1n974/sWP3PRwOCJYkO2cu/SblpasMdi3dr/H0ax+NlR32bG651ChuMx4e3PlVNrc/HivbZRfvOePXVHpnG+yeanmIP9bHlT4rM6fx9cW/x6Uc+WM2EWt6d/OFXX8lqEdwyDa+NusmVhUYV1gP+fp4+/rfoY8eu02S+eeKD1AwBqE/EkbUMDev+w89YT8ADknmd0vfxDRPNIVCQFP54IYX2DcyENvn+opaPjljkaGdhpFhPr5pLX3hEDLwvtpZ3Fx94tzr7m/o4d59nehAnsPGj5ZOYWqW8YPlLwcG+MO+/qiNU+HHy0qo9hhXmn61y8eDB40iIx+a5ebGcQhKMp7dEeHF3XHhFEWCd1/gpCLP+CIJhQX/fi5Ez6hAS22VwiUr7bEJBF0X/OtvQSIJitXnXminrDI+QaDrgtcfCTHYFf/dnLvKTvmMuE3vfpUDz0RI1PFx5UgsuOXk/agTmk7k/gb0hqiIlFztwX7zVCRb6i/jyLO70V5rBEDKycBxy3Ikr/maatsbiTy+AXQdnHYcN5yNXFWYXvFLEekVv4nhroe28sCGlvENTzByXApbvnLZiR5GGv9L0DX4282w/4mJ2UsyeIphuP34jusw7JnwyZ3R1cU0xsVpoeo5YViQPgD1b3+LFyxIH4C+JjXCAlFCFnz1p1HSBxDxE3z15ym3M1D/WJz0AQidjnXfjRUH29YZSB+Av283Q+1xJc+e1pdMpA/g0J7/Q4iJT2+GQv3s3PNbElWghIiwZcePTbYvbf6KoRyODLH9wP0T7ssXHjSQPoCIHuTpA782tqsFua/hp4a6Q74DvNRh3Hc8/PTAfwmOXquwrvLTA4+abL68+5EY6QNQhc4396TWz2E8eGhXjPQBhIXOD/fGr9njbY0G0gfwcEs9jT6jmuIfGvbSF44KHOnA7w7sZShiTF/wRmEorPL7/V0xNc6+sMof641KoAMhjT/t74/bhDT+XD9gsGnxaSbSB/DbvX5C2sQno/whYSB9AJqAxzabz8/OejVG+gDqmzVaO+PPxs5tEQPpA3jtVWNFd7NuIH0Au9dEEKMKpkIIml4xkj6A4IAwqXqeTNB3DcZIH4DeOIK+cyD1dvp8MdIHIAYCqGsbTHZC14k8tyVK+gBCESIvbEu5vzTSmChOBdIHMBBMXbk3jTSOiPpnJ076ILpC90aRPoCID1783hvX32mOU4L4lTqOUvEnfJw+krUIIjBgqBK+npSbUX1mOXQ1GG83EugybQcIB+J9BYabx2hdR+gT/+AMhfoRwmwfDJqPS1X9prr+IXM6hLHgjwxY1g+FjETCr/kI6+Zr2B/uNtUdCT3hQWM5ZJar7wubj6nTwm4iaAuYU3D0huOpCnrC1mkLekKBpLKRIEWEzsDxuqfHwWBEI5LkJdATNJKjgbCGmsTdeoLGe6o3aD0ZEdYhmALx84WtbYfNnBJfwGybWDc0YJGqIYkIhnxmGy0S5y8IiJhvIQACFu2fLBDDyYl5QQyZ68aFxYkXIxaqzKoGgXCSXWppPNJII4000pgA3kgSN1n0HjjRIzhtcEoQv3aLj3FLWMjaA7AowXVuLOGMrNQFPCSbE9s0oyqkffqlKbeTPfUSknXivTWXxP7OKT8HkuPsJIWcsriiaOnUa0xtALjcZcjKxBUps7OnkuOdYaqvqjAfV2VxstIonDHrQxPuqzBzCm57jql+YYnRzSXHkc9M70JDnYzMmYVmBc4j4dKixYbyJcWLTDY3VCw21d1WdWZK/RzGdRXm83hVWVxd64KiStMDWOjMYEGOMVXFxSXGmLxZ2TlUZabuenosUJnpZGaS297FZcZnpzrLQV22I8nGON45uTZKLOLjZuUoeFNI3l6YJZNvkfZgsUVcXN0UG4lhoU4HTCmL281dZI75LKs0jqWoWiFZvym/XEYZjeOTZIn8OouYPAlK5h8/wZmjhTzLC4mxiDYJeXZOyu1IFblIOcb7Q5lrDtyXHHbk6cb7WplTlXJ/aaQxUXjsp8TnThppHHtMv/zkT5lw9ifGt0njmOCUj/FLVPUUuk74pz/D4K9VVIjz9tuNNj/5fMIUPeBy4/jQlyclFiIiQcKb/4rWtRulYgmO+TcijSEaciSMtK2na/1P0MLDZFVfSPEZHzK0M9K7m4Nr7ibs68SRWczUlV8nM8+o/jXQvYVda+4iEoombM/01rHwgntTzuMXDPWxZ9+f6Oh6DVm2U1l2IdNrb0axIJDPb/gch7peQZGdrJh7J7UVl1i0ODYGg53ct+3zdIzU47J5OK/6Ns6svNF0LXyRYf5y4Kds73+NbHset9Z+nFk5ZuJ2JER0lQdaXmbrYCNzs6u4qXKVpcDLz/Y/z7/btyBJcHPlMt5VfbZFaxPD6q4m7jmwibCucVVZHbfXGFM6bOnv5jcHttMZ9DPHm8+HaudTkmEWuHm87RAvdbVT4c7k5upach2TF0I5WgyEVe5r6KHFH+acoiyuqDD75feHNO5vGKDVr3JuiZvLys0iOZ0Bjd/s9rG+RwUBywrtfHJeJpkpfqD5QoJ/rQ/R0CWwKXBmnY3zZtksn+eWDo2d9Rp2GyycZSMvKbfewXqVTa9H0DQoq5A5+3zzeR7s0tj1SoSQX5BfITNrpQObPd6XrgraNqn07NWIBAR2N9SscuCtPHmJH4De5kd9rRsE2JYVIFdMTqVXDEbdO8VICGVuGcpMa6EgEY6grtuL6OxHri5GOaMWSZbTMX4pIh3jNzFoms7MLz5B5CT/5NnypYvIyTxxv+9p/I+iYwc89ilo3Rh15RQCSPa8kcDmgmXvgZpV8PinYfBQ9HtZkqL7GZLBS+DMBlmB4MBom1LURraDMzMqeqiF4/vZMqJ9BKPfqdjdcNl34Yxbj+/x/w/haN+RpwzxS7/Y0kgjjTT+95Emfqkh/X5MI4000jh9cNqkc7DK4QfArW/CWRpNQi2EIPzb30Vz+B2Gx4Pj/e9DGpWKDY8MIe75hqkZ+YN3Y3en5j4ndBXfIx9Hb9kIkoRStYLMN//IYBPpO8Dg679CHW4jY+oFZC96lymP3/ChV2hf8220YD+SbMNTuZKSFXdic8VXUroP/JeWTT9Gi/iRbS5KZt9G2dzbjX2FBtj8/Huj8X6STEn1m5mx9HMpHRPAoZZn2LD126iqDwC7PYvzz74Xb/bUlNsaD0F1hCf2/5yD/ZupyJ7NFdM/isdhzB3XF+riV7u/yq6BzQgEFe4aPr/gZ+Q6jywpb4VhNcAvGx5j88BB5mRX8ZGpV5JrkTrjSBiKhPjx/pd5pacJgLPyq/jk9HPw2o2qjYORIL+s38j2wS7me4v4UO0Ssu3HbyZ3//Awv9m/n85gkAtLSri1psYyT994aPUH+dW+QzT5gqwszOGO2nJDkvmn2wZ4qLEXRZa4ZWohK4usU150BlR+vaePA8NhlhZk8N4ZubgSpP01IfjdHj+PNodQhWBJgZ0753vITsHVE6CpR+OPq8McDg2UgI9e6qAgO7UVts52lZeeja72AcyaL7NgsfF6hYM6rzwYInI4lE0aVfWcnqD8qQl2PhTC3x0dkDMH5r/dhawYr4XqE3S/GCHYoeOukClYZUdxpn699AEd9Uk/eoeGXGvHfkkGkiP1dt5ICH8I9YWt6C29yBUF2C6Yj5SRXuVI4/jh1fpubv7d6yd6GOPi3x9cwcKq/BM9jDT+l7DvGXjgJtDD0bChK38MwT5Y/3sIDkJmIShO6N41sfZsbvAUwGALJiUzyQaKHdSkmG1H1qgQohT9/2HtCVcunHcXrHj/UR9mGhPDKbPiN5F0DuEnn0Jss1CGKyvDecvNAIR+cOfY7Xw6NVWhwAvfJbLzX4Y6+xm3kXFmNH2C0FU6HrgWzRcXIfEu+zBZC26JlSO+LuofuobkJffM8hVUXfSTaD+DB9n52NtN/Vev+CIFU98UK69/8u34h4wKenWL76Ss9vqJH1Ogi/8+fRXG5XxQlAyue9PqCbczUTyw4262djwVK9fmLeOOxUZl1C9tejf7h7Yb6kozqvjx8n+k3N+Xdt3Hs91bY+UVuTP48fw7UmrjCzue4oVu43k+u6Ca78273FD32W3P80pPXK11VWEV35pnjAk9VgjrOje8/DJ9CaIvH50xg7dUpRY3JYTg1jU7aPLFRTpurinhfXWVAGzr9/HhBNVGRYI/raxlisf80f7eNa3sHYyP59op2Xx8dvyD5oEDAe7ZY4zfXVlk55tLrRPdWyGsCr7+L7OgiCTB126YeFoIXRf84y9Bkn8OL7jMQVFJnECuvi9AyGfef9XNTlyZUcJa/3SI3n3G59lTCnOuN46n5aEQ/sa4XdYshdIrJx6PexjBXw0hWuNKgMpyJ46rTu54jvBDr6Dvb4uV5RnlOK6LxiynV/xSQ3rFb2KovuuxEz2ECaPxO1ee6CGk8b8CLQJfLyT5m+6kw/W/h3k3nOhRnBI4LdI5eMYSZEmC2L3bekNHxzEcTRyRhtWmOnVfPC1EpHe/gfQBBA69aij72tdj9rMGX+trCD36MTfQ8pJl/4Ota2J/CyFMpA+gs/kpU92R0Nb5ClY/EJoWIBKx+OI9SuztWWMo1/e9jpagQuqLDJtIH0B7oBk1BbXSw1jTt8dQfq1/H1oK6S4A1vSaFVTXWta1HLF8LLF3aMhA+gDWdqemegrQHggZSF+0nbga6mvdRqVSTcDrPWb10v6QZiB9AOu6/EllszLpuu7UlCQP9VpfOyEgkoI6aF+PbiJ9AA37jdLqVqQPoK0+btd/0DymkSThXqEJA+kD8DWkLuMufLqB9AHo+yahxvkGQ69vP2I5jTSOJTT9JP/oTSON44WOHZz0pA9g/9MnegSnDU4J4jeSrKk+FvLHcI9wH5/ZbyW32lQn50+L/W3LKosunyfAnmt0l3TmWLtPOrKrYi6hGbnTLW1c3prY35IkYXOYV0qycmaa6o6EXO9Y9jI227E/j8WZNYZygbsKJUFwJcOWSZ6jMHk33LYsbJMQ0alxFxvKVe5ClGSZxvHayDSLmdS4Leoyc45YPpaocLuxJ7l11nhSV/7MdzrIshldJGs88ZUqq5W9Gou6LLtMntPYTrXHOIFTnWV2xZziSe1aFGSNbZ9K7vEsr7VrZEGRsZGxbrnckridy6KtZH0lSZGw5xrtHPmT+Dl2SZBlbEcqOrlFZACkwuykcuqqymmkMVEo8snt+pxGGscNedUnegQTQ2Fq36ppTB6nBPGbKBw3WLs02t76lnhh+YXWO69MTY0SIOOSr4E9wX3LmUXGRV+MFWWXl9yzP4Nkj6rjOYrmkb3Y6FaYUTCL3BnGcStOL6UrPx8re0tXkFNxnsEms2AuJbNuMtTNWvENpIS0D86MEqrnvTelY8rLnU1VxWWm+vlzPjIp1dPxcPXMz5CXEZV1z3YWct2szxu2y5LMB2bejVOOx88pko0PzfzypPr7TN21lLmiMYRFTi+fm566a8GdM1aRn5BbMs+RwWdnrLKwO5NiZ/Tal7gy+cyMyaWFmAhyHQ4+MXMmbiV6/Rfk5HBrTc04e5nhVGTunFON1x5lOLVZGbyvriK2/cJSL5eV5SATdfO8YUoeSwrMBNMmS3x2XgG5o/F61R47H55lnJi5rc7N1ATyl22XuHO+dbzgWPC6JS6YY2Zj582SU7pfnU6Z6bOMhCnLC9OmG+sWXmT2PiicIpFbHLeru8JhTPkgwcw3m/crudSObfTU2b0SRRZtjwdJkXBclwmZo+kkCmXsV0zcxfVEwX7ZEsgefYa8buyXnnFiB5TG/zzOqT014ubOq8sb3yiNNCaKjFxYdIuxrmol1CSl40pOGTYeUpwwPyJqL4blY4dzpXFsccrE+G3YsIHQlm3w1Gux+sRUDokI7d0L9fXI06djr6uztvnLT6CzDUqm4Lxl4rnnrKB27gJkbMXWMxZCDaKHhlAyi8ZuIzRMeOgQNmc2dk+JZUqIcLCP0HALzsxSHG7zKhiA0DUGe7bicBXgzp58XqxQaJDBwQNEIsOUlJyFoqT+UTpR6EJnKNRFlqPAsNqXCFVX6fAfIqD5mJo1c0y7ifbXFRqkwJmNLdUfu1gbgvbgEBJQ7Moac9VQEzrdIT9FzsxJCa2kiqCmMRKJUOByjW98BIR1nf5whGKXteDGQFhFkSSy7Ec+fxFd0BfSKM4Y+3p1BDQimqA8U5n0OQqrgh3NIfp8EufNtmNTJvdSCod12g/p5BdJeCxWJCHqVt3ZqKJrgvwyG063dV+DrSp6BHKrxz52oQvUEYEtSzqqiRWhCsSIQPIeXTtvJISuw3AAst2GMadj/FJDOsZv4ghH/p+98w6Po7r+93t2V9Vq7r0bF4wx3fROCIQWAiGhhJCEkOQXAumFFNJIIQVC8k1ChzQIoffeqzvGveDeZdnq0pbz++POamdmZ7W7smRJ9n2fR492Zu7ce2d3dvaee8/5nDjn3PIam3c00hCDKGb2uwDzWkk5xRVghKKSDumFQJ8iqG2BOFAaNroWTQpFzrHGVohEzP6GeJuwPWHnD1c7OG0nnHYGlxfw5vdOJdzBZ5fF0i7NtbDkCdjvI9DHEcar2wyJuEmvUFIF21fA6jeg33ho3GZcXCqGQ7wFKkfCxvlQ0g8GTYKygbBxrjEAQxFoqYdoAwyYCOVDjKBM0y7o09fUVz4I6rea9A/xVti5BgrKoHIYlGUeG1vS2WdUPQGP0QdG6dNv/MXXrIFnn4PmZhILF9EyYwZFJ3hnNlpmvmaMPoDNa2h58TGKTjnHU0bjMRIrZ0JLI6EJRyAl6SsR2tpA67LnSWxfRnjAfmjfkUihN/dVvLmW2tm3obEmyg/5PAXlQ9PqScSaqVl8P6116+g78RMUVoxIL5OIUb9lLvXb36egeAD9Rp9CUVl6YuTqze+yfNYNiAgTDv0eA1xJ3vMhFm9k9bonaGzaRHO0hrGjziLkM7ZaWnexYNW/2Vw9hyH9D+XgiZ8nHMrfQAxJiLAUMHvj4/Qp7MfkAcekGXaRUIQRZdlXsBbWrmBR3QoOqpzMfmVj0o7PqVnJ3WtfoiAU5stjP8qEgPdwed0W7ls/i/6Ffbh89FH0iaQbPyERBheV8Wb1Gt6r2cDxA8bQr9Drz7eusZb3dmxkTJ9KhhTvmYTrxeEwxeHdd/UrDIUyGn0AJeEQr22pJZZQjh9SQZ9IcJsFIclo9LXGE/xtcSMLd8Y4dVgRnxgbXEdClbfWx5m/Jc6UAWGOHxUm4nPdemVRK7NWKQlV6pqjnHNoYZp7V3OLsmq9yeE3bkSYcDjdQCosDDF6fPsDLxGhtDxMzeYEzQ1QFOAB3VKbYNOcOC27EtRtiDPs8EIiPqXN5m1xds6JEyqCfocXEMmQNi9WnSC6MkF4kFAYkJgeQCKCVO2ewacJJbG8Fq2LEp5UiZSnf5e1OUZ8yXYkEiI0eQDSjj9tYk01ia31hMb1J9Q//f6XUAgqO5Yr0GLpCN9/6H2W+GKNE0BLQFl/gEkr0Ooq2OgKrW0BWpLHXCcmDby48+cn4Sq3uS7KV/89i79edkR7l2CxdIziCjjI8RLbOA/WvQcjD4fiSph9t8nDt/+5cITLK239TJh9D0SbjEjMsIOhagS8+muoXgGFZcboO/hSmH0vrH7VhDcVFEPfcTBwkql39DFmRXHhQ7B1IRRXweQzYfhhMOSAPf5W7Ov0mhW/XFQ9Y7PnEH/xxfQCo0dRdNFFALQ89g9Yli4WwsjxFF1k2tBEguj9P0Y3LTPHSispvPgGpCK1ypZo2kX9/ZdDfUo4RsoG0+eiuwmVmHiveEsdm/51lpktAZAQg867i8IBk1L1xJpZ8dD5xJt2tO0bfMQ36TflwrZt1QRLX/x/1G+dm2orVMDEk26mfPAhbfvWLLqL1R/8zXNZY6Z9mdFTPpt+ve1QveMDXnr9StyiM/2q9ueUE+5q265v2sLDr3yKaDz1I1pSNICLTnk0zUDMxpb6Vfxt1pU0x4xIyH79j+RzB9+cVx0A/1r/OLes+gcAgvCDiVdx9pCT247fu+Yl/rr6Gc85v9n/co4fOLVt+8WtS/jRokfbtkvDhTww4yr6+ow6VeVr8x5n9s4NAJRHirjt0PMZVVoFwFvb1/O9BS8Rd75fnx65P1/d7/C8r6kn0hxPcNXbq/iw3tzXg4sLuO3ocVQV5v65x1U57/ka6lzZlKdUhvnrsVVpZX/1VgsLtqXuxbFVwi+OL2pbJbrp6SaqffoyRRH4wXnFbSuIdQ0JHni2hSZHt2Zwf+H804oIdSD2Z92iGIveSI3uphxTwCiXu2njjgQL/u0dSoYK4aDLiikoMe3VLomx+QnXCDEMYy4vorCf15BqWRqn9v7WthFkydERyk7rmtX31vtWkVhaazYKQxResR+hISm3Ua1vpeWOuVBr1kBkcB8KP3dQoPEXfXkp8bccsSkRCj5xMOFJg9PKBWFX/PLDrvjlxmm/f5nl2xqzF+xmRvUt5rXvZghJsVh2l5l3wJPfcO1Irks7HPt1OPV6ePfv8HRmFfxOY/zJcNnD2ctZ2tgnVD3DObouxV9/PfjAGpfiYpDRB7BuZdtLXfN+yugDaNxFfP7znuLRpU95jD4Ard9CdPFTbdt1c+5IGX0AmmDXu95UBbVrXvYYfQDb59/u2a7bMsdj9Jmqomxa9A/PvtUL78LP2oV3pO3LxsIlt+JXGt2xcxHVO1Lv3dK1D3uMPoCmlu2s3fJq3u29te7+NqMPYHn1O6zd9UFedSQ0wd1rH2rbVpQ71zzoOX7HmhfSzvvLh095tv+2ytv/xngrj2z0vvcA83dtajP6AOpiLfxvfer9uXfN+21GH8AD65dQF01XseyNvLalts3oA9jSHOXpDTvzquOlDS0eow9g8a44a+q8Sq3rahMeow/gw53KEkfNs7YxkWb0AbTEYLFL7XLhinib0QewpVpZuyk/NdckK+dE291e83r655xohe2LU9dW/YZPkTYOO2ali1g1vhH1/CY3vRsj0dL5k3WJzU0pow+gNUHsna3eLs7b3Gb0AeiWBhJLq9Pq0pYY8Xc/dO1QYm+uTCtnsexJeoPRB7C2Jj09jcXSabzqT1vm+z15+y/GbfPlX+6Z/qx8CdbN3DNtWYBeYviFyHFWvpNWLzUeoCLq3xdUBswIL1lPLN2BxF93UFvqS1OgiWCDQRP+c9MHsppnqgKAeIb23PsTGa4/Fs/fuImlXQfEA/ZlI+p736Ka2lYITNsQU68DTlTTHXJa4ulpI6KJ9LpaE3HXa+/xhGreaSN6Kq0B0ujRPOXSmzNkLmj1vUXRDG9ZLOH9H1jG1UY8oFzQvlxIxNvfDriFTLmEu0z6+xV4nv/WSxD0Nd99At8gbx81FvAZB52nmt7Hjr7ZFovFYuk84kGOzS4ScZNcPdMYtyvI1idLp9IrDL9ojgPm0KGHBB/o51LJGjY6uExVSvErNOYgpK8r9qugiNA0r+tFwaSPmiBVN0VlFExKJfEuP/iKNKWkisO8MYkVY05GfGkS+k6+0LNdPuQIiiv9aR+EQRO95YaNOwc/Q8Z/PG1fNqZM/Gzavj59RjCw/8Ft2xNHnUNIvC5nBeFSxgw92X9qVmaMOJ+wq67h5ZMZXTU9rzpCEuKCYad79n1yeOqzCEuI84elq2pePtKbUP3SkTM82xEJc97wg/FzSN9hTOiTumcKQ2HOG55yGb1wxBRP+dMGj6WqcPcEV3oKJwyuYGBxyrWxvCDM6cPyk+M/fUQRhb6nz7CSEPtVet1Fx1WFGF3hnfgZWAr7DzAn9ysL0Scg53lY4ICRqe/e/uPCFLiqriwXRg/r2ONv1AHePo72bY88Mt0VU0IwYFKqP32P8LnFCvQ9OP28khneckUHhgmVdL54iwwrRUa4nkMhIXLYAE+Z8PTB4E7RUVlEaFK6UqIUFxCe5o2dDR+e4blrsewh+pX2/DQnAGX+B6PF0pnM+HL7xw/6tBF6OfIre6Q7DDkQRh29Z9qyAL0oxu/dd98l9rs70475xV2iM2eSePmV1I6hQym6zCtl2/LQXbDKley9/xCKrviGp4w21xNf+IoRd5lyHKG+AaIsdVtoXfAA8e0rCPefQOGBFxAqH+LtT81qdr77JzTWTMUhV1I8LN2IiDZWs3XWzUQbNlO13zlUTTgrrUystY7tKx6lbus8Ckr6M2D82ZQNSA+K/fCD21i39B8IwsjJlzNm6ufSyuTC9up5vL/wLzS3VDNsyHFMnfxFCgq8Qgy1Det4b9EtVNcuY0DlZI6e9l1KitLz2eXC5vqVvL/5ecoK+3HosI9RlEnpoh1UlZe3v8vCuhUcUrk/x/Q/JO34wxvf4b4NrxOREF8a+1GOD3gPX9m2lP+un01VQQlfGX8iI0qCr6kh1sqTm5ews7WZ0wZPYGwfrwz3vJrNvFW9gbF9qjht8Fgiob3nB31HS4ynN9QQSygfHV7F4JIA6ytrHXFumFfPmro4hw8s5GsH9KE4QHClJaY8tjzGwu1x9usb5uOTIpQWpMpF4wn+/UYLq7aZxaZhVXDpcUWUFXvf7511CZZ9GKegAKaMi1Bc1HEDauvqODWbE1QNCTE4QHCldkOMD1+OEm2C8iHCmBMLKfLlHKxbHmPn3DihQuh/TITigcED09bVcVqXJ4gMEoqmhZEuykmmrXHi82vQ2ijhqVWe+L4kiZ3NJN7fApEw4emDkCCrG0coZuFGEtvqCI0bSHhM7lL6NsYvP2yMX+4c9+sXWLez564uDCgNM+vH6emULJZOZclTsPZtGDnDKHy+eyu01MLUj8P0T4GTQ5r598Pcf0DzLrM9ZDqMO8EIvuxaB+FCKCqDSWfCgv9C9SoTMhguhNKBUDXKrOaNOAwkAosfg/pNRgBm1FEw4RQjOFOUXxqnfZ3d/Y3sNYZf8oet5Te3mZ0RKPpmcDoHVSUWi1FQkFkEoaWpEVpboaiIouL2816pakaJ9EQiQTweJxQKEc6ipphIJAhlGfy311YuZVSVRCKBiGRtKxvxeDzrNcXjMcLh3ReHjcVjhCTUbp+T92p7709CE4Sy5JfJpZ5cPoeeSiweJ9LO55ZQRWj/+nOhs96jWDxOONR+3r1cvjvxuPGVzHbPZiOX+yPZXqgT+t3T7rVc+9MZ/Q6qwxp++WENv/zYvqOGwkiYeDzO9h01FBUWEo6EScQTSChESXExRYWFRGNx6hoaAKUgEqGwoID6xkYikQKKCguIhITmaJxYNEokLCBhROPU1DVQEBIqysuIxxMUFBRQ19hASXEJrS0thMJhYrEo4XCEwkiEkpISdtXVU1leTnm5Vbm17EFUIfn8db/OVFYVgn7Pkuf660gkUuUz1e8uY8mJfSadQ5vBlySW2pdc9dO6elrvvLNNV7kFkKOPovDYY1P1LJwDT9/nrRuQj3+WwvH7e5uY/QTxdx6ERJzwIWcSOeZTbccS0Wbq7zgDYk2uM0KUXnQ3kYETPfXUvPUHGhb9DzRBuGIEA8+5nUhJladMtGELG9/4KY2b51DcbxJDj/khxf28OQhr1r3Cutk3EW3eTr/RH2H0Ed8lFDaS+6rK7OcupWHXirbyEiph+gk3UzkwP7fJd2f9mLUbnm27pgOmfIkpEy/3lNm0fTbPvfd14gnzXg/tfzhnHPXnvNoBWF79LnfN/TrqiF0LIS6e9ksOGJxyGW2JN/O3Jb/gnW0voCil4TIunXANJw9NubbWRuv5xbL/443q2YwoGcL39ruKQ6q8n2drIsYvltzPC9vmo8DAwkp+sf8lHFg5pq3MusYd/GzJkyys3cjUimH8ePLHGFnaOxLqXjd/Pq9uNYIcxaEQ9x1zjCefX100xg/nL2JOjZm9G19Wyq8OmsrQkvxcUOOq3LJ4M0+sr6EsEuaLEwdx5oj8V3rf3tLKdbPq2sLBhpUIfz22ikqXq9PO5gQ/fq2F7U0QEjhrQphP7e9dZXpneZQn53mD4U7cP8wpU/NbhayvS/DWK63sqDaGX1Vf4ZiTCimv8P4ovfNIM7u2pibMxkwPMWmGN/VFS12CRQ+10FoHCAw+MMyY47z92bUgxvbXoyRaofLAMANPKuhWAzCxrZnoI2vRjY3IqD4UnDeKUN/0lB7xlTXEnl6B7mwmNHkABWfvhxTl91MS/3ALsWdnozsbCE0cTsHHDkeKui5XqMXy1X/M5ImFW7MX7Gb+cME0zj+s4zl4LZasNO6AR74My58z+flCYdixCsaeAB//O1S4PNx2roV/fAKqHcHDwjL4zKNmFW/ef+CFn5j6CkrNquHEj8Loo+HlG8z4OFxkUjZsmg/lw+CMX8Pkj8F7t8GzPzA5/Ur6wWWPwLD8xqqWjrFXmdmtjz7iSqZj0LfeRptdKlk+o6+t3MN3e7YTG5cRf/VeaGmAaDPxdx8iviKlPNT46NU+ow8gQeNDXv/pli0LaVj4X5PRFYjXrmfHi9eltb/5nd/SuHkOAM07lrLx9es9x2Mtu1j11k9obdyMJmJUf/gUmxf/q+342sX3eow+AE008cGb38xL4GXjptddRp+5pg8W/x/bq+e17YnHW3l+5jfajD6ATdUzWfTh/Tm3A5DQOPfO/1ab0QegJPjPgh8Sdwm1PLLmbt7e9jzqqE81xuu5bekNbGxMqbX+dfV/eK16FgmUtU2buG7xH9PEXv6z/jWed4w+gG2tu/jBon94BF5uWPo0C2tNjseFtRv55RKv6mdPZUltbZvRB9CcSPClmV6lrFtXrG4z+gBW1jfy60XLyJcn19fw0NodtCaUHa0xfvvBRjY05ifqo6r8eHadRwNkY5Ny8wdeic4/vtfKdudrllB4bHmcjXWpz6uhRdOMPoBXFsVZV52foMjMt6JtRh/Azhrl3Te8Ae7rFkc9Rh/A6vkJtq72KrMsf7rVGH0AClvmx6l1qYy21iTY8myUeCNoDHbOiVP7QQZVmD1E9OE16EajfKhrG4g9sS6tjLbGiT64GK1pBoXE4u3EXl+bVq49NBoj+sjbaE09qJJYup7Ya/mp+Fos+dIbjD6Ab/wvg/K4xdJZPP9jWPaMGZfuXGOMPoAPX4WnvuUt+9jXUkYfQGs9/OciqFkNj34F6rdAIgotuwCFZU/D8z9KjY/jLbBhthGM2bUW/vd52LYMnvq2MfoAmnbAv72aFZauo1cYfmNKK7IXAti6LXC3ZtjfHonNy9Pr2ZTal9i+Iu04ANEGz2bz+rfTisR2pJ/btM078GnZuZJENGVYNtYsQ33KRw3bF7a93rH5zcDuxFrraG3eEXgsiA2bg9MxVNek2qpr3EAsni45vX7bOzm3A1Dbso1YgIJogjg7m1OpMpbXpg8KFWVlbapPC2u9n1dNdBcbmrd49i2sTR+gVrfWsa0lZQx94Bh9befUbcpyFT2DJzZsSNu33TcJ8sHOXWllFu2qS9uXjUU7vRMeCWDJLv8kSPvsiirRAC/z93d4jbj1demF3t+aMug278xs3K3fkZ/hV70tvbx/36YVwcbZzq3eco3V6f2u25g6tzkglUTTxu5TvtSEopt8n+v6dPl73d4ILXFfufzuId1RB83e731iY+7PKIslX+J5qg5bLHs169txDd8wO3vZhu2wYU7bgkZexJpgyZOkpZGo32ISxVu6nF5h+K1urM1eCJAhQ4L3Dx6Ud5uh4VPS9snwyanjg9KPA2lBqsWjj0srUjAw/dySQQd5q+k3kVBBKvawtN8kQhFvLGLZoNSy+IDhJwZ2p6CwisLi3IUVRg47NXD/gH6ptir6jKTAp0QKMGrw8Tm3A1BRNIiCULorWVgK6FuScjWYXHVQWpkQISZWHti2Pb1ysuf4wMK+jCj2JoyeXjk2rZ5BRZUMLqpylRnhO2cEvYGPj0jv5+BirwvnQX2r0spMr8pPjRPgwL7ezz4sMLWq/ThZP1WFoTRVT4DDBvgUMyvTXR8PHpI6cVjfzI+wUQPye7wNHJxe3r9v+KTg+MG+Q7zl+gxM73fFiNS5xcNC+LPUlI7ovsexhMSr6gmERqXHG8nAUiiJ+Mrldw9J/woo9X7vQyMHZChtsew+4S4SRLJYeiWj0xXO2xjlOzY6QHGzbDCMPAJCHYgWKyyDqecZqWs3FcOhIL9xhKVj9ArDr10GpVYDC847F0p9g5eTTkSKUoMMOT9Y5VI+9SXveYPHETn1SijrD6WVhI+9mPC4lEpkn3P/lK5EJGH6fMIbi1g0YBLlB10BIRO/Euk7nv6n/CKt/aFHfYeyEccgkWJKBh3E8ON/7jkeKaxg/LE3UFwxhnBBGQP3+wSDJ1/cdnzkpIup6Heg55xwYQXTTrg5r7ihIYOPZNzo80mOSkUiHDzt2/Tvl1K/DIUinD7jTxS4lDdHDT6ByaPzSx0RkhCfO+QWwpKKfQpLhEun/5aQKw3GOSMv4+Qh5xKRAkKEqCrsz/+bcj2DS4a3lfnSmE9z+qBjKQ0XM6lsLL/a/5tEfA+li4YfyzlDjiAiIaN6WjKA30y93CMGc93kMzm872iKQwUc3nc0100+M69r6i7Gl5dzhmviozwS4dbDD/eUuXLCaI4Z0I8Q5tOdWlnOd/f3xpHmwkeHV3HJ2AFUFIQZXlrIjw4cwZAOqHr+5ohyIq5bc1x5iK9OLfOU+cYRhQwrM4UiIbhoSoTBfVL3Rkmh8PHD0n98Tp8WYXg7RmEQhx9dyKDBYt4cgQGDhCOO8cadDZ9YQP/h3u/T+MNCDBzlNQj3O6OI4r7OdygEww6LUD40VaawKsSQMwsoqBRCJdBvRoTy/btXbr7g46MJjSmDghChCeUUnD0yrYwUhCm8cAoyqA8UhglPH0zkuPRy7SGRMIXnH40MroLCCKFpY4gcOzXreRbL7nDZEb1jEu+OyzOkpbJYOotTr4cDPgEFfWDgZBh8gInRm/QxOPNGb9mzb4ahB6W2S/rBpQ9B5Qj4xO3Qb5xJbdZnEERK4YAL4GN/hOJKQKCwHMYeb8oMnAyfvBf6jYVz/2LaBCgfauq07BF6naqnxWKxWPZerKpnftjfR4vFYtl32HdUPZethIdfStvvzuOnqrQ+/zzMm58qcMQRFJ14greuB++AD5emdlT0o+iL30urO9HSSOyFW9Hq9YQnzCBytDf4VJt30Tzn38RWvAAiFB5wPkUHX5xWj6rStPI5WjbPp3DwNEonfNSzCqeaYPuCe6hb/RKF5SMYPOObFJR6XZ9am6tZ++5vaGnYSP+xZzJkSno7dTsWs3zO72iqW0u4oA+DR5/O6P2/QCicv1peY9MWVq1+mEQixtjR51Be5lUZa2ndxctzf8Lm6tkIIcYOO4Wjp32HSDj/JOWLtr7K8h3vMrRsPw4ddjbhjrgPAK2JKH9aeS9zdy3iwIrJXDvhcopC3pWoWCLOk1tmsax+I0f03Y8TAvL4rWmo5keLHmV9Uw2Diir4/qSPMr3Ku6pRH2vh0Y2L2NrSwKmDJjCtMtjNeG/m5c27mLujgckVJZw+vIpwBxQpb1/awEsbWwkLnDKskE+MLaG8wLtSt3pngkeWRdnRrBw8OMyZ4yMUuZYK4wnlzaUxFm6IU1kqnDatgIHlXefMsGJ2lHWLYoQjMPW4AvqP8N6vibiyaW6M7ctikIDyYWGGHhyhJM8VyHyIL2wlvjJGaGiY8CGFSEA+xGxoQonP24FuaiI0rozwlKoO90ebosTnrkXrWwhPHUZoeMfrslg6A1Vl/PefovsiabNTVRxi3vVndHc3LHsbtZtg9l0mjg6BRNykVigbDId+Fnath4UPQcUwaKmDuf80apyn/BimfSJzvcueNTn9NsyB1jooHwInfBfqNkPtBpMXcNSRe+oqLTnSa1b83rzwqozHk8Zfy1NPwwcB6nAnHE/RjBmmjD95e5L+gyi6wqtm1HLrl6A+JToQmnwsBWd+DQBNxGi47zMkkmpIDoUHfYriY6/17Ns186/UzbunbbvswEuomnF12/aG139C7aqUkmaooA8TLnyMsJMwXRNx5j14OvFoSvFw0KRPMerQVDvNDZt598mPg+9nre/gIzjwhFvSr7cdWlp38exLn6KlxVx7JFLKaSf+k7I+xrUykYjxn+fPpCXqFQvpVz6R8074R15tvbn2fp5Y9oe27YOGfJSLDvhpXnUkuWLO91lcv7Jte0LpKP552O88ZX6+5H6e2pIKXr5m/Nl8akQqDrOmtZGz3rrFH3bM3w++hGlOvJ+q8oXZD7G4zqjEhRB+d+CZHNl/35HgvnflNm5fnlLJO29kX74xdVhedfxkdh2vbvaKfIyvCHPbsZWEHCNyZU2Cn7zeglubYeoA4bpjUhMM/3mrhUUbUvd9OARXn15E/7LON7QWv9XKWp/65pEfL6JyYKqt5U+3sGOl93sYisC0TxVRXNX5fYq+0Uzs6VRQfPjQQgrPzz8fWPSxtcTnpp53kVOHETkm//hoTSitd7yJbnVEX0QovORwQqNzizW2K375YVf8cmPM957s7i7kRHFEWPKL3hFiYOkFNNfCX2ZA3cbg48VVJg1DJqGWc/4Ch1yavn/mHfDkN7I0LnDJA7Dfafn02JKF3f2N7BUxfoMjOQZ8LlwYvP/Nt1Kvg4w+gGqv1HNi+zqP0QeQWP5u2+v4xnlpRh9A66L0H5f6RV7f5YbFD7e91kSc2g9f8LYTbaB+XUqlc9fGtzxGH0D1qic822sX343f6AOo2fIe0ZadafvbY8PGl9uMPoBYrJG1659u295UPSfN6APYUbeM+qYtafvb49313vdm/ubnaI7VZyidmR2tuzxGH8CKxrVsbalu226INfPslrmeMg9vfNu3PTfN6AP497r32l4vrtvWZvQBJFAe3bgo7z73Zh5d6/1uPLl+J9FEfnPpb25JV3RdWRvng5qUsufLa2L4BfkWble2NJi2mqPqMfoA4gmYt6ZrUiNsWJJe74pZqeuItWia0QdGyXpbwLmdQfxdr3prfG4r2prfhJ5GE8Tnez/T+KztHeqPrq9JGX0AqsTmpqeGsFgs6TTHev5kvKUXsfTpzEYfQPPO9tU53/xj8P5Zd+bQuOZYzrIn6RWGX10sxxxhmVzNwh0QTSgMMDZDqXqkIF3VEkAi6W6VIZ9SkbgNWQkhAa6NIVf94cLytOMS9rowRgrL0so4BQPrb49IgGJnxCXkEqTo2VYunK7S2R5FvroioULCkr+rZ2GoAPHLJILH1TMSClMQ8t4Lpb7+lkeC+18WSa0wlQa4zpYGfO57MyUR76OjKCxtq3S5Esnw9Cl1uXGWRILrLHRcGUNiVEX95JlPPGck4FESKUx1QELpYmVJwvnr3+RGoe8NKCD/J3uI9A+kqIM/D4Xpb5IU9pqoAovFYtl7KMzf+8N7foaxZab9HS1n2WP0CsOvkdxmykMnnhi4X84+K/X66OB0BUw5yFtXxQBk2CTPvvARKdXK8OD9iYxNT19QOONLafsqDvsiKe12ofKwL6b6I0L/6V6l0cKKUZQNT/lFlw86iOKK0Z4yww/0tjNq/88TCqcbq8MnXECkIL8v3vChJ9C3KpVyoqzPSMaMTLmeDOp7AP0qJqWdN27YaRQXVuXV1injPu8x9E4a+1kKOhAnWBYp5aODvKkzTh5wFJUFKaO5KFTAFaNTn39YQnxutNcF4Zyh0ynzGYMFEuJyl/zxmD59+cjglBpmeaSQi0celHefezOfmzDIY3CZ7fwMv0+NS79fTxhSyISK1P3wkXFhynw29UfGhuhbbNoqjAjHT/YaGuXFcMiYrjE0Js7w1Ssw8YhUB8MFwrBD09suLBcGTumaPhWcUux5kkdOKkEyGMyZkHCIyAmuONUQ3u08CA2pJDTZlUqlpIDwjDEdqsti6Sz6FPSOlA7jB+7mQN1icTPxdBg5I/PxgVMcBc4gBE7/ZfChE74DgfoRru9ZUSUcc02uPbXsIXpNjN+sWbNo+c1tacfc4i4AsY0bif/vQWhuhpJiQhdfTEF/b2xJdM0KEg/cmtpxxicpmhrsLhtf+AqJDUsITzuF0FCv9L2qEl8/k9alzyAKBQdfQmTA+MB6ojvX0LplAYWDplLQNz2fXNO2Rexc8QTF/SdSNeGstFU6VWXb8odorFnGoEkXUlo1Ia2ORKyZNYvvpnbHQoqKBzB47Nn0HdQxaehEIsbmLW+R0ChDBx9D2GeMqSrL1z3Owg/vIxQq5KD9Ps/oIek5C3OhpmkTq2pmM6RsAsMrJmc/oR3erJ7Dq9vf49j+h3H8gODPdGndBlY0bOKQqnEMLe6XdjyaiHPHh2/w9o5VHFQ5kivHHUeZbyVQVZm7cyNbWxo4qv8oKgvyN1Z7OxsaW5m/o4FJlSWML+/Y9X+wI8qja5opjQgnDC3i4P6RtPQjjVHlzfVxtjYkOHRoiMn90w2oddVx3l8XZ2CZcPDYCAUdEDfJldrtcZa/F6WwVJhydKFnxS9J3eY425fGQIXyoSH6jgsT7sKBZ2JHnMRqI+4SGtpxAzOxuYnE5kZCo8sI9c1v9d6NqpJYXQ0NLYTGD0JKcl8RtzF++WFj/HLni/e8w3OLq7MX7Ca+fNxovvuxdMExi2W3iMdgxQsmli8UhmRYRlEZTDjVCLosf96IuxRXwCu/Mf9P/hFUDs9c7671sPQZWPce7FwNg/aHE38A1cvMsQmnQZ/c80hbcmN3fyN7teHnN/qStLz1FixfAQcfRNGBB6Ydj8dixO69GWq2w6RpFH7s03nlunOTaNpJbMNswhXDCGdK6p4jsaZqErEWCsuDRTJaGjYhoQIKS9pPdtzaXEM81kBJWdfmLUponF31aygrGUpBrnGY7bCzeQuCUFmcLigRTbSyuWk9Q0tGEgl13K1SVVnTtI0BheWUZehzayLGusYatrfUMaS4ktEZHlxrGmvoV1BKeUHHB8idiaqysr6elniciRUVFIS6dkF/e3OUuMLgDIP67c0x53j7hsiWxjizqqMcNbCAfsUdy2UXjSsbdiToUwQDKzqeD09V2VkTZ9dOGDosRFFx8HvYVJegsU6pHBAKNPw0oexanwBR+gwIU1AS/Hxp3ZEgXCKEMxzvDrQljtZGkQFFHX4u5tSOKrqjDikrQYpS95A1/PLDGn65s6mmkRNvfJmWLOHIyVynSV+jPmGIJiDP0FlPfdkioMsKYc6PPkphQffm87TsY6jC9mUml15xhVHkjLdCVReL1SUSUL3cJG4vsu6g+bDPGH65qHomdu4kemv6qmDBl64iVGESvbe88Ty883xamfCnv0Jk+Ji8+tX85i20zv1Xakf5EMovugfJuGyemS0z/8SOxfeDxukzbAYjTvx1W2xgIt7KqjeuY+eG10FCDBx/LqOP+G5gPave/z/WL/0nqnGqBh3K1GNuJFLQ+a4jNXWreH7mN6lv3EhBpA/HTf8hY4ae3KG64okY/114Pe9veR5BOGjoGVyw/4/aEqsv2jmHmxb+gNpoDZUF/fjGAb9mUuX0vNvZ2rKTry+4k1UNmykKFfC18Wdx/rCjPGXm7lzH9z94iNpYc9u+aRXD+b+DLybs9GdbSwPfnP8kKxqqKQyFuXr80XxiRPfO0m5uauKrs2axudn0uzQc5saDD2Z6376d3lZCld9+sJGnN+xEgZOGVPCjA0cQCRkjQVW58YPtPLW+HgVOGFzKjw8a1HbczQ9m7eKtLSkxl7NGFvGtA/P7EVi5Jc4/32wl5ozShvcVrjixyJPyIRcaG5Tnn2ymqTG1b+r0CNMOThkliYQy55lWqtebYZwITD0hwvCJqTL1W+MserAVdXmojzgywvDDUmXijcqGh1po3qxIGPofE6HfEd0fJxqfv4Pok+shmkD6F1FwybjdWvnLRGJnA9H/voZW10FBmMhHDiFyoPGEsIZffljDLzdO/8PLLN3amL1gN3P2AQO55dIjursbln2BmtXwrwuN4RcphRGHwpo3jdjLpI/BhXdBBt2D3WL7Cvj3hbBjlYkBPPtmmHZB57ezl7JPqHrmSvT+/wbvf/zx1EaA0QcQ/++tgfszEd+51mv0AdRtpnlm/gpGTdsWsmPRv0mOFBs2vkvNskfajld/+JQx+gA0wbYVD1O7eWZaPfU7l7FuyT2oU8/OrbPZuOKBvPuTCzMX/Yn6RqMUFY018NaC3xBPRDtU1wdbX+L9LeZzUZS5m55i8bbX247fvuw31EZrANgV3cGdy27sUDu3r36eVQ2bAWhJRLl5xePsijZ4yty47FmP0QewoHYDL2xJqcHetXoWKxqMu1BrIs6fVrxJTWsT3cntK1e2GX0AjfE4Ny7OoGC7m7yzrZ6nHKMP4OXNtby0OaXy+u72Jp50jD6AV7c08sKmdKXWpTujHqMP4Il1LWxuzE/98qGZKaMPYEONMnNlLPMJGfhgXtRj9AEsnB8jHk/N1W9eEW8z+sBMli56PUbcpcS38rmox+gDWP9OjOZdqfN2vBejebM5R+Ow/fUY0druzTCmrXGiTxmjD0CrW4i9tKlL2oq9usAYfQDROLHn5qItHXt+WCy50BuMPoDHP9jW3V2w7Cu8+HNj9AHEGmH16ymFz6VPwvz7uqbdF35ijD6A1nqTFiLavWOofYleYfj1z3XGoaEheP/O9NQDacTzGygmdq0P3l+9MnB/e7TWpUudt9aubXvdHHA8aF9Tjvs6g9oGb73NrTtpjdZ2qK7tjel9rG5MXf9m3/FNTWv9xXNiXZNXnr5VY2xu3ukrUxN47vKGVPqGdY3e+ymqCTY11/lP2aOsb0wf1ATt65y2WtL3NbS6XqcP4Dc0pH+/1tQHG3gbG3M3gOIJpTbg96K6Ln9Phrra4HNaXfMADQFlEnFoaUztjzYG19O8M7W/tcZ3jQrRnd3rfaF1MWj19kur0z/rTmmrxjcREI2h9faH32KxWPYYO7KMV6tXdE27/nFy8y5o6Fj6IEv+9ArDrzqW2+BDxgcLq4SmuGLvMsWs9MsvUXFk6EEQSRe0KJicf+LVPkOP8KZ4AMpHndD2umrE8biVkiRUSKXPRRGgatBhhH3pEfoPPyGtXGcwaoi33kF9p1FS1LEg3ikDjyPk0skPSZjJA49t2z5sgFc99fABJ3aoneMHTPVsDy/ux4Syob4yXgGfJGcMTrlyHj/QK84zpLiciWXtx112NccNSr9/TwjY1xkcNbCciOt7FAKOGZRSTz1yYCluL8sQcPSg9BQgMwYVpiXgiAhM7Zu7OEk4JIwfnP4YmzI8/ziZEaPSzykohJI+qfoHjU4v06cKSitSZSpGpvcnXATlw1L7yyZ46wmXQvGw7n0cS79CZKD3mRaenL/bei6EJ3rjmKV/BdIvPW2NxWKxWLqIyR/z7RDv67TjXdTu0OlQNbJr2rKk0ftj/K79DEVFqRXBlttuhxrXqs3IkRR9+lNtm7GWJuK3/MRbRzhC4bW/QDIl4MpAbOtSmp79AVq7CcKFFB5yKcVHfCGvOpI0bl1A9YK7ibc20HfSeVSO+6jneM3al9iy7AFC4SKG7H8ZFYMPDayndsci1i66k2jrLoaOPZchY88KLLe7xBNR5i2/gw1b36FvxXgOnfRlSos7bvws3vYGb679DyIhjht9CRP7p9JZNMbquf/Dv7F81wImVU7nk2OvoiSSf9xiQhP8e/1rvLxtAcOL+3Hl2NMZ6RPKaYi18LdVr/H81kU0xlupiBTzlXEncubQaW1lVJX71r3PS9tWMKS4givHHs6o0qoOX3tnkFDl7lWreHj9emKJBMcOGsTXJ02iNNI1KQRmbq/nPx9uJ65w4Zh+HDuownN81vYm7vtwF9GEcsGYCo4bHPx5zdzays/m1VMfVaoKhRsOL2dKVX6xbk2tyiOzWlm5NUFhGE6eGuGwcfnHy6kqC+e1snhhgkQcSvvA8acWUVnlfS5s/jDG0ndiRJuVqkEhpp5QQElZqkwirqx4tpWdaxKgUDpAGHtyIX0GeOvZOTdG7aIYkTKh/9EFFA3s/nk43dlK9OVN6PYWwpMqCB87GAmIzdztdhIJ4u8sJb5sA9KvjMjx0whVmXvExvjlh43xy43319Zwzv+91d3dyMqCH59KeWnPEAyz7OUk4vDGH2HJkzBgP9jvIzDv3xBrgRlfhP3P7Zp241F4/few7BmTTuLkH7avHmrx0GPFXURkJHAvMBhQ4FZVvVlE+gH3A2OA1cAnVTXYv87B/rBZLBbLvsG+YPjZ30eLxWKxdITd/Y3smuUAQwz4pqrOEZFyYLaIPA98FnhRVX8tIt8DvgcES1S6CMrhB96UDppI0Hr3PbA95Sss48ZReMEn2rYT0VaiN//QW8mRp1F0rDeRd660LnyE5tdvhkSU8NDplJ53S94rhxqPsv2Df9C4eRbF/SYzYPrnCBd6lQ2ba9eyaeHdRJu203/sGfQfe0ZgXS2N21j41vdoqltDaeV4ph7zawqL8ld2XL32CT5Y/DcSGmPCmAvYf7J3JXNH7QreX3EPO2qXg4QYVHUAB038HGUl+Sd93lC7mCeW3cT2hrX0KxnOmROvYXTVtOwndoDq1jruXPMCaxq3cVz//blw+NFt6qFJXtq6hF8ueYqmRJQQwkUjDuPqCV7F0vpYC3etns3Sum0c2nc4l446mILQviPDnVDlf2uqeWtrPaPKCvns+EH0K0o9TlbXtfLDOVtY3xgjJHBY/2J+fshgisL5fTc21CV4dFmM2lbl+JFhjh6R/shaX53gn2+20OB4hI8eIFxxQiHhLkpnsWJ2lDULYySiUFwuTDqigEFjuu6zj21N0PhGjESjUnJwhKKp6W0ltsWJvdKM1icIH1JEZHphl/XH0il06u+jJTem/eRp6rLlcuhGwsD713+EPsXdr/BrsVj2TvaYq6eIPAr82fk7UVU3ichQ4BVVndTeubmmc2j5939gfbroSmjGERScYGLSWv74g0Ahl8iV3ydcmZ+BFN+5joZ/XujZFx51JH3OuSmveja/9wdqFqcUSctGHMvIU37Xtp2It7LgsU8QbUqpfY075uf0G51urL792Jm0NqcS1Bb3GcGMjz2YV3927FzMi69+1rPvsIN+yNjRZwPQGq3ngZc+TotPzKWyz2jOP/G+vAzfupZqbnzzfKKJlIJGWAr45tEP0LdkaDtndozPzr6ZpfUb2ra/MvYMLht1Utv27Jo1XB2gZPX7aRdwVP9UDOm33n+Kt6rXtG1/csQ0rt3v2LTz9lb+sXIbty1PCd5MqSzh70eNAyCaUM56fjXNvvHVQf2KuXlG7p9pc0y59oVmal0hvt84opDDhqYMn4Qq1/+vGf9TbMyAEJ8/qfPdpdYsiLLk7fTnx+FnFdJvWOcbf4kWZcfNzahL96Ti4kKK9ku1pa1K8+92QUPqXSi8pA/h/Xun8bcvrPj52d3fR7vil52P/ek1Fm7sXhGuXOhTGGLhz4Indi0Wi6VXpHMQkTHAwcC7wGBVTWqEb8a4urTL/uX9cmsowOgDSMx/P7WRQb0z/sYzubXhomXmXen1bJiTdz21q1/0bNevf5OEK6VA/bb5HqMPYMda7zkAzQ2bPUaf2beeaGt+apvLV6YbPitXP9T2euP299KMPoBdDWvYUZufCtTS6rc8Rh9AXKMs3v5GXvXkwvqmao/RB/Ditvc92y9tWxp47m0fpvrTFI/ytsvoA3hpa/5qrr2Zlzd7P//Fu5rY1GiUPRfWNKcZfQALaprTd7bD4u0Jj9EH8M5GrxLokg3xNKMPYG1118zqr18arES6eVV+KShyJfphwmP0AbQs9LaV+DDmMfoA4gtasfQOdvf30ZIbvcHoA2ho7bkrkhaLpffT5YafiJQBDwLXqqpntKhmuTFwyVFEvigis0Rk1qurggfjaRRmmOHuk10IJDR8dG5tuAgPmpK+szB/0ZFCn7JkpKQ/Ek5dS2GfIeDTPyzqk75yUlBUCb7VNglF0pQ+s1FRPjZtX5/SlApfWYaVuJBE8hZ46VscXFem/btD34I+FIe8LjRDi/v6toNVDMf3SV1XYShMv0LvezqkeN9SJBxS4n0fS8IhKgvNKtTgkmAP8rJIfo+bAaXpoiIDS7z7BlYG11nURU7spRXBQicl5Z0vgAIQrkqv179P+qa/B9J333E77s10xu/jtm0271suRLrmK2qxWCy9ii41/ESkAPOj9i9VTS4ZbXFcWHD+bw06V1VvVdXDVPWwgQMH5tRe5OyzA/cXfPKTqY3DTww+96Cjc2rDTeGBFyCl7hQGQslpP827nkGHXUO4yBgcEilh8Ixvetwli8tHMnTq5W1GXUnleIZMuTStnnCkhFGTL/fsG3vAlwiF8hsFT97vM5S6DL2CSDmHHPittu0BVVOYMuZCvMZoiEMnf5mSohxXZx3G9T2Ug4d43VoOGHQSkwbk/3lko0+kmKvHn0WBkzpicFEVV4053VPm48MOYkRxlWdfgYT59sRUubCE+MZ+x1LsvK9VBcVcPaHz+9uTuXK/QQwsNtdfGBK+OnkwpRHzvg4tLeCM4d4YVQG+MTW/dB8jK0J8bEKk7S4bXSmcMd57Lw8sDzFpaPpj7LzDuyZGZtKRBUR880sVA4WRU7rG0owMCVEyI2XERYYKJTO8bYUGhYkcV9T2dZQhYSLHWFXAns6e/n3c17nj8t7hPfy1k4PTUlksFktn0JWqngLcA+xQ1Wtd+28Eql3B6/1U9Tvt1ZWMYUgTeDnvRIomefOuJaJRoi+9ZNw+J0yg8PjjEV/uvlhjPfF7/giNDXD8GRQdvnu57qKrXiNevYrCgy8hFOnYgDMRa6alZgWFlWPShF2StDZuJdq8g9K+k9KuyU1L41Z2bH6HfsOOpag4P0PMzZZtM4lFGxg+7MTA4/WNm2iO7gJVSosHUVrcsTx+ADsaN7CpfjmDy8YxoHRUh+vJhZrWejY11zCxbBiRDIIsC3dt4JGN85haMYzzhh8cWKYu2sLaxp1MKOtPUbgrdZJ6JrGEsqy2iWGlhVQVBoiuNLTy2qZGSiLC6SPK2gzDfNnemKC+1Rh+me77LbsSzFoZpbQIjplUQGGeq4v5oAll+/oErU1KeX+hYkDXr67FdybQZmMIZiKxMwGNCWRouN3nQ09nX4jx64rfR0t2orE4Z978Csu35ed2vicYUh7h6WtPpG8fO2ljsVgy05Nj/I4BLgNOFpF5zt+ZwK+B00RkOXCqs90xHnklbZc2NMCuWigtJTJwICTS/eUlHIbCItAEvPsy0W2b0srkSmzzB8R3riXUdxRCx+N8QpFiSgYekNHoAygsHUSffpMzDuo0EWf7htfZ9OHjlFaO2y2jD6CqYgJKgrr6tYHHy0qHsqt+LfNX3MOWHfM63M6SbW/w9Iq/0BitpX9J1yfx3Ni8g1e2f8C8XasylplaOZzrpnwso9EHUB9vZUtLPbWx4EFETWsT/123iP+tW8zO1swDjY1NDby8dT3bW5oyltnZ2sKrWzextqE+Y5k9TSQk7F9VGmj0AYzoU8j4ykK2tsTZ2BgcW5sLRRFha6OysT7zJFWfYogprKtWVmzumng7N63NCao3xqmtVhKJ4H611CWoXhGnpW73Y3bCVaF2jT6AUFWI0LBIh40+TSjxVXXEV9WhGa5JW2LE5mwm9vZ6dFdLYBmA+IadRF9bTnzZlox17eN0/e+jJY37Z67tkUYfwOa6GG+tDFzgtVh6HvEoLH8BPnwd8llA2roEFj0GjTu6rm+Wdun9CdxJqXrGPviA+FNPew+Wl1P42cuRkhIA4ls3Erv3prQ65LiPUjjj5LT97dH47A+JLX8htaN0AGUX3kGofM/H48djzcx54XM01qZERgaN+ihTjszf9RRg67ZZvPHuN4jHWwBh+tSvMXHCxW3HVZVHXruUmrqUmMvAqgM4+9g78mrnjtlXs6LmvbbtvsVD+ebR/yOcp3tqrvx62YM8uundtu1j+0/hxgOuyLuepzcv5YYlLxNXJSIhfjb1NE4cOK7t+Hs7NvKt+S8Qd75fBRLipoM/wkFV3nvjsQ2ruHHJbBJOmZ9PO4rjBg7zlJlXU8235r5Lc8IYNF+eMIVLxkzIu897mm+9t4mZ1alB1mcnVHHFfvkp5y6tjvObt1tpdmy5i6ZEOHeid1V91dY4d73qFTMZ0ReuOrWkYx1vh1hUefOBZppd9ndRKRxzYTEFRSmDa/vSGCtfiIIaD+3xpxXQf7+euyqs0QSt96xANzQCIMNKKPzsfkiBKzH91gZa75oPrSnDuuDjkwgfMMhTV+vjC0i8nxLakgFlFF5xFJJhgsDPvrDi15nYFb/c+MgfXmHZ1obu7kZWjhpXyX++uO8oRFt6IU074c6PwrbFZnvMcXDZwxDO4vH26o3w8i/M68IyuPQhGDWjS7u6N9KTV/w6jVydJ+MvpCtdUldH/P0FbZuxx/4ReK6+np+qZ3zLIq/RB9C4ndb59+dVT2exde1zHqPP7HuGhl0dU5v8YMnfHaMPQPlgya3EXCtbW3bM8xh9ANt2fsDOutU5t1HduN5j9AHUNG9i0bbXOtTnbGxvqeUxl9EH8Eb1YlbU57/i+5eVb7cZdTFN8LeV73iO/33lnLbjAFFNcNuquZ4yCVX+tnIBCVeZv69cgJ/bVy5tM/oA7ly1lKYM6rQ9hQ/rWj1GH8A/V+4kmufqz/+WxNqMPoCHlsZojHrreHJuNO289TWwdnvnr/xtWhH3GH0ALY2wwaf2ufataJsshyZgXUAKiJ5EfGFNm9EHoBubiH/gzRsee3Odx+gDiL7woWc7UV3vMfoAdHs98Q82dnKPLZb86A1GH8Dbq3Z1dxcslvaZ96+U0Qew+nVY9mz75zTthNduTG231sOr1qGhO+gVht+QohyVMuMZBnrNTcGvdwNtDn44Z9rf1URbg9vNN5VDklbfefF4M4lEyrUrKJ0DQHNrTeD+IBoz1NEQzb2OfKiPp+d7A6iNNQbszUxClbqo181tV8y3HU13J/Lvi6tSH/MaLbXRdBl+/76WRILmTPd6D6E2mu7eGFPyNvzqfUZeNAEtvktvjgbX2dgFGQ2iLcFt+ffHfV6QseYe7lnRGHA/+fc1BRivTdH2t7Ptt1gsFkvvIshNsymL62a0Mf2H0bp7dgu9wvBb15LbTJ1MmhiwUwjtv3/bZvjY09PLAAwfk1efwiMORcr9KQeEgikfy6uezmLQyFMIhb1B4cV9RlDZ/8AO1ZdM1p5k+NATKCxMpToYPnAG4ZC3vYJwKYP7Tc+5jREVUyiNeNMnhCTCtEGndKDH2RlTOogxpV63tP6F5RxYOSavekIifGzoZM++s3zb5w5Lz7l8zjDv/VkQCvHRId40ImcNS0+lcdZwr9jNsQMG07ewZwsAHNC3iMoC7+PloL5FlOYpunLiKK974EGDQ/Qt9sawHTE+3YWwMALjB3f+423IuAAhF4GhE7z7B05pf7unEZ5aBYWu96swZPa5yxyU7sIePsT7DJThVdDPlz4mEiK0f+enZ7FY9kaKesWozLJPc+AnIVKc2i7pB5OyjH0rhsF439jukMs6v2+WrPSeGL+f/RoWfJh2LBnfl6T16afRhYtMsOnAAUROP53wUO+go+Wlx2COK0H40NEUXfL/8u5Xon4bLbPvIb5xHlI2iKJDP0Nk2EF519NZNOxaxYcL/kpT/ToqBxzEmAO+SOFuCLysXf8sm7e8TWXlBCaMvYBwuNhzvK5xEy/N/j619WuoKhvDyYf9lj4l+UmL17fU8K8F32dT3TKqiodw8bQbGFQ2psN9zkZdrImbVzzO/F0fMrFsGN/c7zz6Feafgy+WSPDIxoUsrN3KQVVDOXvoFEI+UY3HNyzjoQ1LEREuHDGFM4amy3THEgke3rCSxbU7OKTvID42dEygOMcLmzfw9vatjCsr5xMjx1DcC1REdzTHuHHhdlbXRTlsQAlXT+lPYTh/4ZF3NsSYuyXB8HLhI2MjFAck5HptSZTXl8SIxmFYFVx0VBGVpV0zgqqtjrPwtVYad0FJhTD12AIqB3kNO00oWxfGqducoHxoiEH7h5FQz1baTGxrJj5zOwDhwwcQGlicVia2rJr4G+sgmiB04CAiM4anXZc2tBB9bTm6ZgfSrw+REycSGpT7d8zG+OWHjfHLjVg8wYTrns5esBsJAyt/3T2TxxZLXmyaD7PvNgbgEVdCv3FZT6GlHt67FbYvg4mnw9SPd3k390Z29zey1xh+9ofNYrFY9n6s4Zcf9vfRYrFY9h129zey5y8bOKTl8Ety/kkU7WcUDhN1dUTvuBNaXcE9AwZQcPlnCIVTM/It9/0N1qek/OXgYyg85dwu6Xdnsn3VU2xedA+qCYZMvpiB+3lnSzauepRV824iHmumT+V4pp/0Vwo6sJoFJqZv3gc3s3HTa5SXjeKgaV+nqjLAlXYv5bGN8/n3OiM8c+moGZw1tGMus53BQ+tW89+1q4iEhM+M2Y+PDB3RZW3FEsptK9bzwqZqBhYX8uWJI5ne13sPrWto4aZFm1hZ38Lh/ftw7f5D6dPBHH2xhHLrkkZe2tTK4OIQX9m/lKl9uyb5ei5sXB9nwZwoLS0wbmKYqQd2LD2CJpR178SoXhanoA+MOqqAihHd5+4ZfXMn8Zm1UCAUnNSX8P6Z08ZYLHsja7bXc8LvXu3ubmRl1nWnMqC8Z7vyWyyW3kvv9yZ/6OW2l9H/3Oc1+gC2byf+2ONtm7GZr3qMPgCd+yaJTcG56noKDTuWsPqdn9Ncu4aWunWsmfkb6ramVCJbmrazfNaviMcagQQNu5bzwRvf7HB7C5fczqrVD9Hcsp1t1XN4491vkUj0bGXCzmLBrvX8etkzrG3awdqmHdyw9GkW1naPKuGsHdv4w9IFrG9qYHVDPT9fOJcVdR0T7MmF/63dwn9Wb2ZbS5RFuxr4/tzlNMa8Ih8/nLuOmdUN7GiJ8ezGXfx5yeYOt3f/qmb++2Ez25sTLNwZ4/sz62iJd48XQlOj8sZLrdTsUBoblA/mxli9smMiOlsWxNk0J0ZrvdKwRVn6ZCux1u65rviSBmLP7UBrYujWKK0PbCVRbcVWLPsWJ/YCow/gvL+8kb2QxWKxdJBeYfgNLckxH9fOnYG7ExtS8uLxZe8HloktX5hvt/YodZtngU+TsnZzyr1nx6a3047X1yztcHtbt830bDc1baG+YV2H6+tNzKpJnwSYXbOmG3oCs3ds92wrMKdme3DhTmnPa1TWx+Isq02JK+1oifFhvVeZa3Z1x2XSZ2/3q5oqK2q7Z4Jh+9YECZ8Y6ZZNHUu+vmud12BMRKFhy+4ncu8I8VU+JeMEJFZ3jrqxxdJb6PlBLYb1O3tmgnmLxbJ30CsMv01NOQ5SSkuD9/fr3/YyNDxdNREgPCJ4f0+htF+6SqR7X+WAdFfE4j7D0vblSlWVt72Cggr6lO4bynyTytPVCyeWpe/bE0wsr8xpX+e15/0OFYaEMWWpiZfKwjCDir2umBMr0kVAcm6v0uv+WBSCUWXd4xJZ1S/dpbNvv449IvsM9J4nISjpYF27S2houttY0D6LxdL9VJX0bAVgi8XSu+kVhl+7lKYekgWfOD/9eFERBeee07YZPv5MKKvwlhkxlvC4yfRkKoYcztCpVxAKFyGhQgZP/jRVw49rO15aMZrhEz8NmMFrpLCSqUf/tsPtTZvyZQYNMLGjJcUDmXHo9WmqnnsrR/cfzyUjZ1AYilAUinDZqCM5sn8OilVdwImDhnLhyLEUhkIUh8JcMXYiB/Xtn/3EDnLJ2KEcO7AKAaoKInx36liqClOGXliEHx04nKElZt/UqhKuntzxCYFLJ5Rw1KACBOhbJHxvehnlBd3zWCqvCHHokQUUFIIIjB4XZsLkjg3Chh4Soe84cx2RYhh7cgGFfbpH1TM8vYzwoeVGMrBIiJzWj9Awa/hZ9i3+funB3d2FnPjPF4/u7i5YLJa9mF6l6plIJIjeeEfbfn8qhyTRmhoS9Q1E+lYRLgsWMYg3NRDfvpnIkFGECrpPTCJfEvFWQNNy9iWJx6PEWmspKukc4yAabSASKUGk988R5EtLPIYIFIa6XwOpJR53+rJnZoObYnEKwyHCGYRNVJXGeKLDoi5+GmNKUZiM7e1JEgklkYBIQNqIfIlHlVCYHpHKQaMJEEE64bq6EqvqmR9W1TM/nnp/A4/MWkNdc5SR/csY2beEJZtrSahSWRSmMZ6gJBwhGlM21zfTt0iJEqZvWSEiSktLgmFVZazcVktpJEJFWSHFIWVXS4KGpih9SwvY1RpnUFkRCpQVRWiNKw0trdQ3JygpgMZogoFlxQzrW8qDs9ZSHE5w/QWHMGVox9MvWSyWfYN9RtUT8Bh9YJQ+g4y/0KbN6IIFJAYNJHTccUjEe5mxTeuIP/EvqNtFtKofkYuuItynIq2enoaqUrv5PRp3LKNiyOGUDZyWVqa1aQvb1r1EYUl/Bo08Nc1AVI2zecMrNNSvZdCQY6ioSlfqjEbr+XDt41Tv+IDyslGMG30upaVDuuy6djZv4f0tz1McKWP64I9QFEl32V28cy6Lds5hQsVUpvc7ssNtbWrewYtb36eyoA+nDZpOcbgwY9miHpQrryi8Z91/Stox6GpbYzy/aRcbGlspDAnT+/bhqDzytAVR2o4x0hpX3lofp7ZVmTEszOA+wZMQC9bGmPVhnCFVwqkHRCgId2yyIhQSQp00zxEu6DlGlnTTSqrF0lM49tcvemLo3l5b38GaqjunQy7OuPltjhnfj39deVSn122xWCxJes2K35sXXpXxuNv4i77yCon3XMIkFRUUfSl1bmL1MqL/uz2tjoKv/8qT8qEnsm7On9iy5N9t22Nm/JAB489q267bsZh5L19FIm7ENyoHHsxBJ/3NU8f8mdezcW0yiW2IQ476LYOHpVxGY7FGnnv5MhoaU4I4kUgppx5/N+Xlozv9mrY3ruUv711Bc8z8AA8pm8BXj7iHsGuV7en193PPij+0bV8w5kouGPOFvNta2bCZL879M41xo/w6pXwktx/8/wjtg6uZHaUuGufzb61kc5NXlOXTY/vz5UmdPzmgqlz/eivLa4wwSlEYfnJcEWMqvZ/ZCx9EeXVxShSmbx/hG2fuG67Jext2xS8/7Ipfbkz+4VM0x3r+eGdYVTFvfe+U7u6GxWLpoezub2SvGPFGyH3WPDF3nndHbS3xDRvaNqNvPBt4XvztFzrStT1GItbM1mX/8+zbvPifnu0NKx5oM/oAdm2bS231grbt5qbtbFz7jLtWVi//N242bHrVY/SBMQZXrn5oN68gmPc2PNJm9AFsrl/Bsuq3PWUeX+e9zifX/YuE5q+Q+NDGt9uMPoDFdeuYs3NVO2dY/LyyeVea0Qfw4JodtPolMTuBpTsSbUYfQEscnv8wXfXznRXefTUNysaajqVisFgsexeJhPYKow9go1X1tFgsXUivMPx0Twgx94DYorzJqc9ZyqQdzlB+j74/2duSPCYDdq8li5tM73t3v49B7ffGr7TFYrFYLBZLV9ErDL985u1DB/uUuyorCQ8f3rZZcNxHA8+LHHVqB3q25whFihk06ULPviFTLvVsD9/vk4RcypuVAw+hov8BbdvFJQMYPvrMtm2RMGP3u8Rbx9ATKOszyrMvEunD+DEBiqmdwBHDP05xJBUfNrRsIhP7e2P4zh31Gc/2WSMvRTowqv/EsKModcU8HlA+ioOrukets7dy4pAKhpWkiyFdMLo/hZ0VGOdiUr8Qk1xpEIrCcPrY9NjLIyd49/XtIwyt6tmu2xaLZc8QCgklPVzUKMmIKuuibrFYuo5eE+M3a9YsWn5zW9qxIHGX+JKlxBcsQAYNInLsMYgvdi++ZQOxJ/4FtTXQdyCRT15FuLRPl/W/M9m18W0aa4y4S5/++6cdb6rfyPb1L1FYMoCBI04m5BMvUU2wdePr1NevYdCQYyivHJ9WRzRaz5p1T7O9ZgHlZaMZN+psSkoGddk11bZs4/0tL1Ac7sOBQ06jMFySVmbprvks3jmX8RVTmdb38A63taV5Jy9tM+IuJw88kOJw71F07SnUReO8tGkX6xtbKQoJB/btwxEDg9VzO4PWuPLuxji1LcoRw8IMLA02MBeujzFrVZyhVSFOPiBMpAsMUUvXY2P88sPG+OXOyb99iVU7cswL3A2cMmkAd1wxo7u7YbFYejC7+xvZqww/i8VisezdWMMvP+zvo8Visew77BPiLhaLxWKxWCwWi8Vi6TjW8LNYLBaLxWKxWCyWvRxr+FksFovFYrFYLBbLXo41/CwWi8VisVgsFotlL8cafhaLxWKxWCwWi8Wyl2MNP4vFYrFYLBaLxWLZy7GGn8VisVgsFovFYrHs5VjDz2KxWCwWi8VisVj2cqzhZ7FYLBaLxWKxWCx7Odbws1gsFovFYrFYLJa9HGv4WSwWi8VisVgsFstejjX8LBaLxWKxWCwWi2Uvxxp+FovFYrFYLBaLxbKXYw0/i8VisVgsFovFYtnLsYafxWKxWCwWi8VisezlWMPPYrFYLBaLxWKxWPZyrOFnsVgsFovFYrFYLHs51vCzWCwWi8VisVgslr0ca/hZLBaLxWKxWCwWy16OqGp39yErIrINWOPaNQDYnuW0ziqzp9uzZfbNMj2xT7bM3lemJ/bJX2a0qg7Mco7FIeD30bLnyPU7Z7Hsbdh7v/vYvd9IVe11f8CsPVVmT7dny+ybZXpin2yZva9MT+xTrv22f/avp/3Ze9f+7at/9t7vvX/W1dNisVgsFovFYrFY9nKs4WexWCwWi8VisVgsezm91fC7dQ+W2dPt2TL7Zpk93Z4ts2+W2dPtdWa/LZaehr13Lfsq9t7vpfQKcReLxWKxWCwWi8VisXSc3rriZ7FYLBaLxWKxWCyWHLGGn8VisVgsFovFYrHs5VjDz2KxWCwWi8VisVj2ciLd3YHOQET6AV8CmoHbVbW2m7uUFyISBgbj+jxUdW0XtVUITHQ2l6pqtCvasVj2VUTkAGB/oDi5T1Xv7b4edT0ickh7x1V1zp7qi8XSUxCRY4AGVZ3X3X2xWLoSETkN6KOqj3R3Xyzt02sMP+cBOk9VG0TkUuAQ4GZVXQM8CLwN9AfeFpGzVXVVO3UNBg53Nt9T1a1d3P2MiMjVwE+ALUDC2a3AgR2oq733CBE5EbgHWA0IMFJELlfV1wLqGoR34Jq3ISoi44H1qtritH0gcK+q7nSVqQSuB45zdr0K/ExVd4nIN9qrX1X/kG+fcujz1cA/VbWmnTLTVHVBO8ePwVzTaMx3TABV1XEBZc8PqGIXsCB5X2b7XDuTXIwWEflM0LkB5foC+/nqes11vA/QpKoJZzsEFKtqo4icrKovZXh/UNWHnHPCwNdU9Y9Zruts4MlkW1nKZr33M5URkZ8AJ2Lew6eAM4A3gHtd54Yx34NLsvSjFPgmMEpVrxSR/YBJqvqEc3w/4Fekf17jnOM5fX/y+Z65PzMRmQhMBp4Gfu8UKQYOA+Zj7vsDgVnAUa46DsN834cBTcAHwPPtfecslt6EiIga5bxfAjcC87q3RxZL1yAi4rw8C0gbS1p6Hr3G8AP+CkwXkemYwdDtmMHUCUB/Vf0BgIg8B7wqIjudcl9Q1U8mKxGRT2IexK9gBia3iMi3VfV/rjITnfYGq+oBInIgcI6q/sJV5jDgOtIH9we6ygwEvkv6wOxk13VdgxnMVbd38TnW1d57BGZw9hFVXeq6zv8Ah7raOccpNwzY6lzfYmCqrz/nA78BBjnXnrz+ClexB4HDRGQCRvr3UeDfwJmuMndiBn7Jz+gy4C7gfKDc2TcJY6g/5myfDbwX8P5cCYzBu3L6ORFZgDGmA3F/ZpiV15kiMsfp27OaLn37fyJSBNwN/EtVd/mO3wF8HZgNxDO16/B5zKD4ZWf7ROe8sSLyM1X9B1k+12z3hog8nuX6z3HKZTVaHA53vS4GTgHm4DVuvoC5t0dgBj1HYiZn3Pfri8CpQL2zXQo8BxztXNtLmM86rcvAQ07f4yLyaaBdww+4CLhJRB4E7lTVJf4Cudz7OZS5AJgOzFXVK5xJpn96Om/6PFpEClW1tZ0+34W5F5JG0wbgAeAJ1/GfONd+EnAFXvf9XL8/5eTOa8BxjlH/HDATuEhVTwIQkYeAQ5ITI85EwvXO6yuAq4EPnetairl/jgW+KyIfAD/qKm8Hi2UPIpjnVAxo6ea+WCxdRnJ85Ezi9+vm7lhyQVV7xR8wx/n/Y+Dzvn1vAmNcZQUYjhlIDvXVMx8Y5NoeCMz3lXkVOAIzeEvu+8BXZilwDjAWM/gbDYz2lXkOM7BfjBnI3gn8xlfmZSCSw/XnUlfG98h5/X5Ave/7tudjVk7nOtsnAXcEnLcCmJLjZ/Zt4Grn9VxfmXkB583zbb8GlLu2y4HXfGXewhiinwQ+kfxzjiU/n986f9Ocv18Dvw5oX4DTgfuc67wBGO8rk1xtWYExZk9zHXs3j/v6WcwEQ3J7sLOvX/Key+FzbffecPadANwM3I8Z+J/t9PuPrnILMIbDfFdfns/hGqqAZ3z7FmAG9fOc7cnAQx347McGlBnr2/4j8GfMKtIhyb+A8yqAq4B3MEboF333VdZ7P1sZjAcBGMOmwrmXlgT05V6M0fQj4BvJP1+ZWf7vDK5nFTA7+V779+X7/cnjfk3ei1cD3/F/ZsDCgHMWOv//H1DSTt0HAad0pF/2z/71lD/MROopzuu7gaOd10WkUmiFuruf9s/+7e4fxrvjZuf1TcAXfcelu/to/9L/etOKX52IfB+zInSc4xZW4Bz7HFCYLKjmjtvgbDb66gmp17WzmnSRm1JVfS+1gg2YmTs321T1Mdqnv6reISLXqOqrmJXImb4yq4BXRORJXDODmu7GmEtd7b1HALNE5HZSKxCXYNyw3ERVtVpEQiISUtWXReSmgGvboqqLs1x/1FmNuZzUyk2Br0yTiByrqm9Am1tjk6/MYMC9MtLq7HNTqqrfDeqEplxdT1PVg12Hvues7H3PV15FZDOwGfO59wX+JyLPq+p3nDLLReSHmPfvT8DBjsvDD4CXReRGzKqU+zMNinMaqapbXNtbnX07RCQZf5n8XC8Fjg/4XNu9N5x9iMjvVfUw13mPi4j780+68MVEpCLZl4A++2nATIC4aVbVZhFBRIpUdYmITPKfJyKHJN8XETmU9M/+QYwh5+Z/uFapMQYDwM9c+xTv6iKqWisi/wNKgGuBjwPfFpE/qeot5HbvZyszS0SqgNswxl89xsj0s9L5C5F5xa1VREqca0m6TrtXD1qce2G5iHwV88wrC6gnl+8PIlKMmUCYinfl+HPeYnIU5tnxeWdf2HX8/YBnzPtOPX/JcJ3Jdua1d9xi6SUcA3xaROow38cKAFV1f3czemBYLL2IauAYEfkFxpNjtfugM5ZKuj1begi9yfC7CLgY+JyqbhaRURiXTdRxXcyRZ0TkWYyLY7Lep31ltjuDrOSA6wJgk6/MT5wBzot4B/cPucokB+6bRORjwEbSl8LXOn+FuIzXAHKpK+N75PBlzKz715zt14H/89WxU0TKMKsE/xKRrZiBPeCJSZslIvcDj5D5+q/AiO78UlU/FJGxwD987X0ZuMdxEwCoAT7rK3Mv8J6IPOxsn4eJVXTzhIicqapPkRkRkWNU9U1n42h8Rr+IXAN8BtiOcan8tqpGkwNs4DuO6+8VwMeA54GzVXWOiAzDDPKT8aVuIyvNEHF4RUSewLjwgVmpfEVMLNVOZ1/yc/18hs81l3sDoI+IjFMn/tX5PPq4judktPhcR0MY19D/+oqtd+p6BHheRGoAf0zitcADIrIRszI2xLlWRGQyxgCpFG+cXwUuowRAHTfD9hCRczH31QTM/XSEqm4VE0e3CLiFLPe+Q7tlVPUrzsu/icgzQIWqvu/vj6r+1OlXmbNd7y+DceN8BhOL+y/MgPKzruPXYLwavgb8HHN/XR5QTy7fHzDfzSWY1e6fYYw2/+TOtcD3gYdVdaGIjCPlpgzme/Flp29g3qe/uisQkXuAa9SJ9XXcRn/vMzAtll6FiPRR1QZV/ZOINGHi+yYDA0Tk85hn3BbMuGuJiNxkB8SW3ogzSZhwxnUXAH8DPgKsFZE3ML9LBZjJ4xUi8mt7r/ccpDd9FiIyGthPVV9wBmxhVa3rQD3nY+JKAF5X1Yd9x8dhYtKOxhgiHwKXqupqV5l/Yh7qC3GJsrgHLyJyFsa4GokZWFYAP81hpTCozznVtbvvkWNwNGN+pC4BKjFxbNXO8bvaOV07OnhzVpjQDIqszmpQ8jN7TVXn+o7XYYyYFowhlBZz6NRxp3NNgvlsP+deiRORn2JiwNKEU0RkiqouFpFXMXF8D6hqk6/MZWri8nK9bsEYe8c4u94EHsznIZnHvfFRzH29CnP9o4GrVPXZgDrHkMFoEZETXJsxYI2qrm+nfydg3vNn1BfTJiIFmBg0cKnMOobaeRh3avd11AH3qepbrjoqMUbS8c6uNoEgV5m7MZ9rkJDRKar6YrZ73ymb7fvxceClZNuO8Xui+pTOxMS+/YOUgb4d+IyqLvSV64+JjxTgHVXd7u9/LmT7/jhl5qrqwSLyvqoe6Hw2r6vqkQFl2zNYs/Vlrm/lPXCfxdJbcJ7Bn8Q8D+/GxEafjnF/ewgzTgDjFj8U8yxauaf7abHsLs5v3JcxInSvOxMdYzChJGOAczFjiwlALcbVf1H39NYSRK8x/ETkSkxMTj9VHS9G0e5vqnpKnvWMBTaparOzXYKJsVodULYPxjU0zXASkaWq6nddyxsxwhzfId29Kmh1KFtd7b5HEixysgvjrvgLzSIw42urbeXMvy9DO22oVwDnBuC3vtn/b6rqD311d1rKi+TqoqaLsnRaW87Km/8z/VnmM9qt60iMQTcFsyocBupVtbLdE4PrKsJMWICJPWsRkcmOK2agJL/PMA4DL2RbZXNWJYPqWis5KnY69RylqkGuku62HsQIBCVXsS4Dpqvq+fn0uTMQkXmqepBvX5Ch8xZwnaq+7GyfCNygqke7ygQakRhD8lrJINqjjliPr72s97SIvKeqR4jIa8BXMK7O76lLjVZEpmFWEPthjNFtuAxWSVe0TbblrmO+cw01znY/4FVVnebvt8XS0xGRqRjPn09jYqnLMJOPP8d4hVwB/Dzbc8xi6emICdf4LybGuwX4C2Zi9i+YkIU7gTdU9cfd1klLVnqTq+f/wwiuvAttMVaDOlDPA5iVvCRxZ1+bUmGOxshbIrJ/ezMZ0o7SpKvYvzCCG2dh3CIvxwymknV8R1V/KyK3EDzI+5prM9t79LRzvf92tj+FWZLfDGwREX88pLudCt+uW0iPvUruO8vVH0i5d14acA1nqKPI6rRTIyJnAm3vtXhTXsRJKaZ5Ul5I9vQBRZjVtTFARJwYTrdBJiZW6noC0mu0Y9B6FF1F5G+Y9/UkjLvoBfhUSF3t5aKO+mfMZ/UAxn30M6RyMSZXqG/GqD8mMO6ZX9fglCaHkrofpzvvwXGY+/T3AeU9LqpqFCkTIlKZyXB2eNI5VzCfx1iMINJUclDsTN73wMVi4kS9hbz3/XhV/YRr+6ciMi/XPovIG6p6rLNqnOxz239VrXAdSzsd7+fljxeG4Odsn6TR5/Qx6d7r5ifq8kZQ1Z1ilFe/4Oz6XUC96R3M8fsD3Op8h36E+TEvwwgKufk7RoTGbbDeRuqZmoui7e8xaXeS7s0XYgSULJbeSB/gaec78bKYEIKzMRM71zkTNn8SkzblDUgpIVosvYwCjHfKu86k8QWY5/lXVPXnYpSbHxKRiHtcZ+lZ9CbDr0VVW5ODdRGJ0LEA6Yjb3cyp0x9bl9UYwbhfzRORDzEzH2npHDDpC14HXiDzICibaEsyxsYvwhJEtvfoVFV1G2sLRGSOqh4iIpeq6jQR+TkmnvEfpNzZhiZPECPscDQwULz5vypwRB40s5jKdyVdTCUsRvyjxTmnBKN+5uYasqS8kNzSBzyKWeGcTWaJ7WvbaeusgH1BHO24yr2vqj8Vkd+THkea5LeYGMF2hXJUdYWIhFU1DtwlInMxsVZgDPm/YMRKwBiJ/wFmuOsQkX8A4zHvT/J+VFW90nmR64pYPebeeR5vfNvXXK89qzfOauJXnGM/cf5f0U4b+dz3uQgEZeyzqh7rvM6Y1qC9Yz5micgfMJ8HmMmP2QHlVonIj/BOivgN9UAjUlWT9fXH5CbMJhef9fsDoKq3Oy9fBdJyTjpkM1h3qWqmez15zr1iRIWS383z25tAs1h6IiJSrMZzaCVwhIh8WlX/o6pvifkRvlBEDlfV25ztNdbgs/RGXGO0NZjf5hNF5FVVXS0i3wQeEZFqVf0/x1PF0oPpTYbfqyLyA6BERE7DDCIf70A920TkHHXin8TEEvnjZnIxRj6aQ1sZlSZdtCvMoaqPO/+DxBj8ZHuPwiJyhKq+ByAih5NS5Euqlp6jqtNd5/zVcc1KzvwXYlYCInjVCGsxK1tuRLKIqWBWPF+UVOzgFaQLT6zDGGztcQ1m1fYdVT1JjDiIfxVhhKpm+9wytqW5J0xPGh2NYgRfqnEZzz5yUUdtdCYn5onIbzGGuft9LFVvXOE/ReTbAfUcBuzvH3xIBpfLJOoV7AETs+Lf1y5qxG9mOO1lTRie533vFggSYAfpAkE59dkxUI/FTJi8oQGxcE65TEner8asmN3vbD9PauXbzeeAn7r69Lqzz002I/Js4I9iXDPvx8RQ+tWHIbfvT6bPZRcmRcQ8ZzubwZpV0VZE/qGql2FEdfz7LJYej4icDBwlRqCl2vlOnCsiO1X1aTUhD+diPHhmquqt3dtji6VjOOPSw0TkBlWtE5GVmAWBrSKyxDH+vgZcLkbp2uZh7eH0JsPvexj58AWYXFxPqeptHajnSxg1vj9jBonrMK5zbrIaI65VLc8A0EcuSpO/cAas3yQlzPH15EHJMfm2Q9p7hHE1TPIF4E4xwgyCMda+4MzY/8op0yAil2By2CkmbsG9QpJclbw7B0Po8057HjEVX/9/IyLvY5KAg4mF8IuN5JLyIpf0AW+JyDR1kktnIGtbEhxz1+By93vCce+5EZPYXDHucEHkoo56GcbQ+yrm3hgJfEJMbBTA0yLyPVKf2UWYz97PBxjlTL9CbdLlchBmNfclZ/skTH5Ej8Gkqvc4kyGjNIOirs+ICGFcgDc62zknDJcsyemd1/MwbqsZBYJyMSBF5McYt8Pk9d4tIg+o6i9cZdpN4K6qDfjSgwShJr7ta1mKtWtEqkkQXwCcgfme/kVMypEv+OrJNWXMYc5fcrLoLEwqhi8578NvyW6wznDV1dYU3pX3qa7XyfhDd3oOi6XHIkYk6wbgWuf7DkaUaxBwiYgMcCbilgCHi0ih+kStLJbegHOv/xITOhIFUNU/ihHB+yZGlft5jCfRQMxvfSJTfZaeQW8Sd7lGVW/Oti+P+tpVpXNu+FOdzef9xkimAaCqTnWVyUVpMukukqmfSQXF8zGD9mR+rE9jVou+HnhiO0g74iaSUmc6BjNgexPzA7faV+5lgmMO00Rp2msvx/7+JGi/OpL4TpmHMQb6tZhBZg1QoKpnusoswihNZXTPzbGtWQTE3Knq9/3niYkrLM507RKskqrqxIE6g+J7VfWSgHM/JBWLFlTHOF/5lzE5797DawCc4xx/DrhcVTc520OBu1X1dF89Z2PiywpVdayIHIRR0TzHVcb9PsYw+X0ebO9eD8Lp0/3At3DFwKrqd3NZOXTVsx9mcsNvQLpFR5ZiRGHcwk/z1CXi5Kx+n4wRizlYRE7CrHrVaQ6CK3lO5OSEY/x9FHP/H6+qA3zHs97TTrnXgDOTz0TnGfmkU/dsVd0/37756v8+Js9lCSa/avK+bQVuDfr+WCw9CTFqvLOBT6rqo87EVBgzltrkrPL91ilzAiZsJE0Z2WLp6YgRLXoY+LWq3ikm/nsC5vd3tYhcitEV2B+zYPF5tblYewW9yfCbo974tEC1vHbOv1RV/5lpsOif/ZYsaREyDQBV9fPkgYiswIguvO78vZHBIJul3uTbafskXVEvadi4B7edojYpRh4+STFGNCWmToJzp4xHTMXdnqQLarSdRrq4Sb59C0wf4HymaeSwcumvf5aqHiaO7L2zr+1eFJPj5iu4XAaBv+Zr9LjaewM4eXdnjcWbhqENTSV4X6yqU1zlQxgp5inu8iIyG3Pvv+K65g9U9YA8+5MUpTkS8z6lidKIyGxVPdT3Xs9U1cNdBs0kjJtvMu3D2Rg1yktd9byBETj5o3P8Coxi749dZV4GPq4pUacq4CH3ZIbrs58PHKwm4f18TFqQ2Tm8xzlP5IjIRIzBOwbv9+dk5/gZmNXdE4FXMGprz2mwu2dWRGQJME1TKTWKgPmqOllSqR6yqhBne8aIyK+skWfpjYhRBf8exp38P5jJ3w2YVfcvq+pDzgB5CLAzOYlmsfQ2xOSy/gXwHCbX9E8wYSvqbH/TKToWM/G5pTv6acmfHu/qKUbR72JgrIi483mVYx6+uZIUIMjqZiautAiYJezhmASV7tQRUTW+/SExfs0vi8hNzvk5y+Or6gQx0vfHYaSf/yImTuAgf/+l/eTbkEVRT3JQm3SMls+TPnDzu2j6BSveFBG/cmVGMRXNQVDD1ad2B5vOqthCVZ3s7H81qB7NwT03l4Et2WPu7sXkm7vF2b4YExN1YUB7I5xyyTx+r2OSW7vz4q3CvL+P4XW7/YNTh99VOXn8Xt924Pvi4kUReRYzoAFjVLwQUC6qqrtEPAuNHveODCtbydQhf3eM4FxEaTLGwGoqCfprwCHJiRkRuR6zUuWmRE2uPnHug+sdA/bHklLM3QUsFOO6osBppKux7pSABO7J70O299hlAP7eN5HzuJiVZDcPYJ47txMsDvUZzGroVdqOwEuO9zQYF/d3ReRRZ/ts4N9iXMEXucq0p0Kci6Ltdc5s8Vg1SnAjgaHqxB5bLD0VNQmrb8S4ac/GKNze4kzC/EtEVjgrfDXd2lGLZTdwfidXihH7+y5mYvUmVb1VRKZgNB9mqMmnu6I7+2rJnx5v+GFijDYBA/DKzddh4k9yQlX/7vz/qf+YpKt65pI6InAA6Bz7BsZwzCqP7wz8j8EYftMxiV7fCDjv65g4HU/ybV+ZbIp6uahNJmMTTgd+hgniTRMfkVR8GRij51DMKpubXMRU/PVWAf9PVX/p2t3uYFONXP9SERml7QQWS5b4rFzacgiKuXMLpBzgc4t7WYybaRB3YQygpFF4qbPvNFeZlc5fiOCJi8Ndr4sxExRzMAZoG5IlNlFVvypGkSuZCP1WdaUTcLFQRC7GiAXthxkEveUrswrj8+82IuswaShuw7yHuYjStBsD6zAY4y6YpNXZ56bFWcFcLiZlxwaMSBGklENnY1xbkrxCOudiErh/nVQCd/dqVlaXUodcJnJiqvrXgD4k60xLc5GBXO5pHCPsaVKTEF9S1eR7k3Q1zqZCnMsz5i+YiYKTMbnO6p19h2Ox9FDEUVVWo7D8O+BFVX0UQFWfFpH/YeObLHsBqqrOgsYiEfklJgTiAefYYmfS1/97ZektqOo+9YcZzI1xbR+OcWdyl3nX+T/X+R8B3veV6YMZOEcwA6mvYQZF+fYngTEwz82hbBHGOJwOFAUc/zVGUOQojJjGIZiVEP91vYMxfoqAFb46ktf8vvO/AKOU6W/rQ8zg/kNgOcYd4FhfmVsxrmNB1zLSOf4ERnSmD8Yo2wbc7Cs7290n5/VMX5nXMIbFixiXv8eAx3xl5mMk8JPXeBJwRwfauibgeq5xvf4ncKRrewYmTi/ofZiXy74876kqjJurf/8sjI/+XOfevQL4la/MYMxKz1nAoAz1l2ICvmc6f7/AxDG6y8wMOG+m838JZtXuNxi3qTEYI/w7/v7keL3XOZ/t9c7fPOAHvjKHYwy9ERjD+iH3Z9SBNiuca+gH9HPtfwNjeL/vXNP1mPhH//kfxbjLvIJJn7AaON1X5nqMy/DQDG0d6bz/9RhjNw7UBrSV9Z529o0K+vOVecf5/yzGQ+FgYKXreC7PmDnO/7muffP9/bF/9q+n/GFCPZLPx5OS+0iFy1zsPINGdHdf7Z/9250/TAiEf5+4Xn8cM0k6urv7av869tcbVvyAnJQUc+VXwDMi8ieMC+cZmAGwm1clS+oITal5QXr6AXe/jyY9Rse9EnMwJhbsYjHKjMuBV1X1joDq0pJv++rKpqiXi9pk0rVup5hA9s0YtTIPqjo2oH9+jgU+K8G5Du/FDHgfxAyCZ2EG7NNUdXOGPgWmvHD4UQ79yeiem2dbl2Ni09x81rXvUIyCaHL1cRSwVJwE8OrN9VjtuL0lV8Y+jfGjb0PyENJxaCBDHjZtJx+giHwSc2+8gvmsbhGRb6vq/5zjxZgVowkY5dijNHM8WZl7BdZxZ06usI3FfN5JX1H3yrUC33e5Xwai3pyBvxSRZzD3G8AV6kvDoKrJVal60r/vOH08C7MC5Y+RdYsxXYVRtWzGTNqI08/k+53RpdTXn2ec1cHJzq4lmu6uebnz370K6m7rzwSIDAVcWi73NBj32OR7XoL5nJbiXREPWoG91nU86BnjVhYGiDru2WZEYVxR7UqJpUeSfF46LskPAt8RkVJVbRSRiJh0ONdhBF/Wt1+bxdLzcH6vFEBN3Hol5nfmKxhRtmeccldi1KYv1jy1ESw9h94k7pKzkmIOdZ2IkUbfjhFo2Ow7HsLEuX0EM7B7FrhdXW+W87D/DcYoEoIHiZkSZntk3B2X0WMx7p6XOoVG+8rkVFeuSAa1STGJ0B8EDsSsjJQBP1bVv/nKFWDypyXdAl/BxG5FXWU815BEVdeIyHx15QsUkfWY1YW0AaAzIH8ds0qYHGz+VJ1cjHlc8wvAeRjjfwDG3fNwVT06l7YkFW96rFMmSTmQUNVT2rtu9/W72hvttHMUZiD8FvA1dbmsShYhHfHG04Uwbob/VVVPWgExsXCnYgbimzEu1J9Nfg5iREpOU9WtzvZAjHhR8vj9GCPidcyEyWpVvTboGkXkTEx82krMd2Ms5kfkFeBKVb2pvfdIRC53bf4UE1jehgakZ5DMufVyijkUI7R0PrDA/V33tbEcY/D6c38mj7+FuT/+h0mLsQGjiuZPLZJUCPS7hN7rL5cJySIy5CrXoe+PmBjlr2h6egh/uWuDPs92njGXYFx/D8FMml0A/FAdVyKLpafgMvpGYMSTfo/xmPgRRqF2M2bicomqfth9PbVYdh8xgmsjMPf505hJ2atU9RHn+FSgVVWXd1snLbtNrzL8chnk5FDPj4BPYmLwDsTE6nxTVZ/0lcuWp2wFcLa2k3xbRBYTkDDbf10Yd6i3cJQ9g2ZS2qtLclQslU5UmxSR2zFuoMkB+GVAPGiQGDQgd4yME0mt+rzs3lbVnIR7JF0VtO0Q6YZ4H8xKjZCKz/qXqlYHnB/U1miMAfMrvLna6jBudDFf+YyGyO4iRkjnYozrkXvlPoa5vk2qujKg/1sxn9vXMdf/f6q6wjm+QFWnucqHMC540/zHRSSCUc4MFDByyhSRWtFa6r/PJEdRmmzfc0mP3RyFGYi5U6vcTHrMYS3m3qlQ1cucldVTgiYfXPU8A5yvqo0Zjh+OiRutwqweVgK/VdV3fOV+grnf98fkXDwDo+h7ga9cRuMwmyHfGfjviQxl1uJd9UtDvXkpEZHJGJdYwcRKZXyOWizdQXIVxFnp+y9mFXsuJg74x/lOPFosPRkxomgHYUIQXsWE8twBXKhG6KVtVdDSu+k1rp5kV1LMlf7AEaraBLztDORux6UC6Awkb8S4lI6VgDxlGOn1bIOVTAmz3ZyhqmlCC3nWlatiaVa1SWknBYOvrsN9A8yXHGOujYAB+WhSYiqVGD9xtzRkUu1UgXG5uPtpDqqgrvJZ3XPFiGxcTfr1n+MY5Gswq3MZyXLdyTI5uzJKZiGdm4Dvqy8hvYhMc46d7d7vmlBowqyi+XlG0lU93Yng21ZzVTUmXlXPIPbDpFooJtg1OSdRGtp5nxx+jol38+fWc3O0qrrbe1xSaSEWOvu+AzwlIq+SOdH59zFuvO/6ynzN+Z/VpdThAkys7lw1idgHk0rtAGQ2Dkm9P5dhXN7dIkOfcJ2f8z3mlHdPHIUwK3Ib27mGtlPx3Wv+pkglfE+2vQRYIiJftEafpafgMvZCalze+mO+b8mVvgeAH6nq43YgbNnLeArj7bVBVXeIyK8wCwMrwcyid2vvLJ1GbzL8sikp5oSaJMslIjJJVZc6g+HTfMV+glH1fMU5Z55jELiZ5bi+PYJ3APiQy62sHFjkrM54EmYnV+mAy4IG0L7BJhjXxMC6tB3FUh+5qE1mTMHgIy4i45MPBcdFwC85n3FArqpjsvQVUmqLu0U+q4KYz/MOTEynP0VBrvXkYoi4ry3NldHHbKddwazofYhxRf6j3+jDdGSBiIxx9XtBhn4nyx/o/P+2GBfmZKycX9VzuojUJqvFxMDWEry6ms1oQVWvdvdDTGzYfZn62Q65xG62F3OYVAT9JcZgK8ZM+gTxd4wL5wIC4tJE5DBMvE8yThBIvccumpyBZUxEKjATBCN9Zdo1DnMw5PP9/rgnUWKYybAHczhPVbU9I7c9voQRebJYuh3X4HYKRmG7FOPdsQXz2/AjVX3cV9Zi6fWoK52O49EzFq/KtWUvoTcZfuep6s0YV71k/q5rSBfZaBcRORv4He2v5gXlKfM/5CuARkwcoLvMQxhFycF448DAxPAlV+xyzivocH22ApI9IfYcETky6XYmIjNIHxzmmoLh2xjDMVn3GNJXOHIZkLv7f72qXp/cVl8cl5hYSFS1Pof+tZHPqiDQrKp/2s16sl63+9rExEhlFAjSDEI6jqGUiRLX67Ny6zZgXI7jGKPGLdOPqobzqCfrilYADZgfG7+RXeozOP3G+k7JnFolyTeBN0TEE3Moxv03+d4P0+xJ6AtUNdCl2uFfmO9GoGHoYpbz+d2GMezrMd9XN4HGYR6G/D0AInKh+uLnRCQtpySwKEO5B7JMepRIju7mGc63WHoMIvI54PMicpqqrhORTRj3/h+o6lNZTrdY9gZ+h/mdtblV90J6k+GXTUkxV64nfTXPr4CYS56y21X1TfcOEUnmvzqXYBe8HcANmBQCua7S4ZR7NYdigQmxRaQUM2grIF1tcomvjrdEZFrQSpJzDYcD69QoF+6HCf49D5POYb6veC4DcjfnEGDgiolz+gdGiVBEZBvwGVVd6C/bHj6XySR16hKkAW52Vquew7uyOiftzMwkr/t1crvuTEIi2Va0Z4nIlarqUWYVI9Azu63ydDGZ/VT1BTFxrBHfeT/GrGglVT1/pqp3ZulHEFlXtMQruBLGzLL/1+lzPsb6uZhVr8Dcek59T4lXRdMdc3iT8/8pEfmIqj7XTltPi8gXMSvC7vsjGZO6TXOI/VHVrzgv/ybG3bxCTeJnN5mMw+uz1e/j+xgXtQ7vy/Z5iFE7hdwnspK05yJqsewxku6dmJCK36gTx6vGrf16VW2w7p2WfYT/w3iZub8Xlr2EHi/uIpmVFCswYiKn5FnfO6p6pLgEI8QlGONsl2LctZKrec8Cv3ANFBGROeoTtkjuEyd2KEP7fgGNYozb3lS8Ag6fc47nI17iuQ5n33yMQZURn2GwCCPXH5SCARGZA5yqxgf8eIxr3tWYoOAp6hKnkDzFVCSDiIcYpcTrVPVlZ/tE4AZ1qXHmgoisxhgfNU6fqjCiGFswSpOzxfi1X4ZRo0w+7FQzp04IaqeU1HVfirlX/6UZBGuC7iVn/13Oy0HA0RiDDOAkzETE5zGuGK2kDL3DMKvZH9d0tdorMaJG/VR1vGMI/U1TaqRLMbFw1c52f+AtDVCkzOE9+D+M6t2nMKtt9Zj8hFe4ypzgOiUGrNEOyKE7q0z3q+qGLOXaTa3ifNf6YO77KMHfsSDlPlUnQbuInIJJyfEiPhdwX1+OJwBVfc05LpjV93XO9hh8xqHz/Uoa2BMxRu3TyYkMETkDOBMjZnW/q5kKjFDUEfmU210yrQYmaWdV0GLZIziTwHcA31LV2a59azVz6hqLZa/DGnx7L71hxe8tjHvkAEyAdZI6TJLkfGl3NU9MfqknVfUkjPHnQUSOwgzCB/oGMhWYVQswBkUmSnzb/8Csup2OWaW4BCMEAuS98vG0mFyA92GMxaQ4R51T1w4RmY5xOQWjIOpfpTsjSxthlwFzESYO7EHgQRGZ5y6oOeY6dJFJIbJP0uhz6n3FGfTmy/PA/1T1WQAR+QhGDOMuzAzXDIzQzThVbc1YSwYyGOlJV7YfO26G1zmrpVldGZNGkog8hxmAb3K2hwJ3q+oW4GgxMYRJF8UnVTVpIPr5f5jV7ncxjSwXozyapBrnXnGow5dTMBcco+VXqrqTdla0VPVVERni9EkxxnZHKAeec1bU78esUG3x9SkwHQremMOs3zXNnr/yCowBVoBr4gCfuAne3HzFmPdgNk7OTVVVEXkKmOZsrw5o6zXgOBHpi1mhnon5Tl7iHN+IceU+B9cKMOZz/bprO9dyWckykZXvaqDFskdwnlkRzPfyToyI3FSMi+cajNhbp6kyWyw9HWv07b30eMNPfUqKzirE8UB9B2fgrsYYdC0Y9cJnMWIcyfbiIpIQkUr15Z9yKMSIQkTwDmRqMXFNkIMLnohEnP5PUNULReRcVb1HRP5NemxgrnzS+X+Vb/+nABUjaX8lqUHoP0XkVlVNqny2rf6JLxWBi7Cr76dgVpCSRJxzk0aN4DWEglZQKjGua8c5269iYi7d7/0qMWk4/uFsX4qRGs6XI1X1yuSGqj4nIr9T1avEqJmCUU+twrgm5kV7hoMzoXAAJgbsgDwN+pFJo89hC8ZNN9nuy5h0GNloUdVWcWJXxQRwq2sCYwXwrog8ivnczqUDkys5Gi2d5lqqxl36pyJyIMbweVVE1qvqqa5ih5E9tUq7q3BOmVLgG5hUL190Jo8mqeoTTpHDc1khVVWPi6MYyfibfMXmiMjhmlIKTeuymiTSn8ek5fite/LFmdSZ7zxThFRy96Xqcm9W1fki8gFwurYTa5oj7U1kPdXOtVgs3YbzXIiKSDlGjflFzETKfODXGFdyi8Vi6fX0eMNPRJ4AvqeqHzgrHXMws9PjHaPlpnzqU+O3fx0Bq3ku6oEFIvI8rtgsNekDXsUMLO9Wk4i8VNNzel0LPCwmUXGaC56z/R5mhSs5ANspJpZtM8a1L2+yrUaIyPvAjORKnIj8BhMzdIurTLZUBP/BXP92zI/h6855EzBqoPmuUt6JMbaSRutlmBU4d3zb5zCCPg9hDJLXnX35sklEvktKOfIiYItjlCVnt6owMvMz8amndqC9NlQ1jhmE35K1cDovSnqahRc6UM+rIvIDjBjHaZicjo+TmsBYiXfV7dEOtJEkm9ECZnb9YL9rKeae6AhbMd+fatK/Q7mkVml3Fc7hLmdf0s14AyYuLmn4vSUi+6uqXy03G+sxMY5uZgCXinFRbsDndo1ZqDgKY1x93tkXJMBzNGZlc7VTx0gRudxt0DoTXiNFpLAjq90u2pvIulVM7Ot9wH868B5ZLF2GiEzCeHwI8FvgefXGf1ssFkuvp8cbfsBYVf3AeX0F5mH8GWdm7k3SZ8kDEZF2BRd8A/uHSK2KJVcI/Opzw0Tkaczq3yjHhfIqVf1Kni54tzquWj/EqIGWAT/K5Zr8SHqC9tcxMVzJ2ETBm3IhHnBd7aYiUNVfisiLwFDgOdcKSgizmprsSxhYqKqTaZ/xqvoJ1/ZPk6sWzvV8CRNzuAD45m7+EF+MSZvwiLP9prMvTMrwbC+twm6jjqhPnud8VYzQS9JF159mIVe+C3wB815ehXEDvr29VbDdYAZwiYisIdhogc5zLf0K5vMbiDHCrgwwKjKmQ3G9zmUVbryqXiQm9hhnxc39HToS4yYWGCPrqtudYy+EiZGd4xxLpp04PculX4sRX3lYVReKiUUKWvn9A/ARVV3q1D8RM4lwqK/ch8CbzrPSPeGVT+xdxoks53kyCeOB8D8RiTr9uC/TqrDFsqdQ1aUiMhCIuSdzRaygi8Vi2XvoDYafe6B/CkbhDlWtE5F8fJCPAtZhBhrvEiAjLiLnYgQV/uJsv4cZTCpm0OzmJszA7DGnP/P9rmJZXPAGuVzskoIXf3H+dyR+DTIkaBeRBlX9LGa14l0RSRoN52EC2d3kkorgHX/DqrrMtx0XkaWuQWwmmkTkWFV9A9qUUZNuNfdgPv/XMbGHUzCD3Q6hqttxGac+VjjG6t9zMFb3OGrEQfxxYjnjM8Rvy1Am1xx0uZDNaIEMrqXJ70UeBsdI4FpVnddOmetzrMtN0Cpcqxg1VAUQkfF4813mkgoFvGlUYpgVsKRK8CPAIY5HwYO+iZE2XN4HZSJSpiZty9cCihYkjT7nvGUiUhBQLrniG6Lj8XjJiawfkZrI+rGr7aWY1fufOpNln8KsaG9W1WOCKrRY9hSqWhuwzxp9Fotlr6E3GH7rRORqzCDsEOAZAGfwFTR4ycQQTKL2pErok5jBljslwHcwA5EkhZhZ8TKM0eSROleT48e9y5/AvD3CTr1Beaw6+kOTKUF7M5iBtIi8QipB9xWqOtdXR74pGNqjL0ZM5z28Kwju1dUvAfeKifUDo7h5ufN6f3UUUEXkDox7bIdxVjq+RbqyY1JQI1djdY/irPb9BrNyIgTESmYjx2vLNQddLu1lixWFzK6lORkdkkrPcaNvO9mHHa7XWdOhtLcK5+J6zDNopIj8CzgGV/7KHK8b4H+YnJFxp3zY5Tbufib4U824+zsNM9mTLc3JLBG5nVQexUsISO6uTmoZ6WC+TOec252Xr2bpewhzPw/GTHTlHVNrsVgsFoslP3qD4fd5jEjAqcBFapQCwbhU3ZXpJD/OAOsZ4BkxQh6fBl4RkZ+q6p+dYoXqyKc7vOEMHndIuorkOjHy8OrMnl+DS40zBzap6s+yF8uLTAnajxCRg0kNKN9w/ouIHKKqc8TE6A0mPSfaaDKvkmUjF5fVWlWdLibXG6paKyLJWEW3AEXMZ2R3hAeAvwG3k9lIz8VY3dP8FjhbVfO5v4LIdm055aDLBckeK+o2NILiZHNhNpldsRWX4SFeFdVCzKRRg894bm8VLtnn50RkNub5I8A1zkpysp2s1+3wIuaZljSuSjDKnEfjnfhpbxLo78A31Jvm5DZS8YdJvoxRdE2uBr6OUbH1IN58mYiJ480rX6bzbP0E6ZMrP3OOH4d59p6HmWC4D/i6BgtpWSwWi8Vi6UR6fB6/IERkiPpylOV4XhHwMczAYwzGFelOdfJ/icgKVZ2Q4dyVqjretT0Akzz+VMwA8DnMIDCnGCXJkLNudxCRxcAkUrLTo4ClGDW/JoxKmR9V1ZPFiOgEJZ2fhsmZ16FEy+JNGF6KSQdR5zoelA9xtqoeKiJxUgaKYAbHyRWRvFa83PVmKXNC0P5cVoy6ChF5szPc4LJdm+SYgy7HtuZjRFE8saKq+nlXmaMwrsZlquqJk823vTz7JpgJjiNV9Xt5nvui+nKHuvflct1OuXmqelDQPtd9777nwXffi8h8VZ3uqyNoXx98q4tAkd/Ylk7IlykmdccujFHeNrmiqr8XkXUYheb7gP+qql3ls1gsFotlD9IbVvyCeIrMOd8CEZF7MUIrTwE/1ZRgjJt3JTgNw1X43AydWf5L6Dh5JZ7PkUzxRU8CH1NXovYABvuNPgBVXSAmeXTeiCthOCaH2nDMitspIjIZswpS6bgyJqnAcZFT1SCFwt3hcTFCIA/jNWw8LoFBxmon9yNfZonI/ZjYrw4bZDkYr7nmoMuFrLGi5BAnmytOXNl+eHPHvRZU1onZeUREfgJ8T0QWELyy1ibMIkZoqBQY4LSVXGGswNzXSXK5boCG5Gq70/9DcWJb87jvc01z0t7qopvOyJc5QlUzPYeO9T+DnPdyp42jslgsFoul6+mthl9HfP4uxcyiXwN8zeU26J5F/zpmQHgxqdieQ4EijGsSIvIdNfmy3PFAbahqkLhCGm5jY3cRkQo1Qel1GYpEsxh9kF/S+VxpL2H4JOAsp133amIdJtdgV5CMHXTL9vtdAjMaq13Up1yowKz6fMS1L2eDTIITy0P6ymlOOehyJKdYUd29OFmgLR/gNcAITIL2IzFpSk52lXFPLoQw6VWSardn5dDMVRhhoWGY1axkp2uBP7vKJa/7ddqPkb0WeEBENjp1DcEbX5wL7jQnkDnNSbE7Xk9V650JDT+dkS/zLRGZFjSJBFwuIv9V1SWO98UzwHQgJiIXq2pHUpRYLBaLxWLJkd5q+AWqEraHqoZyKLMVk4bhZFIxOf40DF9yXKLSxBG6kX9jBq/JmCf3SFoxAiqBiEh/xz01a9L5DhCYMBxAVR913Eu/q6o3dLD+vNAseQ4d2jNWuwVVvSJ7qXbPz1WhsaM56ILwx4pWYmJ13exunGySa4DDgXdU9SRnNdl/T7knF2KYnHbnQkqQBUBEBjt1AbyXdEdU1ZuBm0XkalVtLxfjORiD8hqM4VSBMc48qOpMp59JQ9uTVD0XVLWGYBVPP/7VxcMITkjd4XyZYhLAJzC/KVeIyCrS01lchEkXA6lJmIEYV/R76FhuSovFYrFYLDnS42P8xKfU56czV85yQUSuxQxghgL/xQhA+JUxezQishLj/vlP4G5V3d8Z8D4MtBKQdL6DMZW/BXYCn8EIxHwFWKSq17nKvKeqR+zG5eTSj++o6m+d1xeq6gOuYzeo6g9c2++q6oxkDKZjrM7RjqU06BREZAQmRUcyzu91TDzp+k5uZzFmlbPdHHQ51jUWI2DU7GyXYNyJV7vKBMXJfi3f77SIzFTVw8Xkf5yhqi0islBV/YIq2er5JEYh9BWnP8cB31bV//nKHQDsj1e18y+kr6omJ2CaMeql1wGH5nov5tDfxwPa3IWZlPq7670/HBNXt9EpMxQjlDXbOe7Pl3lnvkaoiNRgVFADUZOaYq46cc0i8iAmD+jfne20WF+LxWKxWCydS28w/D4ktYo1CiP3LxgXwbU5ruJ0Rb9GY1yzPoVxhfw3xghc3g19aXfAlJzp953zdeB3mJQO97r2u5POL9TgpPO59iuEUWX9COYzexZfwnAR+SMmpux+vEqTaX3ejX60DSr9A8yA7azG6p5GRJ7H3F9uF7xLVPW0Tm5ndND+HNyEg+qaBRytqq3OdiHwpqoe3s45fYGvqOov82zrYUx84rUY984aTO66MzO5ZCdxu2aLEWY5LbnKJyaZ8wvqEktx4gJPxBh+T2HyS76hqhe0078w5jv1L6A113sxh+u+GbNi9h9n10UY11PFrDT+CVinqpudFdWrgPOBRcCPkwa2Ez/qzpe5WlWvzbUfufZdRN4BvgBswYhOHaqqHzrHlmgPzJ9psVgsFsveRI83/JKIyG3Aw6r6lLN9BnCeql7VvT0DMakS7gQOzEOYoTPbz5QkHswgMAZcqakcY0diXKtuBD6iqp/s+l4Gk6Hvqk5uvU5qw73S0PY6w7bbWAV4VlO5yboFaUcBsova8+Sg0w7kNMzQ5/lqUneMxKT6GIZZZb4P42L4GczkyTW70fcTMG6lzzhuxpe7Dv8U+Im7vKre4zp3gTp5I53tEDDft28BJi5trnMtg4F/5mKEixGJ+lKu92IO9c30G9Ku1c+FmFXbU1V1hxjRnPswkxkHAVOSxqr7up0V7vfyXX0TkfXAHzIdV5ND9EjgboyxepOq/tw590zgMlX9dD5tWiwWi8ViyY/eFON3pKq2iX6o6tPO6ky34AyQzsCs+J2CcQ+7vjv6oqontXfcGYQnjb6PYQy+s1V1mTMY7RJE5BjMezIac68lXQfbxFSy9b2TaC8vmgKIyLkYRcK/ALeJEXkZCBwqIjv97n57mGoRuZTUys6ngZzShuSD5J6DLhe2icg56uQFdN7fZL67ezEJvh/EKNHOwoiyHJiPS7EYgZJo0i1RRCZh1H7XJFcafYbdte7tAJ4RkWfxrqA95SvTpKoJEYmJyT25FRiZS39V9e++71vgvZgHZSIyKmmYi8gooMw51opJnZJ0m70IuFVVHwQedNxik3RGvsyw03bGk9XkF01b1XMm8/zvs8VisVgslk6mNxl+G0Xkh5i4NDCCERvbKd8liMhpmIH3mZgUD/cBX1TVIOW+PdWnk1X1JfEqF7ppcVY+RmJm/A9W1Y3OwDVfufZ8uAMj7uHJ6eXGWTG5ARimqmeIyP7AUap6Ryf2Y7qI1GIGpSXOa5zt5MrWd/CqKhZiFF3LgLuA7jT8PoeJ8fsjxjh4C+Pa2Nn8HKOI6clB18G6voRRtfwz5n1eh1nRA+inqtc7r58VkQsxrquJ9Gra5RnM6uxyEZmAUfL8F3CWiByh6Tn6Ag0r59zBqvpt5zt0rHMoWZ+bWSJShRGYmo1JkfB2Hn3O5V7MlW8Cb4iJ2RVgLPAVMSkY7gG+ICIRVY1hJqe+6DrX/eyf7utHiauPqrnly9ykTpL2TIjIN3y7FDMZ8EbS5dNisVgsFkvX0ZsMv09j3LQexgwYXnP27Wm+j4m3+qYaVb2ewAnAS3iVC5Moxkj+HmYV4LfAnWKUSc+lAwqpebBLVZ/OUuZujGGVjKFbhon36zTDL0f320JVXefafsNZLdkh+ecy61Sc1dpz9kBTueagy4qqrgSOFJPaAHWlE4C2eL7k6lA1Jp+jOGVzFXfp64qpvRzjJnq1E084G3PP58JNmO91MjfiQ04fpznH2r5Xmkou/zcxycorVPX9HNvp1NyUqvqUiOxHahVtqTqCLsBNzn37qohsx6h4vg5thu6uTu5TLsuEQeqyY4DrROR6Vb2vE/phsVgsFoslA70mxi+JiPTpztW1vQExYjCnYOKUOl1CXVJiM5/EuIA9hDfx+BxX2WRMkjsOr8vi1zIhIitUdUKGYytVdfye7I/Tbs7CJJ3U3guYfJW/AgZg3BgPV1V/ou/26rhUVf8ZsLoDtMV6rcZI/wcZCx5X4Cxtva+O4qiIvAncqKqPONvJeEJ3DsNSTD5EcK1mBcXKudrwx/0FJpjXDMniuxIR+UzQfvWKNR2JUfF8LvncFJGJQJl2roBSvzwM9rRzMavMVtXTYrFYLJYupNes+InJ93U7xvVulIhMB65yzcDv84hJivwJzCx622frd8FyBnydNugL4Pe+7cPczeNKrI3JMdafVKzdkbhWI/Yg70pwHsOrMC693YE7V2SaMElnkXR1JD333miMa3A+JFdHM+YOVNUx+fcykPdF5HfABkwqgucAHFfMZFu55DCsaudYiW/7267XxZicj7Px3tN7CrexWoyZzJmDiaEE2uLqPKjqss7uSEeNvuS5ydVei8VisVgsXUevWfETkXeBC4DHXCtDH6jqAe2fue/guJ7tIj2m7nraXznKJYanI/0Zp6qr2tvnrA7egpG7/wAjqHJBPu5zndTXQcAjmJXJpFF8KFCEUY/dsif74ydfxcc8634C+L6qLvDtnwbcoKpBLsSd3YfrXXF/uZ5TgkmUPhSTe26+s/9oYLyq/qO98131/Ad4KcDo/wImvcNF7Zw7EqNQ+Yl8+t4VOAbvfar60e7uSz44saQ/0k5U8rVYLBaLxZJOrzL81JVY29k3X105tvZ1shnCIvJzYBMmH5xgVnWGquqPu6g/abm9RGS2qh7q2xcBJjl9Wqp5Jo/uTETkZFIqlruVx7AzCXovO7HunF0dc6irvXtJ1ZHwDzivU65PRA7J14XRERh6GBMDO9vZfRhG4Ofj7SmNOitVC1V1/w52udMQk6vvA1Wd1N19CUJMKgz/D04/jEjXZ1R1yZ7vlcVisVgs+w69xtUTWOfM5KszwLkGIzVvSfGWiEzzr9y4OMdnKP9VTNLqTjX8RGQyxniq9CmNVuBTLgyIUzpERDxxSnsSx9DrEcbeHqSqnWN+V8dsBMXf9sGob/bHKIcG0VmufrdjUjrkjLOae7Sz8pScOHkyyOj3xV2GgIPpWrfpNETkKeD/YRK0J/sSBqYAD+zJvuTJWb5tBaptzLbFYrFYLHuG3mT4fQm4GRiOiel5DrDxfXhm0iPAFSKyCuOymBSwONAp2iAil2BSUChGFbUrBl2TMIO8KrxKo3XAlb6yWeOU9lX8wiQ+yf1cZfZzYVaG+MYvkFoBywlVbYvvFJFyzATNFZh7zh/76ebQdo7lQ4cNSFV9GXg5S7Fk3KUCMeDfqvpWR9vsIHcBz2JSNryHWamMYfIXrt/DfckZR53Wg4h8Ebi1G7pjsVgsFss+R29y9TxGVd/Mtm9fRERGt3dcU8nbx2CM52MwA9c3gWtVdXUX9esoVc0nx1mvjVPqzeyOq2OG+voB38C4Et8D3ByU+kREBmImAsbgFSP6XP5X0VbneUllz85ETAL6Ear6F2f7PUw8qgLfUdU9mufRSZPxI+CjGNftthyIqvqHPdmX3aErXZgtFovFYrF46U0rfreQ7sIVtG9fZAtmRXQCsAC4Q03SZg+OgXfuHuxXtYi8iEmOfYCIHIhxN/1FO+c0YBJRW/YQ+bg6ZkNEbgTOx6ziTFNf/j4fj2Jyy72AV4wo17aCvvtrk/s7M10B8B3gU67tQswqZRlmBW6PGn4YI70BIz5Ujsvw62VYNU+LxWKxWPYQPX7FT0SOAo4GrgX+6DpUgVmN2OfFXUTkfiCKGUSfgXH5uiagXDEm1moqrli73VlhydKvVzHy93/PpMQqIo/jjZnaH/ivquaafNvSgxCRBMbNOIZXyCPNPXV38zWKSHtumdqZKpF+ARwR+bOqftV5/Y6qHtlZbeXQl48CfwAeA36mqo1ZTumxiMiInuyearFYLBbL3kRvWPErxMyqR/DmBqvFpHewwP5J5UURuYPMeef+ASwBTgd+hnHF60qBnFJVfc+Xosu/Evk737EeHadkaR9VDeVR/AkROVNVn+pgWyd15LwO0tfX9lddmwP3YD8ArgMuVNWFe7jdTsFx5/4Mjotv8vmgql/rvl5ZLBaLxbL30+MNP1V9FXhVRO4OEgewAGa1DwBVjbWTC3mCql4oIueq6j0i8m/MKmFXsV1ExpNKzn4BJp1EcvUxq3uqZa/mGuAHItKCuYfzEq0Rke+o6m+d1xeq6gOuYzeo6g86sa/vZhDAuYrMEy1dgqoetyfb6wKeAt7BfO97q4uqxWKxWCy9jt7g6nmTql7rcwlsQ1XP6YZu9ShEJE5KnVMwEvyN+AbSIvKeqh4hIq9hFFE3A++p6rgu6tc4TKzX0UAN8CFwqaquztU91WLJhFsYxC8S0tmiISIyCHgE48aajB08FBNjd54TJ2nJASvoYrFYLBZL99DjV/ww7ongdQm0uFDVcI5FbxWRvhg1wMcwLrRdkrzd6dcq4FQR6QOEVLXOdThX91TLXoxzP+6HN+b0tVxPz/A6aHu3UNWtGAGckzExstBBARwL/xCRK4EnMIY0AKq6o/u6ZLFYLBbL3k+PN/xUdbbz/9Xu7ktvR1Vvd16+CnTJKh8EJmVP7k/2415yd0+17KU4eQKvAUYA84AjgbeBXEVZNMProO1OwTH0rLG3e7QCN2JiFZOfk9KFzySLxWKxWCy9wNUziYgcA1wPjMYYrEk3RjtYyIKIfKO9452d90tEbslw6BxguKpGcnVPtey9iMgC4HDgHVU9SEQmAzeo6vk5np+8h9z3D852saoWdEG3LbuJiKwCjlDV7d3dF4vFYrFY9iV6/IqfizuAr2MSTOed82sfJ6mGOgkz0H7M2T6bLnCxVNWrk6/FLOVdAnwXI+jwS6dMru6plr2XZlVtFhFEpEhVl4jIpFxPtvdQr2UFKSPdYrFYLBbLHqI3GX67VPXp7u5Eb0RVfwrgiLockoy1E5HrgSe7ok0RiQCfBb6FMfguUNWlXdGWpdey3pH2fwR4XkRqAKvcu/fTAMxz8jC6Y/xsOgeLxWKxWLqQ3uTq+WsgDDyEd7AwJ+NJFg8ishQ4UFVbnO0i4H1VzXmVJcd2/h8mdutF4Dequroz67fsfYjICUAl8IyqtnZ3fyxdh4hcHrRfVe/Z032xWCwWi2VfojcZfi87L5MdTsaC5SoEsc8jItcBnwQednadB/xXVW/o5HYSwFZgG16RjeRndmBntmfpnYjIkcBC1wp0BTBFVd/t3p5ZLBaLxWKx7H30eMPPJUySlH1UjEHxhqp+2D296r2IyKHAsc7ma6o6twvaGN3ecVW17nwWRGQuxvVYne0QMMvmeNu7EZH9gF8B++NN42GFuiwWi8Vi6UJ6Q4xfecC+0cB1InK9qt63pzvUm1HV2SKyDmfAJSKjVHVtJ7eRZtiJyFmq+kRntmPp9Yi6Zp5UNeHEhlr2bu4CfgL8ETgJuAIIdWuPLBaLxWLZB+jxK36ZEJF+wAt2dSB3ROQc4PfAMIwr5ihgiapObffEzml7jv2sLG5E5CHgFeCvzq6vACep6nnd1SdL1yMis1X1UBFZoKrT3Pu6u28Wi8VisezN9NpZVlXdQcr905IbP8ckyV6mqmOBUzGKm3sC+1lZ/HwJOBrYAKwHZgBf7NYeWfYELY5b73IR+aqIfBwo6+5OWSwWi8Wyt9Nr3apE5CSgprv70cuIqmq1iIREJKSqL4vITXuo7av2UDuWXoKqbgU+1d39sOxxrgFKga9hJqNOBgKVPi0Wi8VisXQePd7wE5EFeJUhAfoBG4HP7Pke9Wp2ikgZ8BrwLxHZismp1amIyPkZ9o8AUNWHOrtNS+9BRL6jqr8VkVtI/27bfG57Oao603lZj4nvs1gsFovFsgfo8YYfcJZvW4FqVe10g2Uf4FygGfg6cAkmb9rPuqCds53/gzCufC852ycBb2FyMVr2XRY7/2d1ay8s3YKTmifI4LepeSwWi8Vi6UJ6rbiLpecjIs8Bl6vqJmd7KHC3qp7evT2zWCzdhZNSJkkx/P/27j1Gr7rO4/j704JbWW2wCeIFlTULWRfTSBVvKGqNy8YI0TUb4uqy8RI1UYyoMTEaUDQaEUFDJMYYWRbXut5QK6IEL0ExSnpBiLUKkYhoLFJFK7BA69c/njPpdBjF6Jzzmznn/UpO5vn9zkzOJ+mTmefb340XAnur6s2NIkmSNAkrYcRPS6SbgvleZiNxYf+B6mt7euQj5oq+zi5mO4lKJDkaeBNwJPN+FznyM25VtXVB11VJrm4SRpKkCbHwm5azgZOq6of3+Z1L42tJvgps6tqnAFcM9Gwtf58GPgx8FNjXOIsG0h3FM2cV8Hhm084lSVKPnOo5IUmuqqrjB37mvwFP75pXVtUlQz5fy5dnt01TkhuZrfELsBe4ETirqr7dNJgkSSNn4TchST4IPAT4PHDXXL+7bKqFJG8HbgEu4cD3469bZZIkSRorC78JSXLhIt1VVS/r6XlDrynUCtKN/CxUVfXowcOod0nWAodX1fVd+9+B+3e3v1pVu5qFkyRpAiz81JskNzDsmkJJy1SSjwDfqar/7to3AJcxK/72VtWrG8aTJGn03NxlAhoemL3Lok8LJdlYVV/vRoTvxanHo3Uc8Kp57T1VdRpAEtf3SZLUMwu/aWh1YPaWJP+Hawp1oGcAXwdOWuReAb4/xumgOnCKyX/Oe33owFkkSZocp3pORJLVwHur6k0DPnPQNYWSlq8k3wdOrKpfLuh/OHBZVa1vk0ySpGlwxG8CkhxUVXuTDHqUQ1W9dMjnaWVJcihwKvc+wL2vqcdq633A5iRvBLZ3fRuAc7p7kiSpRxZ+03A1sw9Y1yT5IrODs2+fu9nX1Mska4CXA8cAa+Y9zxE/AXwZ+C5wHfCHxlnUs6r6eJJbgXcx+51QwA+AM6rqsqbhJEmaAAu/aVkD7AY2sv8A5T7XVF0M7AROBM4CXsz+9YbSmqp6Q+sQGk5VfQX4SusckiRNkWv8JiDJzcC57C/0Mu92VdW5PT13e1Udm+Taqlqf5GDgW1X15D6ep5UlyenA74Ev4QHuo5fkbcAFf+rfN8lG4JCq+tKwySRJmgZH/KZhNfAADiz45vRZ+d/Tfb0tyWOBXzI7zF0CuJvZ2q63sv99WIAHuI/TdczW+P0/sA34FbNZCEcBjwOuAN7dLJ0kSSPniN8EJNlWVRsaPPcVwGeB9cCFzIrPM6rqw0Nn0fKT5CfAE6vq1tZZNJwkRwHHAw8F7mQ2/fvKqrqzaTBJkkbOwm8C5qZcts4hzZfkcuD5VXVH6yxqI8mDgNvKP0SSJPXOqZ7T8OwhH5bkz27Y0deaQq04tzPbafYbHLjGz+McRijJGcCnqmpnkr8DLmM2xXNvkv+oqiuaBpQkaeQs/CagwWYZDxz4eVqZPt9dmoZTgHd2r/8LWAUcBhwNXMRsjZ8kSeqJhZ+WXFW9o3UGLX9VdVGS+zH74A/wo6q658/9jFa0u+dN6TwR2FRV+4AfJvFvkSRJPVvVOoDGK8kRSS5Jckt3fTbJEa1zaXlI8kzgeuBDwAXAj5Oc0DKTenVXkscmOQx4FnD5vHuHNMokSdJkWPipTxcCXwQe1l2buz4J4P3Av1TVM6rqBGajQOc1zqT+vB74DLATOK+qbgRI8lxge8NckiRNgrt6qjdJrqmqx91Xn6YpybVVtf6++iRJkvS3c12F+rQ7yUuATV37RcDuhnm0vGxJ8lHg4137xcCWhnnUo0V2+y3gVuDbc6N/kiSpP474qTdJHgWcDzyF2Ye87wCvq6qbmgbTstBt6f8a4Gld17eAC6rqrj/9U1qpkpy5SPc6ZlN8315Vnxw4kiRJk2LhJ6mZbqMPqupXrbOojSTrgCuqakPrLJIkjZlTPbXkkpzPbIRvUR7QPW1JApwJvJZug6kk+4Dzq+qsltk0vKr6dfeekCRJPXJXT/VhC7C1u06e93ru0rSdDhwPHFdV66pqHfAk4Pgkp7eNpqEleRbwm9Y5JEkaO6d6qldJtlfVsa1zaPlIsh14TlXduqD/MOBy3y/jlOQ67j0TYB3wC+DUqto5fCpJkqbDqZ7qm/+zoIUOXlj0wWydX5KDWwTSIJ63oF3A7qq6vUUYSZKmxsJP0tDu/ivvaQWrqp8u7EvySuAjDeJIkjQ5TvXUkkuyh/0jfYcAd8zdAqqq1jYJpmWh28hlsVGeAGuqylG/iUiyzd08JUkahiN+WnJV9cDWGbR8VdXq1hm0bLibpyRJA3HET5LURJIjqurm1jkkSZoCCz9J0mCSvGGR7t8CW6vqmoHjSJI0GRZ+kqTBJPkE8ARgc9f1POBa4Ejg01V1dqNokiSNmoWfJGkwSa4EnltVv+/aDwAuBf6V2ajfP7fMJ0nSWK1qHUCSNCkPBu6a174HOLyq7lzQL0mSlpC7ekqShvS/wPeSfKFrnwR8IsnfAzvaxZIkadyc6ilJGlSS44Cnds2rqmpLyzySJE2BhZ8kaVBJVgOHM2/WSVXd1C6RJEnj51RPSdJgkpwGnAnsAvYxO8S9gPUtc0mSNHaO+EmSBpPkBuBJVbW7dRZJkqbEXT0lSUP6GbMD2yVJ0oCc6ilJGtJPgG8muZR5xzdU1bntIkmSNH4WfpKkId3UXffrLkmSNADX+EmSJEnSyDniJ0nqXZIPVNXrk2xmtovnAarq5AaxJEmaDAs/SdIQLu6+ntM0hSRJE2XhJ0nqXVVt7V6uBS6tqj+0zCNJ0tR4nIMkaUinANcnOTvJP7UOI0nSVLi5iyRpUEnWAi8CXspsvd+FwKaq2tM0mCRJI+aInyRpUFX1O+AzwCeBhwIvALYlOa1pMEmSRswRP0nSYJKczGyk7x+B/wEuqqpbkhwC7KiqI1vmkyRprNzcRZI0pBcC51XVlfM7q+qOJC9vlEmSpNFzxE+SJEmSRs4RP0lS75LsYZGD24EAVVVrB44kSdKkOOInSZIkSSPnrp6SpMEkufgv6ZMkSUvLwk+SNKRj5jeSHAQ8vlEWSZImw8JPktS7JG/p1vmtT/K77toD7AK+0DieJEmj5xo/SdJgkrynqt7SOockSVNj4SdJGkySExbrX3iunyRJWloWfpKkwSTZPK+5BngisLWqNjaKJEnSJHiOnyRpMFV10vx2kkcAH2iTRpKk6XBzF0lSSzcDj2kdQpKksXPET5I0mCTnA3NrDFYBxwLb2iWSJGkaLPwkSUPaAazuXt8GbKqqq9rFkSRpGiz8JEm96w5qfzfwMuCmrvuRwMeSXF1V9zQLJ0nSBLjGT5I0hPcB64B/qKoNVbUBeDRwKHBOy2CSJE2BxzlIknqX5Hrg6FrwRyfJamBnVR3VJpkkSdPgiJ8kaQi1sOjrOvexf7MXSZLUEws/SdIQdiQ5dWFnkpcAOxvkkSRpUpzqKUnqXZKHA58D7gS2dt1PAO4PvKCqft4qmyRJU2DhJ0kaTJKNwDFdc0dVfa1lHkmSpsLCT5IkSZJGzjV+kiRJkjRyFn6SJEmSNHIWfpIkSZI0chZ+kiRJkjRyFn6SJEmSNHJ/BGlIkv0un3X+AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1080x3960 with 10 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#age vs Categorical features\n",
+    "fig,ax=plt.subplots(5,2,figsize=(15,55))\n",
+    "r=0\n",
+    "c=0\n",
+    "for i,n in enumerate(cat):\n",
+    "    if i%2==0 and i>0:\n",
+    "        r+=1\n",
+    "        c=0\n",
+    "    graph=sns.stripplot(x=n,y='age',data=df,ax=ax[r,c])\n",
+    "    if n=='native.country' or n=='occupation' or n=='education':\n",
+    "        graph.set_xticklabels(graph.get_xticklabels(),rotation = 90)\n",
+    "    else:\n",
+    "        graph.set_xticklabels(graph.get_xticklabels(),rotation = 45)\n",
+    "    if n!='education.num':\n",
+    "        graph.set(xlabel=None)\n",
+    "    c+=1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Individuals working in the government secctor have atmost age 70 to 80 with few outliers which must be the retirement age for them. There are no individuals who do not work after age of 30. There are no individuals of age >70 belonging to the pre school education category while Doctorates and proffessors appear from late 20's as they have to study for more years to get to that level of education. Same is the case with education num, as the education number increases age also is increased. There are no people after the age of 50 in the married to armed forces category with just a few outliers. Widowed category has seen increase as the age age seem to increase, there are very few widows at an early age. There are less people with high age from other races than the white race. There are more no. of working men at higher age than women. There are very few people belonging from other countries with high age."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:32.344504Z",
+     "iopub.status.busy": "2021-07-05T16:35:32.344245Z",
+     "iopub.status.idle": "2021-07-05T16:35:37.530194Z",
+     "shell.execute_reply": "2021-07-05T16:35:37.529145Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:32.344477Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x3960 with 10 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Hours per week vs categorical Feature\n",
+    "fig,ax=plt.subplots(5,2,figsize=(15,55))\n",
+    "r=0\n",
+    "c=0\n",
+    "for i,n in enumerate(cat):\n",
+    "    if i%2==0 and i>0:\n",
+    "        r+=1\n",
+    "        c=0\n",
+    "    graph=sns.violinplot(x=n,y='hours.per.week',data=df,ax=ax[r,c])\n",
+    "    if n=='native.country' or n=='occupation' or n=='education':\n",
+    "        graph.set_xticklabels(graph.get_xticklabels(),rotation = 90)\n",
+    "    else:\n",
+    "        graph.set_xticklabels(graph.get_xticklabels(),rotation = 45)\n",
+    "    if n!='education.num':\n",
+    "        graph.set(xlabel=None)\n",
+    "    c+=1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Govt employees do not work more than 80 hours a week that also with rare cases. It is seen that people with less education worl more no. hours of the week which is quite logical. No armed force person works more than 60 hours a week while farmers and transport movers has working hours mean higher than other occupation. More no, of individuals who have relationship as own child have high density for working only 20 hous a week. Female works for less no. of hours as compared to men."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:37.532653Z",
+     "iopub.status.busy": "2021-07-05T16:35:37.532050Z",
+     "iopub.status.idle": "2021-07-05T16:35:40.685546Z",
+     "shell.execute_reply": "2021-07-05T16:35:40.684966Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:37.532609Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x3960 with 10 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Capital gain vs categorical Feature\n",
+    "fig,ax=plt.subplots(5,2,figsize=(15,55))\n",
+    "r=0\n",
+    "c=0\n",
+    "for i,n in enumerate(cat):\n",
+    "    if i%2==0 and i>0:\n",
+    "        r+=1\n",
+    "        c=0\n",
+    "    graph=sns.boxplot(x=n,y='capital.gain',data=df,ax=ax[r,c])\n",
+    "    if n=='native.country' or n=='occupation' or n=='education':\n",
+    "        graph.set_xticklabels(graph.get_xticklabels(),rotation = 90)\n",
+    "    else:\n",
+    "        graph.set_xticklabels(graph.get_xticklabels(),rotation = 45)\n",
+    "    if n!='education.num':\n",
+    "        graph.set(xlabel=None)\n",
+    "    c+=1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Highest capital gains are seen in individuals belonging to private or self employed workclass. There are more no. of prof-school  than any other education category with highest capital gains. There are individuals even with preschool knowledge have capital gain more than 40000. As the education level increases capital gain also increases. People from the armed forces have the least capital gain while most prominent capitals gains are found in people who are in the sales occupation. Whites have more capital gains than any other race. Men also seem to have high capital gains as compared to females. There are many people from <=50k income category who have captital gains more than 10000."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Multivariate Analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:49.260323Z",
+     "iopub.status.busy": "2021-07-05T16:35:49.259888Z",
+     "iopub.status.idle": "2021-07-05T16:35:50.244228Z",
+     "shell.execute_reply": "2021-07-05T16:35:50.243292Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:49.260294Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
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+       "        if (typeof require !== 'undefined') {\n",
+       "        require.undef(\"plotly\");\n",
+       "        define('plotly', function(require, exports, module) {\n",
+       "            /**\n",
+       "* plotly.js v2.4.2\n",
+       "* Copyright 2012-2021, Plotly, Inc.\n",
+       "* All rights reserved.\n",
+       "* Licensed under the MIT license\n",
+       "*/\n",
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+       "/*!\n",
+       " * The buffer module from node.js, for the browser.\n",
+       " *\n",
+       " * @author   Feross Aboukhadijeh <feross@feross.org> <http://feross.org>\n",
+       " * @license  MIT\n",
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this._expand(r+1),this.words[r]=e?this.words[r]|1<<i:this.words[r]&~(1<<i),this.strip()},a.prototype.iadd=function(t){var e,r,n;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++)e=(0|r.words[a])+(0|n.words[a])+i,this.words[a]=67108863&e,i=e>>>26;for(;0!==i&&a<r.length;a++)e=(0|r.words[a])+i,this.words[a]=67108863&e,i=e>>>26;if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},a.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,i=this.cmp(t);if(0===i)return this.negative=0,this.length=1,this.words[0]=0,this;i>0?(r=this,n=t):(r=t,n=this);for(var a=0,o=0;o<n.length;o++)a=(e=(0|r.words[o])-(0|n.words[o])+a)>>26,this.words[o]=67108863&e;for(;0!==a&&o<r.length;o++)a=(e=(0|r.words[o])+a)>>26,this.words[o]=67108863&e;if(0===a&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},a.prototype.sub=function(t){return this.clone().isub(t)};var p=function(t,e,r){var n,i,a,o=t.words,s=e.words,l=r.words,c=0,u=0|o[0],f=8191&u,h=u>>>13,p=0|o[1],d=8191&p,g=p>>>13,m=0|o[2],v=8191&m,y=m>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],L=8191&E,C=E>>>13,P=0|o[7],I=8191&P,O=P>>>13,z=0|o[8],D=8191&z,R=z>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],U=8191&j,V=j>>>13,q=0|s[1],H=8191&q,G=q>>>13,Y=0|s[2],W=8191&Y,X=Y>>>13,Z=0|s[3],J=8191&Z,K=Z>>>13,Q=0|s[4],$=8191&Q,tt=Q>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ct=st>>>13,ut=0|s[8],ft=8191&ut,ht=ut>>>13,pt=0|s[9],dt=8191&pt,gt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var mt=(c+(n=Math.imul(f,U))|0)+((8191&(i=(i=Math.imul(f,V))+Math.imul(h,U)|0))<<13)|0;c=((a=Math.imul(h,V))+(i>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(d,U),i=(i=Math.imul(d,V))+Math.imul(g,U)|0,a=Math.imul(g,V);var vt=(c+(n=n+Math.imul(f,H)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,H)|0))<<13)|0;c=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(vt>>>26)|0,vt&=67108863,n=Math.imul(v,U),i=(i=Math.imul(v,V))+Math.imul(y,U)|0,a=Math.imul(y,V),n=n+Math.imul(d,H)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(g,H)|0,a=a+Math.imul(g,G)|0;var yt=(c+(n=n+Math.imul(f,W)|0)|0)+((8191&(i=(i=i+Math.imul(f,X)|0)+Math.imul(h,W)|0))<<13)|0;c=((a=a+Math.imul(h,X)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(b,U),i=(i=Math.imul(b,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(v,H)|0,i=(i=i+Math.imul(v,G)|0)+Math.imul(y,H)|0,a=a+Math.imul(y,G)|0,n=n+Math.imul(d,W)|0,i=(i=i+Math.imul(d,X)|0)+Math.imul(g,W)|0,a=a+Math.imul(g,X)|0;var xt=(c+(n=n+Math.imul(f,J)|0)|0)+((8191&(i=(i=i+Math.imul(f,K)|0)+Math.imul(h,J)|0))<<13)|0;c=((a=a+Math.imul(h,K)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,H)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,H)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(v,W)|0,i=(i=i+Math.imul(v,X)|0)+Math.imul(y,W)|0,a=a+Math.imul(y,X)|0,n=n+Math.imul(d,J)|0,i=(i=i+Math.imul(d,K)|0)+Math.imul(g,J)|0,a=a+Math.imul(g,K)|0;var bt=(c+(n=n+Math.imul(f,$)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,$)|0))<<13)|0;c=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,U),i=(i=Math.imul(M,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,H)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,H)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,W)|0,i=(i=i+Math.imul(b,X)|0)+Math.imul(_,W)|0,a=a+Math.imul(_,X)|0,n=n+Math.imul(v,J)|0,i=(i=i+Math.imul(v,K)|0)+Math.imul(y,J)|0,a=a+Math.imul(y,K)|0,n=n+Math.imul(d,$)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(g,$)|0,a=a+Math.imul(g,tt)|0;var _t=(c+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;c=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,U),i=(i=Math.imul(L,V))+Math.imul(C,U)|0,a=Math.imul(C,V),n=n+Math.imul(M,H)|0,i=(i=i+Math.imul(M,G)|0)+Math.imul(S,H)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,W)|0,i=(i=i+Math.imul(T,X)|0)+Math.imul(k,W)|0,a=a+Math.imul(k,X)|0,n=n+Math.imul(b,J)|0,i=(i=i+Math.imul(b,K)|0)+Math.imul(_,J)|0,a=a+Math.imul(_,K)|0,n=n+Math.imul(v,$)|0,i=(i=i+Math.imul(v,tt)|0)+Math.imul(y,$)|0,a=a+Math.imul(y,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(g,rt)|0,a=a+Math.imul(g,nt)|0;var wt=(c+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;c=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(I,U),i=(i=Math.imul(I,V))+Math.imul(O,U)|0,a=Math.imul(O,V),n=n+Math.imul(L,H)|0,i=(i=i+Math.imul(L,G)|0)+Math.imul(C,H)|0,a=a+Math.imul(C,G)|0,n=n+Math.imul(M,W)|0,i=(i=i+Math.imul(M,X)|0)+Math.imul(S,W)|0,a=a+Math.imul(S,X)|0,n=n+Math.imul(T,J)|0,i=(i=i+Math.imul(T,K)|0)+Math.imul(k,J)|0,a=a+Math.imul(k,K)|0,n=n+Math.imul(b,$)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,$)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(v,rt)|0,i=(i=i+Math.imul(v,nt)|0)+Math.imul(y,rt)|0,a=a+Math.imul(y,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(g,at)|0,a=a+Math.imul(g,ot)|0;var Tt=(c+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ct)|0)+Math.imul(h,lt)|0))<<13)|0;c=((a=a+Math.imul(h,ct)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(D,U),i=(i=Math.imul(D,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(I,H)|0,i=(i=i+Math.imul(I,G)|0)+Math.imul(O,H)|0,a=a+Math.imul(O,G)|0,n=n+Math.imul(L,W)|0,i=(i=i+Math.imul(L,X)|0)+Math.imul(C,W)|0,a=a+Math.imul(C,X)|0,n=n+Math.imul(M,J)|0,i=(i=i+Math.imul(M,K)|0)+Math.imul(S,J)|0,a=a+Math.imul(S,K)|0,n=n+Math.imul(T,$)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,$)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(v,at)|0,i=(i=i+Math.imul(v,ot)|0)+Math.imul(y,at)|0,a=a+Math.imul(y,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ct)|0)+Math.imul(g,lt)|0,a=a+Math.imul(g,ct)|0;var kt=(c+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;c=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(D,H)|0,i=(i=i+Math.imul(D,G)|0)+Math.imul(R,H)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(I,W)|0,i=(i=i+Math.imul(I,X)|0)+Math.imul(O,W)|0,a=a+Math.imul(O,X)|0,n=n+Math.imul(L,J)|0,i=(i=i+Math.imul(L,K)|0)+Math.imul(C,J)|0,a=a+Math.imul(C,K)|0,n=n+Math.imul(M,$)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(S,$)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(v,lt)|0,i=(i=i+Math.imul(v,ct)|0)+Math.imul(y,lt)|0,a=a+Math.imul(y,ct)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(g,ft)|0,a=a+Math.imul(g,ht)|0;var At=(c+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,gt)|0)+Math.imul(h,dt)|0))<<13)|0;c=((a=a+Math.imul(h,gt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,H),i=(i=Math.imul(B,G))+Math.imul(N,H)|0,a=Math.imul(N,G),n=n+Math.imul(D,W)|0,i=(i=i+Math.imul(D,X)|0)+Math.imul(R,W)|0,a=a+Math.imul(R,X)|0,n=n+Math.imul(I,J)|0,i=(i=i+Math.imul(I,K)|0)+Math.imul(O,J)|0,a=a+Math.imul(O,K)|0,n=n+Math.imul(L,$)|0,i=(i=i+Math.imul(L,tt)|0)+Math.imul(C,$)|0,a=a+Math.imul(C,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ct)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ct)|0,n=n+Math.imul(v,ft)|0,i=(i=i+Math.imul(v,ht)|0)+Math.imul(y,ft)|0,a=a+Math.imul(y,ht)|0;var Mt=(c+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,gt)|0)+Math.imul(g,dt)|0))<<13)|0;c=((a=a+Math.imul(g,gt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,W),i=(i=Math.imul(B,X))+Math.imul(N,W)|0,a=Math.imul(N,X),n=n+Math.imul(D,J)|0,i=(i=i+Math.imul(D,K)|0)+Math.imul(R,J)|0,a=a+Math.imul(R,K)|0,n=n+Math.imul(I,$)|0,i=(i=i+Math.imul(I,tt)|0)+Math.imul(O,$)|0,a=a+Math.imul(O,tt)|0,n=n+Math.imul(L,rt)|0,i=(i=i+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,a=a+Math.imul(C,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ct)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ct)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(c+(n=n+Math.imul(v,dt)|0)|0)+((8191&(i=(i=i+Math.imul(v,gt)|0)+Math.imul(y,dt)|0))<<13)|0;c=((a=a+Math.imul(y,gt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),i=(i=Math.imul(B,K))+Math.imul(N,J)|0,a=Math.imul(N,K),n=n+Math.imul(D,$)|0,i=(i=i+Math.imul(D,tt)|0)+Math.imul(R,$)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(I,rt)|0,i=(i=i+Math.imul(I,nt)|0)+Math.imul(O,rt)|0,a=a+Math.imul(O,nt)|0,n=n+Math.imul(L,at)|0,i=(i=i+Math.imul(L,ot)|0)+Math.imul(C,at)|0,a=a+Math.imul(C,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ct)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ct)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(c+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,gt)|0)+Math.imul(_,dt)|0))<<13)|0;c=((a=a+Math.imul(_,gt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,$),i=(i=Math.imul(B,tt))+Math.imul(N,$)|0,a=Math.imul(N,tt),n=n+Math.imul(D,rt)|0,i=(i=i+Math.imul(D,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(I,at)|0,i=(i=i+Math.imul(I,ot)|0)+Math.imul(O,at)|0,a=a+Math.imul(O,ot)|0,n=n+Math.imul(L,lt)|0,i=(i=i+Math.imul(L,ct)|0)+Math.imul(C,lt)|0,a=a+Math.imul(C,ct)|0,n=n+Math.imul(M,ft)|0,i=(i=i+Math.imul(M,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Lt=(c+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,gt)|0)+Math.imul(k,dt)|0))<<13)|0;c=((a=a+Math.imul(k,gt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(D,at)|0,i=(i=i+Math.imul(D,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(I,lt)|0,i=(i=i+Math.imul(I,ct)|0)+Math.imul(O,lt)|0,a=a+Math.imul(O,ct)|0,n=n+Math.imul(L,ft)|0,i=(i=i+Math.imul(L,ht)|0)+Math.imul(C,ft)|0,a=a+Math.imul(C,ht)|0;var Ct=(c+(n=n+Math.imul(M,dt)|0)|0)+((8191&(i=(i=i+Math.imul(M,gt)|0)+Math.imul(S,dt)|0))<<13)|0;c=((a=a+Math.imul(S,gt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(D,lt)|0,i=(i=i+Math.imul(D,ct)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ct)|0,n=n+Math.imul(I,ft)|0,i=(i=i+Math.imul(I,ht)|0)+Math.imul(O,ft)|0,a=a+Math.imul(O,ht)|0;var Pt=(c+(n=n+Math.imul(L,dt)|0)|0)+((8191&(i=(i=i+Math.imul(L,gt)|0)+Math.imul(C,dt)|0))<<13)|0;c=((a=a+Math.imul(C,gt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ct))+Math.imul(N,lt)|0,a=Math.imul(N,ct),n=n+Math.imul(D,ft)|0,i=(i=i+Math.imul(D,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var It=(c+(n=n+Math.imul(I,dt)|0)|0)+((8191&(i=(i=i+Math.imul(I,gt)|0)+Math.imul(O,dt)|0))<<13)|0;c=((a=a+Math.imul(O,gt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var Ot=(c+(n=n+Math.imul(D,dt)|0)|0)+((8191&(i=(i=i+Math.imul(D,gt)|0)+Math.imul(R,dt)|0))<<13)|0;c=((a=a+Math.imul(R,gt)|0)+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863;var zt=(c+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,gt))+Math.imul(N,dt)|0))<<13)|0;return c=((a=Math.imul(N,gt))+(i>>>13)|0)+(zt>>>26)|0,zt&=67108863,l[0]=mt,l[1]=vt,l[2]=yt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=Pt,l[16]=It,l[17]=Ot,l[18]=zt,0!==c&&(l[19]=c,r.length++),r};function d(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(p=h),a.prototype.mulTo=function(t,e){var r=this.length+t.length;return 10===this.length&&10===t.length?p(this,t,e):r<63?h(this,t,e):r<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a<r.length-1;a++){var o=i;i=0;for(var s=67108863&n,l=Math.min(a,e.length-1),c=Math.max(0,a-t.length+1);c<=l;c++){var u=a-c,f=(0|t.words[u])*(0|e.words[c]),h=67108863&f;s=67108863&(h=h+s|0),i+=(o=(o=o+(f/67108864|0)|0)+(h>>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):d(this,t,e)},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,i=0;i<e;i++)n|=(1&t)<<e-i-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o<a;o++)n[o]=e[t[o]],i[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,i,a){this.permute(a,t,e,r,n,i);for(var o=1;o<i;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),c=Math.sin(2*Math.PI/s),u=0;u<i;u+=s)for(var f=l,h=c,p=0;p<o;p++){var d=r[u+p],g=n[u+p],m=r[u+p+o],v=n[u+p+o],y=f*m-h*v;v=f*v+h*m,m=y,r[u+p]=d+m,n[u+p]=g+v,r[u+p+o]=d-m,n[u+p+o]=g-v,p!==s&&(y=l*f-c*h,h=l*h+c*f,f=y)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,i=0;for(r=r/2|0;r;r>>>=1)i++;return 1<<i+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var i=t[n];t[n]=t[r-n-1],t[r-n-1]=i,i=e[n],e[n]=-e[r-n-1],e[r-n-1]=-i}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var i=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&i,r=i<67108864?0:i/67108864|0}return t},g.prototype.convert13b=function(t,e,r,i){for(var a=0,o=0;o<e;o++)a+=0|t[o],r[2*o]=8191&a,a>>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o<i;++o)r[o]=0;n(0===a),n(0==(-8192&a))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),i=this.makeRBT(n),a=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),c=new Array(n),u=new Array(n),f=new Array(n),h=r.words;h.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,c,n),this.transform(o,a,s,l,n,i),this.transform(c,a,u,f,n,i);for(var p=0;p<n;p++){var d=s[p]*u[p]-l[p]*f[p];l[p]=s[p]*f[p]+l[p]*u[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,h,a,n,i),this.conjugate(h,a,n),this.normalize13b(h,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},a.prototype.mul=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},a.prototype.mulf=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),d(this,t,e)},a.prototype.imul=function(t){return this.clone().mulTo(t,this)},a.prototype.imuln=function(t){n(\"number\"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var i=(0|this.words[r])*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,i=r%26;e[r]=(t.words[n]&1<<i)>>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var i=r.sqr();n<e.length;n++,i=i.sqr())0!==e[n]&&(r=r.mul(i));return r},a.prototype.iushln=function(t){n(\"number\"==typeof t&&t>=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&a,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e<i;e++)this.words[e]=0;this.length+=i}return this.strip()},a.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},a.prototype.iushrn=function(t,e,r){var i;n(\"number\"==typeof t&&t>=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=r;if(i-=o,i=Math.max(0,i),l){for(var c=0;c<o;c++)l.words[c]=this.words[c];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,c=0;c<this.length;c++)this.words[c]=this.words[c+o];else this.words[0]=0,this.length=1;var u=0;for(c=this.length-1;c>=0&&(0!==u||c>=i);c--){var f=0|this.words[c];this.words[c]=u<<26-a|f>>>a,u=f&s}return l&&0!==u&&(l.words[l.length++]=u),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<<e;return!(this.length<=r)&&!!(this.words[r]&i)},a.prototype.imaskn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},a.prototype.maskn=function(t){return this.clone().imaskn(t)},a.prototype.iaddn=function(t){return n(\"number\"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},a.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},a.prototype.addn=function(t){return this.clone().iaddn(t)},a.prototype.subn=function(t){return this.clone().isubn(t)},a.prototype.iabs=function(){return this.negative=0,this},a.prototype.abs=function(){return this.clone().iabs()},a.prototype._ishlnsubmul=function(t,e,r){var i,a,o=t.length+r;this._expand(o);var s=0;for(i=0;i<t.length;i++){a=(0|this.words[i+r])+s;var l=(0|t.words[i])*e;s=((a-=67108863&l)>>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i<this.length-r;i++)s=(a=(0|this.words[i+r])+s)>>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i<this.length;i++)s=(a=-(0|this.words[i])+s)>>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!==(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var c=0;c<s.length;c++)s.words[c]=0}var u=n.clone()._ishlnsubmul(i,1,l);0===u.negative&&(n=u,s&&(s.words[l]=1));for(var f=l-1;f>=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),c=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++c;for(var u=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(u),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,g=1;0==(r.words[0]&g)&&d<26;++d,g<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(u),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(c)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var c=0,u=1;0==(e.words[0]&u)&&c<26;++c,u<<=1);if(c>0)for(e.iushrn(c);c-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,i=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=i,this;for(var a=i,o=r;0!==a&&o<this.length;o++){var s=0|this.words[o];a=(s+=a)>>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];e=i===t?0:i<t?-1:1}return 0!==this.negative?0|-e:e},a.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},a.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return e},a.prototype.gtn=function(t){return 1===this.cmpn(t)},a.prototype.gt=function(t){return 1===this.cmp(t)},a.prototype.gten=function(t){return this.cmpn(t)>=0},a.prototype.gte=function(t){return this.cmp(t)>=0},a.prototype.ltn=function(t){return-1===this.cmpn(t)},a.prototype.lt=function(t){return-1===this.cmp(t)},a.prototype.lten=function(t){return this.cmpn(t)<=0},a.prototype.lte=function(t){return this.cmp(t)<=0},a.prototype.eqn=function(t){return 0===this.cmpn(t)},a.prototype.eq=function(t){return 0===this.cmp(t)},a.red=function(t){return new w(t)},a.prototype.toRed=function(t){return n(!this.red,\"Already a number in reduction context\"),n(0===this.negative,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},a.prototype.fromRed=function(){return n(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},a.prototype._forceRed=function(t){return this.red=t,this},a.prototype.forceRed=function(t){return n(!this.red,\"Already a number 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numbers\"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var m={k256:null,p224:null,p192:null,p25519:null};function v(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function y(){v.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff 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e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},v.prototype.split=function(t,e){t.iushrn(this.n,0,e)},v.prototype.imulK=function(t){return t.imul(this.k)},i(y,v),y.prototype.split=function(t,e){for(var r=Math.min(t.length,9),n=0;n<r;n++)e.words[n]=t.words[n];if(e.length=r,t.length<=9)return t.words[0]=0,void(t.length=1);var i=t.words[9];for(e.words[e.length++]=4194303&i,n=10;n<t.length;n++){var a=0|t.words[n];t.words[n-10]=(4194303&a)<<4|i>>>22,i=a}i>>>=22,t.words[n-10]=i,0===i&&t.length>10?t.length-=10:t.length-=9},y.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r<t.length;r++){var n=0|t.words[r];e+=977*n,t.words[r]=67108863&e,e=64*n+(e/67108864|0)}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},i(x,v),i(b,v),i(_,v),_.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*(0|t.words[r])+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(m[t])return m[t];var e;if(\"k256\"===t)e=new y;else if(\"p224\"===t)e=new x;else if(\"p192\"===t)e=new b;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new _}return m[t]=e,e},w.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red numbers\")},w.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),\"red works only with positives\"),n(t.red&&t.red===e.red,\"red works only with red numbers\")},w.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},w.prototype.neg=function(t){return 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r=t.mul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),o=i;return i.cmp(this.m)>=0?o=i.isub(this.m):i.cmpn(0)<0&&(o=i.iadd(this.m)),o._forceRed(this)},T.prototype.invm=function(t){return this.imod(t._invmp(this.m).mul(this.r2))._forceRed(this)}}(void 0===e||e,this)},{buffer:115}],107:[function(t,e,r){\"use strict\";e.exports=function(t){var e,r,n,i=t.length,a=0;for(e=0;e<i;++e)a+=t[e].length;var o=new Array(a),s=0;for(e=0;e<i;++e){var l=t[e],c=l.length;for(r=0;r<c;++r){var u=o[s++]=new Array(c-1),f=0;for(n=0;n<c;++n)n!==r&&(u[f++]=l[n]);if(1&r){var h=u[1];u[1]=u[0],u[0]=h}}}return o}},{}],108:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){switch(arguments.length){case 1:return f(t);case 2:return\"function\"==typeof e?c(t,t,e,!0):h(t,e);case 3:return c(t,e,r,!1);default:throw new Error(\"box-intersect: Invalid arguments\")}};var n,i=t(\"typedarray-pool\"),a=t(\"./lib/sweep\"),o=t(\"./lib/intersect\");function s(t,e){for(var r=0;r<t;++r)if(!(e[r]<=e[r+t]))return!0;return!1}function l(t,e,r,n){for(var i=0,a=0,o=0,l=t.length;o<l;++o){var c=t[o];if(!s(e,c)){for(var u=0;u<2*e;++u)r[i++]=c[u];n[a++]=o}}return a}function c(t,e,r,n){var s=t.length,c=e.length;if(!(s<=0||c<=0)){var u=t[0].length>>>1;if(!(u<=0)){var f,h=i.mallocDouble(2*u*s),p=i.mallocInt32(s);if((s=l(t,u,h,p))>0){if(1===u&&n)a.init(s),f=a.sweepComplete(u,r,0,s,h,p,0,s,h,p);else{var d=i.mallocDouble(2*u*c),g=i.mallocInt32(c);(c=l(e,u,d,g))>0&&(a.init(s+c),f=1===u?a.sweepBipartite(u,r,0,s,h,p,0,c,d,g):o(u,r,n,s,h,p,c,d,g),i.free(d),i.free(g))}i.free(h),i.free(p)}return f}}}function u(t,e){n.push([t,e])}function f(t){return n=[],c(t,t,u,!0),n}function h(t,e){return n=[],c(t,e,u,!1),n}},{\"./lib/intersect\":110,\"./lib/sweep\":114,\"typedarray-pool\":617}],109:[function(t,e,r){\"use strict\";var n=[\"d\",\"ax\",\"vv\",\"rs\",\"re\",\"rb\",\"ri\",\"bs\",\"be\",\"bb\",\"bi\"];function i(t){var 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m\".replace(\"_\",n.join()).replace(\"$\",t)),Function.apply(void 0,r)}},{}],113:[function(t,e,r){\"use strict\";e.exports=function(t,e){e<=128?n(0,e-1,t):function t(e,r,u){var f=(r-e+1)/6|0,h=e+f,p=r-f,d=e+r>>1,g=d-f,m=d+f,v=h,y=g,x=d,b=m,_=p,w=e+1,T=r-1,k=0;l(v,y,u)&&(k=v,v=y,y=k);l(b,_,u)&&(k=b,b=_,_=k);l(v,x,u)&&(k=v,v=x,x=k);l(y,x,u)&&(k=y,y=x,x=k);l(v,b,u)&&(k=v,v=b,b=k);l(x,b,u)&&(k=x,x=b,b=k);l(y,_,u)&&(k=y,y=_,_=k);l(y,x,u)&&(k=y,y=x,x=k);l(b,_,u)&&(k=b,b=_,_=k);for(var A=u[2*y],M=u[2*y+1],S=u[2*b],E=u[2*b+1],L=2*v,C=2*x,P=2*_,I=2*h,O=2*d,z=2*p,D=0;D<2;++D){var R=u[L+D],F=u[C+D],B=u[P+D];u[I+D]=R,u[O+D]=F,u[z+D]=B}a(g,e,u),a(m,r,u);for(var N=w;N<=T;++N)if(c(N,A,M,u))N!==w&&i(N,w,u),++w;else if(!c(N,S,E,u))for(;;){if(c(T,S,E,u)){c(T,A,M,u)?(o(N,w,T,u),++w,--T):(i(N,T,u),--T);break}if(--T<N)break}s(e,w-1,A,M,u),s(r,T+1,S,E,u),w-2-e<=32?n(e,w-2,u):t(e,w-2,u);r-(T+2)<=32?n(T+2,r,u):t(T+2,r,u);T-w<=32?n(w,T,u):t(w,T,u)}(0,e-1,t)};function n(t,e,r){for(var 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r=8*e;h.length<r&&(n.free(h),h=n.mallocDouble(r))},sweepBipartite:function(t,e,r,n,i,u,f,g,m,v){for(var y=0,x=2*t,b=t-1,_=x-1,w=r;w<n;++w){var T=u[w],k=x*w;h[y++]=i[k+b],h[y++]=-(T+1),h[y++]=i[k+_],h[y++]=T}for(w=f;w<g;++w){T=v[w]+(1<<28);var A=x*w;h[y++]=m[A+b],h[y++]=-T,h[y++]=m[A+_],h[y++]=T}var M=y>>>1;a(h,M);var S=0,E=0;for(w=0;w<M;++w){var L=0|h[2*w+1];if(L>=1<<28)p(l,c,E--,L=L-(1<<28)|0);else if(L>=0)p(o,s,S--,L);else if(L<=-(1<<28)){L=-L-(1<<28)|0;for(var C=0;C<S;++C){if(void 0!==(P=e(o[C],L)))return P}d(l,c,E++,L)}else{L=-L-1|0;for(C=0;C<E;++C){var P;if(void 0!==(P=e(L,l[C])))return P}d(o,s,S++,L)}}},sweepComplete:function(t,e,r,n,i,g,m,v,y,x){for(var b=0,_=2*t,w=t-1,T=_-1,k=r;k<n;++k){var A=g[k]+1<<1,M=_*k;h[b++]=i[M+w],h[b++]=-A,h[b++]=i[M+T],h[b++]=A}for(k=m;k<v;++k){A=x[k]+1<<1;var S=_*k;h[b++]=y[S+w],h[b++]=1|-A,h[b++]=y[S+T],h[b++]=1|A}var E=b>>>1;a(h,E);var L=0,C=0,P=0;for(k=0;k<E;++k){var I=0|h[2*k+1],O=1&I;if(k<E-1&&I>>1==h[2*k+3]>>1&&(O=2,k+=1),I<0){for(var 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c(t){if(\"function\"!=typeof t)throw new TypeError('The \"listener\" argument must be of type Function. 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+       "/*!\n",
+       " * The buffer module from node.js, for the browser.\n",
+       " *\n",
+       " * @author   Feross Aboukhadijeh <https://feross.org>\n",
+       " * @license  MIT\n",
+       " */\n",
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h=a/2,p=s/2,d=g(h),m=o(h),y=g(p),b=o(p),T=o(s),k=L(T),A=y/(b+w*m*k),M=A*A,S=L(2/(1+M)),E=(w*b+(m+d)*k)/(w*b+(m-d)*k),C=L(E),P=C-1/C,I=C+1/C,O=S*P-2*c(C)-t,z=S*A*I-2*i(A)-e,R=y&&_*k*d*M/y,F=(w*m*b+k)/(2*(b+w*m*k)*(b+w*m*k)*k),B=-.5*A*S*S*S,N=B*R,j=B*F,U=(U=2*b+w*k*(m-d))*U*C,V=(w*m*b*k+T)/U,q=-w*d*y/(k*U),H=P*N-2*V/C+S*(V+V/E),G=P*j-2*q/C+S*(q+q/E),Y=A*I*N-2*R/(1+M)+S*I*R+S*A*(V-V/E),W=A*I*j-2*F/(1+M)+S*I*F+S*A*(q-q/E),X=G*Y-W*H;if(!X)break;var Z=(z*G-O*W)/X,J=(O*Y-z*H)/X;a-=Z,s=u(-x,f(x,s-J))}while((n(Z)>v||n(J)>v)&&--l>0);return n(n(s)-x)<v?[0,s]:l&&[a,s]};var wt=o(35*M);function Tt(t,e){var r=m(e/2);return[t*wt*L(1-r*r),(1+wt)*r]}function kt(t,e){var r=e/2,n=o(r);return[2*t/T*o(e)*n*n,T*m(r)]}function At(t){var e=1-t,r=i(y,0)[0]-i(-y,0)[0],n=L(2*(i(0,x)[1]-i(0,-x)[1])/r);function i(r,n){var i=o(n),a=g(n);return[i/(e+t*i)*r,e*n+t*a]}function a(t,e){var r=i(t,e);return[r[0]*n,r[1]/n]}function s(t){return a(0,t)[1]}return a.invert=function(r,i){var a=V(s,i);return[r/n*(t+e/o(a)),a]},a}function Mt(t){return[t[0]/2,S(m(t[1]/2*M))*A]}function St(t){return[2*t[0],2*i(g(t[1]*M))*A]}function Et(t,r){var i=2*y/r,s=t*t;function l(r,l){var c=e.geoAzimuthalEquidistantRaw(r,l),u=c[0],f=c[1],h=u*u+f*f;if(h>s){var d=L(h),m=a(f,u),b=i*p(m/i),_=m-b,w=t*o(_),T=(t*g(_)-_*g(w))/(x-w),k=Lt(_,T),A=(y-t)/Ct(k,w,y);u=d;var M,S=50;do{u-=M=(t+Ct(k,w,u)*A-d)/(k(u)*A)}while(n(M)>v&&--S>0);f=_*g(u),u<x&&(f-=T*(u-x));var E=g(b),C=o(b);c[0]=u*C-f*E,c[1]=u*E+f*C}return c}return l.invert=function(r,l){var c=r*r+l*l;if(c>s){var u=L(c),f=a(l,r),h=i*p(f/i),d=f-h;r=u*o(d),l=u*g(d);for(var m=r-x,v=g(r),b=l/v,_=r<x?1/0:0,w=10;;){var T=t*g(b),k=t*o(b),A=g(k),M=x-k,S=(T-b*A)/M,E=Lt(b,S);if(n(_)<1e-12||!--w)break;b-=_=(b*v-S*m-l)/(v-2*m*(M*(k+b*T*o(k)-A)-T*(T-b*A))/(M*M))}r=(u=t+Ct(E,k,r)*(y-t)/Ct(E,k,y))*o(f=h+b),l=u*g(f)}return e.geoAzimuthalEquidistantRaw.invert(r,l)},l}function Lt(t,e){return function(r){var n=t*o(r);return r<x&&(n-=e),L(1+n*n)}}function 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s=i(t,a);t=s[0],a=s[1];var l=g(a),c=o(a),u=o(t),f=E(e*l+r*c*u),h=g(f),p=n(h)>v?f/h:1;return[p*r*g(t),(n(t)>x?p:-p)*(e*c-r*l*u)]}return i.invert=qt(-t),s.invert=function(t,r){var n=L(t*t+r*r),s=-g(n),l=o(n),c=n*l,u=-r*s,f=n*e,h=L(c*c+u*u-f*f),p=a(c*f+u*h,u*f-c*h),d=(n>x?-1:1)*a(t*s,n*o(p)*l+r*g(p)*s);return i.invert(d,p)},s}function qt(t){var e=g(t),r=o(t);return function(t,n){var i=o(n),s=o(t)*i,l=g(t)*i,c=g(n);return[a(l,s*r-c*e),S(c*r+s*e)]}}Bt.invert=function(t,e){n(t)>1&&(t=2*d(t)-t),n(e)>1&&(e=2*d(e)-e);var r=d(t),i=d(e),s=-r*t,l=-i*e,c=l/s<1,u=function(t,e){var r=0,i=1,a=.5,s=50;for(;;){var l=a*a,c=L(a),u=S(1/L(1+l)),f=1-l+a*(1+l)*u,h=(1-c)/f,p=L(h),d=h*(1+l),g=p*(1-l),m=L(d-t*t),v=e+g+a*m;if(n(i-r)<1e-12||0==--s||0===v)break;v>0?r=a:i=a,a=.5*(r+i)}if(!s)return null;var x=S(c),b=o(x),_=1/b,w=2*c*b,T=(-f*b-(-3*a+u*(1+3*l))*w*(1-c))/(f*f);return[y/4*(t*(-2*_*(.5*T/p*(1-l)-2*a*p*w)+-_*w*m)+-_*(a*(1+l)*T+h*(1+3*l)*w)*S(t/L(d))),x]}(c?l:s,c?s:l),f=u[0],h=u[1],p=o(h);return c&&(f=-x-f),[r*(a(g(f)*p,-g(h))+y),i*S(o(f)*p)]},Ut.invert=function(t,e){var r,n,o,l,u,f,h=(w-1)/(w+1),p=L(1-h*h),d=jt(x,p*p),g=(n=-t,o=p*p,(r=.5*d-e)?(l=Nt(r,o),n?(f=(u=Nt(n,1-o))[1]*u[1]+o*l[0]*l[0]*u[0]*u[0],[[l[0]*u[2]/f,l[1]*l[2]*u[0]*u[1]/f],[l[1]*u[1]/f,-l[0]*l[2]*u[0]*u[2]/f],[l[2]*u[1]*u[2]/f,-o*l[0]*l[1]*u[0]/f]]):[[l[0],0],[l[1],0],[l[2],0]]):[[0,(u=Nt(n,1-o))[0]/u[1]],[1/u[1],0],[u[2]/u[1],0]]),m=function(t,e){var r=e[0]*e[0]+e[1]*e[1];return[(t[0]*e[0]+t[1]*e[1])/r,(t[1]*e[0]-t[0]*e[1])/r]}(g[0],g[1]);return[a(m[1],m[0])/-1,2*i(s(-.5*c(h*m[0]*m[0]+h*m[1]*m[1])))-x]};var Ht=S(1-1/3)*A,Gt=ht(0);function Yt(t){var e=Ht*M,r=lt(y,e)[0]-lt(-y,e)[0],i=Gt(0,e)[1],a=lt(0,e)[1],o=T-a,s=k/t,c=4/k,h=i+o*o*4/k;function p(p,d){var g,m=n(d);if(m>e){var v=f(t-1,u(0,l((p+y)/s)));(g=lt(p+=y*(t-1)/t-v*s,m))[0]=g[0]*k/r-k*(t-1)/(2*t)+v*k/t,g[1]=i+4*(g[1]-a)*o/k,d<0&&(g[1]=-g[1])}else g=Gt(p,d);return g[0]*=c,g[1]/=h,g}return p.invert=function(e,p){e/=c;var d=n(p*=h);if(d>i){var 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n=t(\"./lib/text.js\"),i=t(\"./lib/lines.js\"),a=t(\"./lib/background.js\"),o=t(\"./lib/cube.js\"),s=t(\"./lib/ticks.js\"),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function c(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function u(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=\"sans-serif\",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=a(t)}var f=u.prototype;function h(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}f.update=function(t){function e(e,r,n){if(n in t){var i,a=t[n],o=this[n];(e?Array.isArray(a)&&Array.isArray(a[0]):Array.isArray(a))?this[n]=i=[r(a[0]),r(a[1]),r(a[2])]:this[n]=i=[r(a),r(a),r(a)];for(var s=0;s<3;++s)if(i[s]!==o[s])return!0}return!1}t=t||{};var r,a=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),c=e.bind(this,!0,(function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]})),u=!1,f=!1;if(\"bounds\"in t)for(var h=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)h[p][d]!==this.bounds[p][d]&&(f=!0),this.bounds[p][d]=h[p][d];if(\"ticks\"in t){r=t.ticks,u=!0,this.autoTicks=!1;for(p=0;p<3;++p)this.tickSpacing[p]=0}else a(\"tickSpacing\")&&(this.autoTicks=!0,f=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),f=!0,u=!0,this._firstInit=!1),f&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),u=!0),u){for(p=0;p<3;++p)r[p].sort((function(t,e){return t.x-e.x}));s.equal(r,this.ticks)?u=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(u=!0),a(\"tickSize\"),a(\"tickAngle\"),a(\"tickPad\"),c(\"tickColor\");var g=l(\"labels\");l(\"labelFont\")&&(g=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),c(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),c(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),c(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),c(\"gridColor\"),o(\"zeroEnable\"),c(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),c(\"backgroundColor\"),this._text?this._text&&(g||u)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&u&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,c=n[e],u=0;u<3;++u)if(e!==u){var f=a,h=s,p=o,d=l;c&1<<u&&(f=s,h=a,p=l,d=o),f[u]=r[0][u],h[u]=r[1][u],i[u]>0?(p[u]=-1,d[u]=0):(p[u]=0,d[u]=1)}}var g=[0,0,0],m={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var v=[0,0,0],y=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||m;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,u=o(r,n,i,a,s),f=u.cubeEdges,h=u.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=f[A],this.lastCubeProps.axis[A]=h[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,f,h);e=this.gl;var S,E=g;for(A=0;A<3;++A)this.backgroundEnable[A]?E[A]=h[A]:E[A]=0;this._background.draw(r,n,i,a,E,this.backgroundColor),this._lines.bind(r,n,i,this);for(A=0;A<3;++A){var L=[0,0,0];h[A]>0?L[A]=a[1][A]:L[A]=a[0][A];for(var C=0;C<2;++C){var P=(A+1+C)%3,I=(A+1+(1^C))%3;this.gridEnable[P]&&this._lines.drawGrid(P,I,this.bounds,L,this.gridColor[P],this.gridWidth[P]*this.pixelRatio)}for(C=0;C<2;++C){P=(A+1+C)%3,I=(A+1+(1^C))%3;this.zeroEnable[I]&&Math.min(a[0][I],a[1][I])<=0&&Math.max(a[0][I],a[1][I])>=0&&this._lines.drawZero(P,I,this.bounds,L,this.zeroLineColor[I],this.zeroLineWidth[I]*this.pixelRatio)}}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var O=c(v,M[A].primalMinor),z=c(y,M[A].mirrorMinor),D=this.lineTickLength;for(C=0;C<3;++C){var R=k/r[5*C];O[C]*=D[C]*R,z[C]*=D[C]*R}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,O,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,z,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio);var F,B;function N(t){(B=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(A=0;A<3;++A){var U=M[A].primalMinor,V=M[A].mirrorMinor,q=c(x,M[A].primalOffset);for(C=0;C<3;++C)this.lineTickEnable[A]&&(q[C]+=k*U[C]*Math.max(this.lineTickLength[C],0)/r[5*C]);var H=[0,0,0];if(H[A]=1,this.tickEnable[A]){-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]=\"auto\"):this.tickAlign[A]=-1,F=1,\"auto\"===(S=[this.tickAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),B=[0,0,0],j(A,U,V);for(C=0;C<3;++C)q[C]+=k*U[C]*this.tickPad[C]/r[5*C];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],q,this.tickColor[A],H,B,S)}if(this.labelEnable[A]){F=0,B=[0,0,0],this.labels[A].length>4&&(N(A),F=1),\"auto\"===(S=[this.labelAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]);for(C=0;C<3;++C)q[C]+=k*U[C]*this.labelPad[C]/r[5*C];q[A]+=.5*(a[0][A]+a[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],q,this.labelColor[A],[0,0,0],B,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":259,\"./lib/cube.js\":260,\"./lib/lines.js\":261,\"./lib/text.js\":263,\"./lib/ticks.js\":264}],259:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var c=(l+1)%3,u=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[c]=d;for(var g=-1;g<=1;g+=2)f[u]=g,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var m=c;c=u,u=m}var v=n(t,new Float32Array(e)),y=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:v,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:v,type:t.FLOAT,size:3,offset:12,stride:24}],y),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,v,x,b)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders\":262,\"gl-buffer\":267,\"gl-vao\":361}],260:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var y=0,x=0;x<2;++x){u[2]=a[x][2];for(var b=0;b<2;++b){u[1]=a[b][1];for(var _=0;_<2;++_)u[0]=a[_][0],h(l[y],u,s),y+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)c[x][k]=l[x][k]/T;p&&(c[x][2]*=-1),T<0&&(w<0||c[x][2]<c[w][2])&&(w=x)}if(w<0){w=0;for(var A=0;A<3;++A){for(var M=(A+2)%3,S=(A+1)%3,E=-1,L=-1,C=0;C<2;++C){var P=(O=C<<A)+(C<<M)+(1-C<<S),I=O+(1-C<<M)+(C<<S);o(c[O],c[P],c[I],f)<0||(C?E=1:L=1)}if(E<0||L<0)L>E&&(w|=1<<A);else{for(C=0;C<2;++C){P=(O=C<<A)+(C<<M)+(1-C<<S),I=O+(1-C<<M)+(C<<S);var O,z=d([l[O],l[P],l[I],l[O+(1<<M)+(1<<S)]]);C?E=z:L=z}L>E&&(w|=1<<A)}}}var D=7^w,R=-1;for(x=0;x<8;++x)x!==w&&x!==D&&(R<0||c[R][1]>c[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x){if((N=R^1<<x)!==w&&N!==D)F<0&&(F=N),(S=c[N])[0]<c[F][0]&&(F=N)}var B=-1;for(x=0;x<3;++x){var N;if((N=R^1<<x)!==w&&N!==D&&N!==F)B<0&&(B=N),(S=c[N])[0]>c[B][0]&&(B=N)}var j=g;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===D?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=m,q=w;for(A=0;A<3;++A)V[A]=q&1<<A?-1:1;return v};var n=t(\"bit-twiddle\"),i=t(\"gl-mat4/multiply\"),a=t(\"split-polygon\"),o=t(\"robust-orientation\"),s=new Array(16),l=new Array(8),c=new Array(8),u=new Array(3),f=[0,0,0];function h(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var i=0;i<3;++i)t[n]+=e[i]*r[4*i+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],c[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=a.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],i=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],c=s[0]/s[3]-n,u=s[1]/s[3]-i,f=l[0]/l[3]-n,h=l[1]/l[3]-i;o+=Math.abs(c*h-u*f)}return o}var g=[1,1,1],m=[0,0,0],v={cubeEdges:g,axis:m}},{\"bit-twiddle\":104,\"gl-mat4/multiply\":301,\"robust-orientation\":548,\"split-polygon\":567}],261:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var f=0;f<3;++f){for(var h=o.length/3|0,d=0;d<r[f].length;++d){var g=+r[f][d].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var m=o.length/3|0;s[f]=h,l[f]=m-h;h=o.length/3|0;for(var v=0;v<r[f].length;++v){g=+r[f][v].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}m=o.length/3|0;c[f]=h,u[f]=m-h}var y=n(t,new Float32Array(o)),x=i(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),b=a(t);return b.attributes.position.location=0,new p(t,y,x,b,l,s,u,c)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").line,o=[0,0,0],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[1,1];function f(t){return t[0]=t[1]=t[2]=0,t}function h(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,u[0]=this.gl.drawingBufferWidth,u[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=u,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,i){var a=f(s);this.shader.uniforms.majorAxis=s,a[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=a;var o,u=h(c,r);u[t]+=e[0][t],this.shader.uniforms.offset=u,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=n,(o=f(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=f(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=f(o);a[t]=1,this.shader.uniforms.majorAxis=a,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=i;var s=f(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,i,a){if(this.gridCount[t]){var u=f(s);u[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=u;var p=h(c,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=f(o);d[t]=1,this.shader.uniforms.majorAxis=d;var g=f(l);g[t]=1,this.shader.uniforms.screenAxis=g,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,i,a){var o=f(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var u=h(c,n);u[t]+=r[0][t],this.shader.uniforms.offset=u;var p=f(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":262,\"gl-buffer\":267,\"gl-vao\":361}],262:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);r.line=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"}])};var s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis, alignDir, alignOpt;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nfloat computeViewAngle(vec3 a, vec3 b) {\\n  vec3 A = project(a);\\n  vec3 B = project(b);\\n\\n  return atan(\\n    (B.y - A.y) * resolution.y,\\n    (B.x - A.x) * resolution.x\\n  );\\n}\\n\\nconst float PI = 3.141592;\\nconst float TWO_PI = 2.0 * PI;\\nconst float HALF_PI = 0.5 * PI;\\nconst float ONE_AND_HALF_PI = 1.5 * PI;\\n\\nint option = int(floor(alignOpt.x + 0.001));\\nfloat hv_ratio =       alignOpt.y;\\nbool enableAlign =    (alignOpt.z != 0.0);\\n\\nfloat mod_angle(float a) {\\n  return mod(a, PI);\\n}\\n\\nfloat positive_angle(float a) {\\n  return mod_angle((a < 0.0) ?\\n    a + TWO_PI :\\n    a\\n  );\\n}\\n\\nfloat look_upwards(float a) {\\n  float b = positive_angle(a);\\n  return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n    b - PI :\\n    b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n  // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n  // if ratio is set to 0.5 then it is 50%, 50%.\\n  // when using a higher ratio e.g. 0.75 the result would\\n  // likely be more horizontal than vertical.\\n\\n  float b = positive_angle(a);\\n\\n  return\\n    (b < (      ratio) * HALF_PI) ? 0.0 :\\n    (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n    (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n    (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n                                    0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n  return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n  float b = positive_angle(a);\\n  float div = TWO_PI / float(n);\\n  float c = roundTo(b, div);\\n  return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n  return\\n    (option >  2) ? look_round_n_directions(rawAngle + delta, option) :       // option 3-n: round to n directions\\n    (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n    (option == 1) ? rawAngle + delta :       // use free angle, and flip to align with one direction of the axis\\n    (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n    (option ==-1) ? 0.0 :                    // useful for backward compatibility, all texts remains horizontal\\n                    rawAngle;                // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n                   (axis.y == 0.0) &&\\n                   (axis.z == 0.0);\\n\\nvoid main() {\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n\\n  float beta = angle; // i.e. user defined attributes for each tick\\n\\n  float axisAngle;\\n  float clipAngle;\\n  float flip;\\n\\n  if (enableAlign) {\\n    axisAngle = (isAxisTitle) ? HALF_PI :\\n                      computeViewAngle(dataPosition, dataPosition + axis);\\n    clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n    axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n    clipAngle += (sin(clipAngle) < 0.0) ? 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n=t(\"extract-frustum-planes\"),i=t(\"split-polygon\"),a=t(\"./lib/cube.js\"),o=t(\"gl-mat4/multiply\"),s=t(\"gl-mat4/transpose\"),l=t(\"gl-vec4/transformMat4\"),c=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),u=new Float32Array(16);function f(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var h=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=h,s=p,c=0;c<3;++c)s[c]=o[c]=r[c];s[3]=o[3]=1,s[a]+=1,l(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,l(o,o,e),o[3]<0&&(t[a]=1/0);var u=(o[0]/o[3]-s[0]/s[3])*n,f=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(u*u+f*f)}return t}var g=[new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0)],m=[0,0,0]},{\"./lib/cube.js\":260,\"extract-frustum-planes\":248,\"gl-mat4/multiply\":301,\"gl-mat4/transpose\":312,\"gl-vec4/transformMat4\":432,\"split-polygon\":567}],267:[function(t,e,r){\"use strict\";var n=t(\"typedarray-pool\"),i=t(\"ndarray-ops\"),a=t(\"ndarray\"),o=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"];function s(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}var l=s.prototype;function c(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function u(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a<i;++a)r[a]=t[a];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof t&&void 0!==t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r=\"float32\"),this.type===this.gl.ELEMENT_ARRAY_BUFFER)r=gl.getExtension(\"OES_element_index_uint\")&&\"uint16\"!==r?\"uint32\":\"uint16\";if(r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=c(this.gl,this.type,this.length,this.usage,t.data,e):this.length=c(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=c(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?u(t,\"uint16\"):u(t,\"float32\"),this.length=c(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=c(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof 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r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,c=1/0,u=-1/0,f=1/0,h=-1/0,p=null,d=null,g=[],m=1/0,v=!1,y=0;y<r.length;y++){var x=r[y];s=Math.min(x[0],s),l=Math.max(x[0],l),c=Math.min(x[1],c),u=Math.max(x[1],u),f=Math.min(x[2],f),h=Math.max(x[2],h);var b=i[y];if(n.length(b)>o&&(o=n.length(b)),y){var _=2*n.distance(p,x)/(n.length(d)+n.length(b));_?(m=Math.min(m,_),v=!1):v=!0}v||(p=x,d=b),g.push(b)}var w=[s,c,f],T=[l,u,h];e&&(e[0]=w,e[1]=T),0===o&&(o=1);var k=1/o;isFinite(m)||(m=1),a.vectorScale=m;var A=t.coneSize||.5;t.absoluteConeSize&&(A=t.absoluteConeSize*k),a.coneScale=A;y=0;for(var M=0;y<r.length;y++)for(var S=(x=r[y])[0],E=x[1],L=x[2],C=g[y],P=n.length(C)*k,I=0;I<8;I++){a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vertexIntensity.push(P,P,P),a.vertexIntensity.push(P,P,P);var O=a.positions.length;a.cells.push([O-6,O-5,O-4],[O-3,O-2,O-1])}return a};var i=t(\"./lib/shaders\");e.exports.createMesh=t(\"./create_mesh\"),e.exports.createConeMesh=function(t,r){return e.exports.createMesh(t,r,{shaders:i,traceType:\"cone\"})}},{\"./create_mesh\":269,\"./lib/shaders\":270,\"gl-vec3\":380}],269:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"gl-mat4/multiply\"),l=t(\"gl-mat4/invert\"),c=t(\"ndarray\"),u=t(\"colormap\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e,r,n,i,a,o,s,l,c,u){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=i,this.triangleVectors=a,this.triangleColors=s,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=c,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=u,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=f,this._view=f,this._projection=f,this._resolution=[1,1]}var p=h.prototype;function d(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}function g(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=u({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return c(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,g=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],g=+t.vertexIntensityBounds[1];else for(var m=0;m<p.length;++m){var v=p[m];d=Math.min(d,v),g=Math.max(g,v)}else for(m=0;m<n.length;++m){v=n[m][2];d=Math.min(d,v),g=Math.max(g,v)}this.intensity=p||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(m=0;m<n.length;++m)for(var y=n[m],x=0;x<3;++x)!isNaN(y[x])&&isFinite(y[x])&&(this.bounds[0][x]=Math.min(this.bounds[0][x],y[x]),this.bounds[1][x]=Math.max(this.bounds[1][x],y[x]));var b=0;t:for(m=0;m<r.length;++m){var _=r[m];switch(_.length){case 3:for(x=0;x<3;++x){y=n[T=_[x]];for(var w=0;w<3;++w)if(isNaN(y[w])||!isFinite(y[w]))continue t}for(x=0;x<3;++x){var T;y=n[T=_[2-x]];a.push(y[0],y[1],y[2],y[3]);var k=i[T];o.push(k[0],k[1],k[2],k[3]||0);var A,M=h;3===M.length?s.push(M[0],M[1],M[2],1):s.push(M[0],M[1],M[2],M[3]),A=p?[(p[T]-d)/(g-d),0]:[(y[2]-d)/(g-d),0],l.push(A[0],A[1]),f.push(m)}b+=1}}this.triangleCount=b,this.trianglePositions.update(a),this.triangleVectors.update(o),this.triangleColors.update(s),this.triangleUVs.update(l),this.triangleIds.update(new Uint32Array(f))}},p.drawTransparent=p.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var c={model:r,view:n,projection:i,inverseModel:f.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};c.inverseModel=l(c.inverseModel,c.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);s(u,c.view,c.model),s(u,c.projection,u),l(u,u);for(o=0;o<3;++o)c.eyePosition[o]=u[12+o]/u[15];var h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];c.lightPosition[o]=p/h}if(this.triangleCount>0){var g=this.triShader;g.bind(),g.uniforms=c,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?i.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},e.exports=function(t,e,r){var n=r.shaders;1===arguments.length&&(t=(e=t).gl);var s=d(t,n),l=g(t,n),u=o(t,c(new Uint8Array([255,255,255,255]),[1,1,4]));u.generateMipmap(),u.minFilter=t.LINEAR_MIPMAP_LINEAR,u.magFilter=t.LINEAR;var f=i(t),p=i(t),m=i(t),v=i(t),y=i(t),x=a(t,[{buffer:f,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:m,type:t.FLOAT,size:4},{buffer:v,type:t.FLOAT,size:2},{buffer:p,type:t.FLOAT,size:4}]),b=new h(t,u,s,l,f,p,y,m,v,x,r.traceType||\"cone\");return b.update(e),b}},{colormap:137,\"gl-buffer\":267,\"gl-mat4/invert\":299,\"gl-mat4/multiply\":301,\"gl-shader\":339,\"gl-texture2d\":356,\"gl-vao\":361,ndarray:483}],270:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * conePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(conePosition, 1.0);\\n  vec4 t_position  = view * conePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = conePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n  gl_Position = projection * view * conePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, 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r=0;r<3;++r)t[0][r]=Math.min(t[0][r],e[r]),t[1][r]=Math.max(t[1][r],e[r])}l.isOpaque=function(){return!this.hasAlpha},l.isTransparent=function(){return this.hasAlpha},l.drawTransparent=l.draw=function(t){var e=this.gl,r=this.shader.uniforms;this.shader.bind();var n=r.view=t.view||o,i=r.projection=t.projection||o;r.model=t.model||o,r.clipBounds=this.clipBounds,r.opacity=this.opacity;var a=n[12],s=n[13],l=n[14],c=n[15],u=(t._ortho||!1?2:1)*this.pixelRatio*(i[3]*a+i[7]*s+i[11]*l+i[15]*c)/e.drawingBufferHeight;this.vao.bind();for(var f=0;f<3;++f)e.lineWidth(this.lineWidth[f]*this.pixelRatio),r.capSize=this.capSize[f]*u,this.lineCount[f]&&e.drawArrays(e.LINES,this.lineOffset[f],this.lineCount[f]);this.vao.unbind()};var u=function(){for(var t=new Array(3),e=0;e<3;++e){for(var r=[],n=1;n<=2;++n)for(var i=-1;i<=1;i+=2){var a=[0,0,0];a[(n+e)%3]=i,r.push(a)}t[e]=r}return t}();function f(t,e,r,n){for(var i=u[n],a=0;a<i.length;++a){var 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t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function d(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var d=0;d<i;++d)this.color[d]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var g=this,m=[0|e,0|r];Object.defineProperties(m,{0:{get:function(){return g._shape[0]},set:function(t){return g.width=t}},1:{get:function(){return g._shape[1]},set:function(t){return g.height=t}}}),this._shapeVector=m,function(t){var e=c(t.gl),r=t.gl,n=t.handle=r.createFramebuffer(),i=t._shape[0],a=t._shape[1],o=t.color.length,s=t._ext,d=t._useStencil,g=t._useDepth,m=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,n);for(var v=0;v<o;++v)t.color[v]=h(r,i,a,m,r.RGBA,r.COLOR_ATTACHMENT0+v);0===o?(t._color_rb=p(r,i,a,r.RGBA4,r.COLOR_ATTACHMENT0),s&&s.drawBuffersWEBGL(l[0])):o>1&&s.drawBuffersWEBGL(l[o]);var y=r.getExtension(\"WEBGL_depth_texture\");y?d?t.depth=h(r,i,a,y.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g&&(t.depth=h(r,i,a,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):g&&d?t._depth_rb=p(r,i,a,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g?t._depth_rb=p(r,i,a,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,i,a,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null);for(v=0;v<t.color.length;++v)t.color[v].dispose(),t.color[v]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),u(r,e),f(x)}u(r,e)}(this)}var g=d.prototype;function m(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,i=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=c(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),u(n,a),f(s)),u(n,a)}}Object.defineProperties(g,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return m(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return m(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,m(this,this._shape[0],t),t},enumerable:!1}}),g.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},g.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":356}],277:[function(t,e,r){var n=t(\"sprintf-js\").sprintf,i=t(\"gl-constants/lookup\"),a=t(\"glsl-shader-name\"),o=t(\"add-line-numbers\");e.exports=function(t,e,r){\"use strict\";var s=a(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===i.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var c=n(\"Error compiling %s shader %s:\\n\",l,s),u=n(\"%s%s\",c,t),f=t.split(\"\\n\"),h={},p=0;p<f.length;p++){var d=f[p];if(\"\"!==d&&\"\\0\"!==d){var g=parseInt(d.split(\":\")[2]);if(isNaN(g))throw new Error(n(\"Could not parse error: %s\",d));h[g]=d}}var m=o(e).split(\"\\n\");for(p=0;p<m.length;p++)if(h[p+3]||h[p+2]||h[p+1]){var v=m[p];if(c+=v+\"\\n\",h[p+1]){var y=h[p+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),c+=n(\"^^^ %s\\n\\n\",y)}}return{long:c.trim(),short:u.trim()}}},{\"add-line-numbers\":72,\"gl-constants/lookup\":272,\"glsl-shader-name\":434,\"sprintf-js\":568}],278:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=t.gl,n=o(r,l.vertex,l.fragment),i=o(r,l.pickVertex,l.pickFragment),a=s(r),u=s(r),f=s(r),h=s(r),p=new c(t,n,i,a,u,f,h);return p.update(e),t.addObject(p),p};var n=t(\"binary-search-bounds\"),i=t(\"iota-array\"),a=t(\"typedarray-pool\"),o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"./lib/shaders\");function c(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var u,f=c.prototype,h=[0,0,1,0,0,1,1,0,1,1,0,1];f.draw=(u=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var i=t.gl,a=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=a[2]-a[0],c=a[3]-a[1];u[0]=2*o/l,u[4]=2*s/c,u[6]=2*(r[0]-a[0])/l-1,u[7]=2*(r[1]-a[1])/c-1,e.bind();var f=e.uniforms;f.viewTransform=u,f.shape=this.shape;var h=e.attributes;this.positionBuffer.bind(),h.position.pointer(),this.weightBuffer.bind(),h.weight.pointer(i.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),h.color.pointer(i.UNSIGNED_BYTE,!0),i.drawArrays(i.TRIANGLES,0,n)}}),f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,c=a[2]-a[0],u=a[3]-a[1],f=l[2]-l[0],h=l[3]-l[1];t[0]=2*c/f,t[4]=2*u/h,t[6]=2*(a[0]-l[0])/f-1,t[7]=2*(a[1]-l[1])/h-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var g=i.attributes;return this.positionBuffer.bind(),g.position.pointer(),this.weightBuffer.bind(),g.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),g.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r<n||r>=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var c,u,f,p,d=t.colorLevels||[0],g=t.colorValues||[0,0,0,1],m=d.length,v=this.bounds;l?(c=v[0]=r[0],u=v[1]=o[0],f=v[2]=r[r.length-1],p=v[3]=o[o.length-1]):(c=v[0]=r[0]+(r[1]-r[0])/2,u=v[1]=o[0]+(o[1]-o[0])/2,f=v[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=v[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var y=1/(f-c),x=1/(p-u),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),A=a.mallocUint8(2*w),M=a.mallocUint32(w),S=0,E=l?b-1:b,L=l?_-1:_,C=0;C<L;++C){var P,I;l?(P=x*(o[C]-u),I=x*(o[C+1]-u)):(P=C<_-1?x*(o[C]-(o[C+1]-o[C])/2-u):x*(o[C]-(o[C]-o[C-1])/2-u),I=C<_-1?x*(o[C]+(o[C+1]-o[C])/2-u):x*(o[C]+(o[C]-o[C-1])/2-u));for(var O=0;O<E;++O){var z,D;l?(z=y*(r[O]-c),D=y*(r[O+1]-c)):(z=O<b-1?y*(r[O]-(r[O+1]-r[O])/2-c):y*(r[O]-(r[O]-r[O-1])/2-c),D=O<b-1?y*(r[O]+(r[O+1]-r[O])/2-c):y*(r[O]+(r[O]-r[O-1])/2-c));for(var R=0;R<h.length;R+=2){var F,B,N,j,U=h[R],V=h[R+1],q=s[l?(C+V)*b+(O+U):C*b+O],H=n.le(d,q);if(H<0)F=g[0],B=g[1],N=g[2],j=g[3];else if(H===m-1)F=g[4*m-4],B=g[4*m-3],N=g[4*m-2],j=g[4*m-1];else{var G=(q-d[H])/(d[H+1]-d[H]),Y=1-G,W=4*H,X=4*(H+1);F=Y*g[W]+G*g[X],B=Y*g[W+1]+G*g[X+1],N=Y*g[W+2]+G*g[X+2],j=Y*g[W+3]+G*g[X+3]}T[4*S]=255*F,T[4*S+1]=255*B,T[4*S+2]=255*N,T[4*S+3]=255*j,k[2*S]=.5*z+.5*D,k[2*S+1]=.5*P+.5*I,A[2*S]=U,A[2*S+1]=V,M[S]=C*b+O,S+=1}}}this.positionBuffer.update(k),this.weightBuffer.update(A),this.colorBuffer.update(T),this.idBuffer.update(M),a.free(k),a.free(T),a.free(A),a.free(M)},f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":279,\"binary-search-bounds\":103,\"gl-buffer\":267,\"gl-shader\":339,\"iota-array\":451,\"typedarray-pool\":617}],279:[function(t,e,r){\"use strict\";var n=t(\"glslify\");e.exports={fragment:n([\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\"]),vertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 color;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  fragColor = color;\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"]),pickFragment:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nuniform vec2 shape;\\nuniform vec4 pickOffset;\\n\\nvoid main() {\\n  vec2 d = step(.5, vWeight);\\n  vec4 id = fragId + pickOffset;\\n  id.x += d.x + d.y*shape.x;\\n\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  gl_FragColor = id/255.;\\n}\\n\"]),pickVertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nvoid main() {\\n  vWeight = weight;\\n\\n  fragId = pickId;\\n\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"])}},{glslify:442}],280:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  vec4 startPoint = project(position);\\n  vec4 endPoint   = project(nextPosition);\\n\\n  vec2 A = startPoint.xy / startPoint.w;\\n  vec2 B =   endPoint.xy /   endPoint.w;\\n\\n  float clipAngle = atan(\\n    (B.y - A.y) * screenShape.y,\\n    (B.x - A.x) * screenShape.x\\n  );\\n\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\\n    sin(clipAngle),\\n    -cos(clipAngle)\\n  ) / screenShape;\\n\\n  gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\\nvec4 packFloat(float v) {\\n  float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  float e = floor(log2(av));\\n  float m = av * pow(2.0, -e) - 1.0;\\n\\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n\\n  //Unpack exponent\\n  float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0;\\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n  gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return i(t,a,o,null,l)},r.createPickShader=function(t){return i(t,a,s,null,l)}},{\"gl-shader\":339,glslify:282}],281:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),u=c(new Array(1024),[256,1,4]),p=0;p<1024;++p)u.data[p]=255;var d=a(e,u);d.wrap=e.REPEAT;var g=new v(e,r,o,s,l,d);return g.update(t),g};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"gl-texture2d\"),o=new Uint8Array(4),s=new Float32Array(o.buffer);var l=t(\"binary-search-bounds\"),c=t(\"ndarray\"),u=t(\"./lib/shaders\"),f=u.createShader,h=u.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function g(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function m(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function v(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var y=v.prototype;y.isTransparent=function(){return this.hasAlpha},y.isOpaque=function(){return!this.hasAlpha},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:g(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:g(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var i=[],a=[],o=[],s=0,u=0,f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],h=t.position||t.positions;if(h){var p=t.color||t.colors||[0,0,0,1],g=t.lineWidth||1,m=!1;t:for(e=1;e<h.length;++e){var v,y,x,b=h[e-1],_=h[e];for(a.push(s),o.push(b.slice()),r=0;r<3;++r){if(isNaN(b[r])||isNaN(_[r])||!isFinite(b[r])||!isFinite(_[r])){if(!n&&i.length>0){for(var w=0;w<24;++w)i.push(i[i.length-12]);u+=2,m=!0}continue t}f[0][r]=Math.min(f[0][r],b[r],_[r]),f[1][r]=Math.max(f[1][r],b[r],_[r])}Array.isArray(p[0])?(v=p.length>e-1?p[e-1]:p.length>0?p[p.length-1]:[0,0,0,1],y=p.length>e?p[e]:p.length>0?p[p.length-1]:[0,0,0,1]):v=y=p,3===v.length&&(v=[v[0],v[1],v[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]),!this.hasAlpha&&v[3]<1&&(this.hasAlpha=!0),x=Array.isArray(g)?g.length>e-1?g[e-1]:g.length>0?g[g.length-1]:[0,0,0,1]:g;var T=s;if(s+=d(b,_),m){for(r=0;r<2;++r)i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,v[0],v[1],v[2],v[3]);u+=2,m=!1}i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,v[0],v[1],v[2],v[3],b[0],b[1],b[2],_[0],_[1],_[2],T,-x,v[0],v[1],v[2],v[3],_[0],_[1],_[2],b[0],b[1],b[2],s,-x,y[0],y[1],y[2],y[3],_[0],_[1],_[2],b[0],b[1],b[2],s,x,y[0],y[1],y[2],y[3]),u+=4}}if(this.buffer.update(i),a.push(s),o.push(h[h.length-1].slice()),this.bounds=f,this.vertexCount=u,this.points=o,this.arcLength=a,\"dashes\"in t){var k=t.dashes.slice();for(k.unshift(0),e=1;e<k.length;++e)k[e]=k[e-1]+k[e];var A=c(new Array(1024),[256,1,4]);for(e=0;e<256;++e){for(r=0;r<4;++r)A.set(e,0,r,0);1&l.le(k,k[k.length-1]*e/255)?A.set(e,0,0,0):A.set(e,0,0,255)}this.texture.setPixels(A)}},y.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=function(t,e,r,n){return o[0]=n,o[1]=r,o[2]=e,o[3]=t,s[0]}(t.value[0],t.value[1],t.value[2],0),r=l.le(this.arcLength,e);if(r<0)return null;if(r===this.arcLength.length-1)return new m(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],a=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),c=1-a,u=[0,0,0],f=0;f<3;++f)u[f]=c*n[f]+a*i[f];var h=Math.min(a<.5?r:r+1,this.points.length-1);return new m(e,u,h,this.points[h])}},{\"./lib/shaders\":280,\"binary-search-bounds\":103,\"gl-buffer\":267,\"gl-texture2d\":356,\"gl-vao\":361,ndarray:483}],282:[function(t,e,r){arguments[4][265][0].apply(r,arguments)},{dup:265}],283:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],f=e[9],h=e[10],p=e[11],d=e[12],g=e[13],m=e[14],v=e[15];return t[0]=s*(h*v-p*m)-f*(l*v-c*m)+g*(l*p-c*h),t[1]=-(n*(h*v-p*m)-f*(i*v-a*m)+g*(i*p-a*h)),t[2]=n*(l*v-c*m)-s*(i*v-a*m)+g*(i*c-a*l),t[3]=-(n*(l*p-c*h)-s*(i*p-a*h)+f*(i*c-a*l)),t[4]=-(o*(h*v-p*m)-u*(l*v-c*m)+d*(l*p-c*h)),t[5]=r*(h*v-p*m)-u*(i*v-a*m)+d*(i*p-a*h),t[6]=-(r*(l*v-c*m)-o*(i*v-a*m)+d*(i*c-a*l)),t[7]=r*(l*p-c*h)-o*(i*p-a*h)+u*(i*c-a*l),t[8]=o*(f*v-p*g)-u*(s*v-c*g)+d*(s*p-c*f),t[9]=-(r*(f*v-p*g)-u*(n*v-a*g)+d*(n*p-a*f)),t[10]=r*(s*v-c*g)-o*(n*v-a*g)+d*(n*c-a*s),t[11]=-(r*(s*p-c*f)-o*(n*p-a*f)+u*(n*c-a*s)),t[12]=-(o*(f*m-h*g)-u*(s*m-l*g)+d*(s*h-l*f)),t[13]=r*(f*m-h*g)-u*(n*m-i*g)+d*(n*h-i*f),t[14]=-(r*(s*m-l*g)-o*(n*m-i*g)+d*(n*l-i*s)),t[15]=r*(s*h-l*f)-o*(n*h-i*f)+u*(n*l-i*s),t}},{}],284:[function(t,e,r){e.exports=function(t){var e=new Float32Array(16);return 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r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,c=r*o,u=n*o,f=n*s,h=i*o,p=i*s,d=i*l,g=a*o,m=a*s,v=a*l;return t[0]=1-f-d,t[1]=u+v,t[2]=h-m,t[3]=0,t[4]=u-v,t[5]=1-c-d,t[6]=p+g,t[7]=0,t[8]=h+m,t[9]=p-g,t[10]=1-c-f,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],289:[function(t,e,r){e.exports=function(t,e,r){var n,i,a,o=r[0],s=r[1],l=r[2],c=Math.sqrt(o*o+s*s+l*l);if(Math.abs(c)<1e-6)return null;return o*=c=1/c,s*=c,l*=c,n=Math.sin(e),i=Math.cos(e),a=1-i,t[0]=o*o*a+i,t[1]=s*o*a+l*n,t[2]=l*o*a-s*n,t[3]=0,t[4]=o*s*a-l*n,t[5]=s*s*a+i,t[6]=l*s*a+o*n,t[7]=0,t[8]=o*l*a+s*n,t[9]=s*l*a-o*n,t[10]=l*l*a+i,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],290:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=n+n,l=i+i,c=a+a,u=n*s,f=n*l,h=n*c,p=i*l,d=i*c,g=a*c,m=o*s,v=o*l,y=o*c;return t[0]=1-(p+g),t[1]=f+y,t[2]=h-v,t[3]=0,t[4]=f-y,t[5]=1-(u+g),t[6]=d+m,t[7]=0,t[8]=h+v,t[9]=d-m,t[10]=1-(u+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}},{}],291:[function(t,e,r){e.exports=function(t,e){return t[0]=e[0],t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=e[1],t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=e[2],t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],292:[function(t,e,r){e.exports=function(t,e){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=e[0],t[13]=e[1],t[14]=e[2],t[15]=1,t}},{}],293:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=n,t[6]=r,t[7]=0,t[8]=0,t[9]=-r,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],294:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=0,t[2]=-r,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=r,t[9]=0,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],295:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=r,t[2]=0,t[3]=0,t[4]=-r,t[5]=n,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],296:[function(t,e,r){e.exports=function(t,e,r,n,i,a,o){var s=1/(r-e),l=1/(i-n),c=1/(a-o);return t[0]=2*a*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=2*a*l,t[6]=0,t[7]=0,t[8]=(r+e)*s,t[9]=(i+n)*l,t[10]=(o+a)*c,t[11]=-1,t[12]=0,t[13]=0,t[14]=o*a*2*c,t[15]=0,t}},{}],297:[function(t,e,r){e.exports=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],298:[function(t,e,r){e.exports={create:t(\"./create\"),clone:t(\"./clone\"),copy:t(\"./copy\"),identity:t(\"./identity\"),transpose:t(\"./transpose\"),invert:t(\"./invert\"),adjoint:t(\"./adjoint\"),determinant:t(\"./determinant\"),multiply:t(\"./multiply\"),translate:t(\"./translate\"),scale:t(\"./scale\"),rotate:t(\"./rotate\"),rotateX:t(\"./rotateX\"),rotateY:t(\"./rotateY\"),rotateZ:t(\"./rotateZ\"),fromRotation:t(\"./fromRotation\"),fromRotationTranslation:t(\"./fromRotationTranslation\"),fromScaling:t(\"./fromScaling\"),fromTranslation:t(\"./fromTranslation\"),fromXRotation:t(\"./fromXRotation\"),fromYRotation:t(\"./fromYRotation\"),fromZRotation:t(\"./fromZRotation\"),fromQuat:t(\"./fromQuat\"),frustum:t(\"./frustum\"),perspective:t(\"./perspective\"),perspectiveFromFieldOfView:t(\"./perspectiveFromFieldOfView\"),ortho:t(\"./ortho\"),lookAt:t(\"./lookAt\"),str:t(\"./str\")}},{\"./adjoint\":283,\"./clone\":284,\"./copy\":285,\"./create\":286,\"./determinant\":287,\"./fromQuat\":288,\"./fromRotation\":289,\"./fromRotationTranslation\":290,\"./fromScaling\":291,\"./fromTranslation\":292,\"./fromXRotation\":293,\"./fromYRotation\":294,\"./fromZRotation\":295,\"./frustum\":296,\"./identity\":297,\"./invert\":299,\"./lookAt\":300,\"./multiply\":301,\"./ortho\":302,\"./perspective\":303,\"./perspectiveFromFieldOfView\":304,\"./rotate\":305,\"./rotateX\":306,\"./rotateY\":307,\"./rotateZ\":308,\"./scale\":309,\"./str\":310,\"./translate\":311,\"./transpose\":312}],299:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],f=e[9],h=e[10],p=e[11],d=e[12],g=e[13],m=e[14],v=e[15],y=r*s-n*o,x=r*l-i*o,b=r*c-a*o,_=n*l-i*s,w=n*c-a*s,T=i*c-a*l,k=u*g-f*d,A=u*m-h*d,M=u*v-p*d,S=f*m-h*g,E=f*v-p*g,L=h*v-p*m,C=y*L-x*E+b*S+_*M-w*A+T*k;if(!C)return null;return C=1/C,t[0]=(s*L-l*E+c*S)*C,t[1]=(i*E-n*L-a*S)*C,t[2]=(g*T-m*w+v*_)*C,t[3]=(h*w-f*T-p*_)*C,t[4]=(l*M-o*L-c*A)*C,t[5]=(r*L-i*M+a*A)*C,t[6]=(m*b-d*T-v*x)*C,t[7]=(u*T-h*b+p*x)*C,t[8]=(o*E-s*M+c*k)*C,t[9]=(n*M-r*E-a*k)*C,t[10]=(d*w-g*b+v*y)*C,t[11]=(f*b-u*w-p*y)*C,t[12]=(s*A-o*S-l*k)*C,t[13]=(r*S-n*A+i*k)*C,t[14]=(g*x-d*_-m*y)*C,t[15]=(u*_-f*x+h*y)*C,t}},{}],300:[function(t,e,r){var n=t(\"./identity\");e.exports=function(t,e,r,i){var a,o,s,l,c,u,f,h,p,d,g=e[0],m=e[1],v=e[2],y=i[0],x=i[1],b=i[2],_=r[0],w=r[1],T=r[2];if(Math.abs(g-_)<1e-6&&Math.abs(m-w)<1e-6&&Math.abs(v-T)<1e-6)return n(t);f=g-_,h=m-w,p=v-T,d=1/Math.sqrt(f*f+h*h+p*p),a=x*(p*=d)-b*(h*=d),o=b*(f*=d)-y*p,s=y*h-x*f,(d=Math.sqrt(a*a+o*o+s*s))?(a*=d=1/d,o*=d,s*=d):(a=0,o=0,s=0);l=h*s-p*o,c=p*a-f*s,u=f*o-h*a,(d=Math.sqrt(l*l+c*c+u*u))?(l*=d=1/d,c*=d,u*=d):(l=0,c=0,u=0);return t[0]=a,t[1]=l,t[2]=f,t[3]=0,t[4]=o,t[5]=c,t[6]=h,t[7]=0,t[8]=s,t[9]=u,t[10]=p,t[11]=0,t[12]=-(a*g+o*m+s*v),t[13]=-(l*g+c*m+u*v),t[14]=-(f*g+h*m+p*v),t[15]=1,t}},{\"./identity\":297}],301:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],g=e[12],m=e[13],v=e[14],y=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*f+w*g,t[1]=x*i+b*l+_*h+w*m,t[2]=x*a+b*c+_*p+w*v,t[3]=x*o+b*u+_*d+w*y,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*f+w*g,t[5]=x*i+b*l+_*h+w*m,t[6]=x*a+b*c+_*p+w*v,t[7]=x*o+b*u+_*d+w*y,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*f+w*g,t[9]=x*i+b*l+_*h+w*m,t[10]=x*a+b*c+_*p+w*v,t[11]=x*o+b*u+_*d+w*y,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*f+w*g,t[13]=x*i+b*l+_*h+w*m,t[14]=x*a+b*c+_*p+w*v,t[15]=x*o+b*u+_*d+w*y,t}},{}],302:[function(t,e,r){e.exports=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),c=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*c,t[15]=1,t}},{}],303:[function(t,e,r){e.exports=function(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}},{}],304:[function(t,e,r){e.exports=function(t,e,r,n){var i=Math.tan(e.upDegrees*Math.PI/180),a=Math.tan(e.downDegrees*Math.PI/180),o=Math.tan(e.leftDegrees*Math.PI/180),s=Math.tan(e.rightDegrees*Math.PI/180),l=2/(o+s),c=2/(i+a);return t[0]=l,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=c,t[6]=0,t[7]=0,t[8]=-(o-s)*l*.5,t[9]=(i-a)*c*.5,t[10]=n/(r-n),t[11]=-1,t[12]=0,t[13]=0,t[14]=n*r/(r-n),t[15]=0,t}},{}],305:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,A,M,S,E=n[0],L=n[1],C=n[2],P=Math.sqrt(E*E+L*L+C*C);if(Math.abs(P)<1e-6)return null;E*=P=1/P,L*=P,C*=P,i=Math.sin(r),a=Math.cos(r),o=1-a,s=e[0],l=e[1],c=e[2],u=e[3],f=e[4],h=e[5],p=e[6],d=e[7],g=e[8],m=e[9],v=e[10],y=e[11],x=E*E*o+a,b=L*E*o+C*i,_=C*E*o-L*i,w=E*L*o-C*i,T=L*L*o+a,k=C*L*o+E*i,A=E*C*o+L*i,M=L*C*o-E*i,S=C*C*o+a,t[0]=s*x+f*b+g*_,t[1]=l*x+h*b+m*_,t[2]=c*x+p*b+v*_,t[3]=u*x+d*b+y*_,t[4]=s*w+f*T+g*k,t[5]=l*w+h*T+m*k,t[6]=c*w+p*T+v*k,t[7]=u*w+d*T+y*k,t[8]=s*A+f*M+g*S,t[9]=l*A+h*M+m*S,t[10]=c*A+p*M+v*S,t[11]=u*A+d*M+y*S,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t}},{}],306:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[4],o=e[5],s=e[6],l=e[7],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[4]=a*i+c*n,t[5]=o*i+u*n,t[6]=s*i+f*n,t[7]=l*i+h*n,t[8]=c*i-a*n,t[9]=u*i-o*n,t[10]=f*i-s*n,t[11]=h*i-l*n,t}},{}],307:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i-c*n,t[1]=o*i-u*n,t[2]=s*i-f*n,t[3]=l*i-h*n,t[8]=a*n+c*i,t[9]=o*n+u*i,t[10]=s*n+f*i,t[11]=l*n+h*i,t}},{}],308:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[4],u=e[5],f=e[6],h=e[7];e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i+c*n,t[1]=o*i+u*n,t[2]=s*i+f*n,t[3]=l*i+h*n,t[4]=c*i-a*n,t[5]=u*i-o*n,t[6]=f*i-s*n,t[7]=h*i-l*n,t}},{}],309:[function(t,e,r){e.exports=function(t,e,r){var n=r[0],i=r[1],a=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*i,t[5]=e[5]*i,t[6]=e[6]*i,t[7]=e[7]*i,t[8]=e[8]*a,t[9]=e[9]*a,t[10]=e[10]*a,t[11]=e[11]*a,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t}},{}],310:[function(t,e,r){e.exports=function(t){return\"mat4(\"+t[0]+\", \"+t[1]+\", \"+t[2]+\", \"+t[3]+\", \"+t[4]+\", \"+t[5]+\", \"+t[6]+\", \"+t[7]+\", \"+t[8]+\", \"+t[9]+\", \"+t[10]+\", \"+t[11]+\", \"+t[12]+\", \"+t[13]+\", \"+t[14]+\", \"+t[15]+\")\"}},{}],311:[function(t,e,r){e.exports=function(t,e,r){var n,i,a,o,s,l,c,u,f,h,p,d,g=r[0],m=r[1],v=r[2];e===t?(t[12]=e[0]*g+e[4]*m+e[8]*v+e[12],t[13]=e[1]*g+e[5]*m+e[9]*v+e[13],t[14]=e[2]*g+e[6]*m+e[10]*v+e[14],t[15]=e[3]*g+e[7]*m+e[11]*v+e[15]):(n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],t[0]=n,t[1]=i,t[2]=a,t[3]=o,t[4]=s,t[5]=l,t[6]=c,t[7]=u,t[8]=f,t[9]=h,t[10]=p,t[11]=d,t[12]=n*g+s*m+f*v+e[12],t[13]=i*g+l*m+h*v+e[13],t[14]=a*g+c*m+p*v+e[14],t[15]=o*g+u*m+d*v+e[15]);return t}},{}],312:[function(t,e,r){e.exports=function(t,e){if(t===e){var r=e[1],n=e[2],i=e[3],a=e[6],o=e[7],s=e[11];t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=r,t[6]=e[9],t[7]=e[13],t[8]=n,t[9]=a,t[11]=e[14],t[12]=i,t[13]=o,t[14]=s}else t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},{}],313:[function(t,e,r){\"use strict\";var n=t(\"barycentric\"),i=t(\"polytope-closest-point/lib/closest_point_2d.js\");function a(t,e){for(var r=[0,0,0,0],n=0;n<4;++n)for(var i=0;i<4;++i)r[i]+=t[4*n+i]*e[n];return r}function o(t,e,r,n,i){for(var o=a(n,a(r,a(e,[t[0],t[1],t[2],1]))),s=0;s<3;++s)o[s]/=o[3];return[.5*i[0]*(1+o[0]),.5*i[1]*(1-o[1])]}function s(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var i=t[n],a=e[n],o=0;o<3;++o)r[o]+=a*i[o];return r}e.exports=function(t,e,r,a,l,c){if(1===t.length)return[0,t[0].slice()];for(var u=new Array(t.length),f=0;f<t.length;++f)u[f]=o(t[f],r,a,l,c);var h=0,p=1/0;for(f=0;f<u.length;++f){for(var d=0,g=0;g<2;++g)d+=Math.pow(u[f][g]-e[g],2);d<p&&(p=d,h=f)}var m=function(t,e){if(2===t.length){for(var r=0,a=0,o=0;o<2;++o)r+=Math.pow(e[o]-t[0][o],2),a+=Math.pow(e[o]-t[1][o],2);return r=Math.sqrt(r),a=Math.sqrt(a),r+a<1e-6?[1,0]:[a/(r+a),r/(a+r)]}if(3===t.length){var s=[0,0];return i(t[0],t[1],t[2],e,s),n(t,s)}return[]}(u,e),v=0;for(f=0;f<3;++f){if(m[f]<-.001||m[f]>1.0001)return null;v+=m[f]}if(Math.abs(v-1)>.001)return null;return[h,s(t,m),m]}},{barycentric:85,\"polytope-closest-point/lib/closest_point_2d.js\":512}],314:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection\\n           , inverseModel;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  gl_Position      = project(position);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * vec4(position , 1.0);\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal  = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  f_color          = color;\\n  f_data           = position;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (f_color.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], f_data)\\n  ) discard;\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:l,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},{glslify:442}],315:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"normals\"),l=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/invert\"),u=t(\"ndarray\"),f=t(\"colormap\"),h=t(\"simplicial-complex-contour\"),p=t(\"typedarray-pool\"),d=t(\"./lib/shaders\"),g=t(\"./lib/closest-point\"),m=d.meshShader,v=d.wireShader,y=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,T,k,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=u,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=c,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=m,this.edgeUVs=v,this.edgeIds=g,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function A(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function M(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function S(t){var e=n(t,v.vertex,v.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function E(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function L(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function C(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function P(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var c=r[l],u=0;u<2;++u){var f=c[0];2===c.length&&(f=c[u]);for(var d=n[f][0],g=n[f][1],m=i[f],v=1-m,y=this.positions[d],x=this.positions[g],b=0;b<3;++b)o[s++]=m*y[b]+v*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},k.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=f({colormap:t,nshades:256,format:\"rgba\"}),n=new Uint8Array(1024),i=0;i<256;++i){for(var a=r[i],o=0;o<3;++o)n[4*i+o]=a[o];n[4*i+3]=e?255*A(i/255,e):255*a[3]}return u(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var i=[],a=[],l=[],c=[],h=[],p=[],d=[],g=[],m=[],v=[],y=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,T=t.cellNormals,k=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,M=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=s.faceNormals(r,n,M)),T||w||(w=s.vertexNormals(r,n,k));var S=t.vertexColors,E=t.cellColors,L=t.meshColor||[1,1,1,1],C=t.vertexUVs,P=t.vertexIntensity,I=t.cellUVs,O=t.cellIntensity,z=1/0,D=-1/0;if(!C&&!I)if(P)if(t.vertexIntensityBounds)z=+t.vertexIntensityBounds[0],D=+t.vertexIntensityBounds[1];else for(var R=0;R<P.length;++R){var F=P[R];z=Math.min(z,F),D=Math.max(D,F)}else if(O)if(t.cellIntensityBounds)z=+t.cellIntensityBounds[0],D=+t.cellIntensityBounds[1];else for(R=0;R<O.length;++R){F=O[R];z=Math.min(z,F),D=Math.max(D,F)}else for(R=0;R<n.length;++R){F=n[R][2];z=Math.min(z,F),D=Math.max(D,F)}this.intensity=P||(O||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n)),this.pickVertex=!(O||E);var B=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(R=0;R<n.length;++R)for(var j=n[R],U=0;U<3;++U)!isNaN(j[U])&&isFinite(j[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],j[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],j[U]));var V=0,q=0,H=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[W=G[0]],U=0;U<3;++U)if(isNaN(j[U])||!isFinite(j[U]))continue t;v.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[W]-z)/(D-z),this.opacityscale)):3===X.length?y.push(X[0],X[1],X[2],this.opacity):(y.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],x.push(Z[0],Z[1]),B?b.push(B[W]):b.push(N),_.push(R),H+=1;break;case 2:for(U=0;U<2;++U){j=n[W=G[U]];for(var Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t}for(U=0;U<2;++U){j=n[W=G[U]];p.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[W]-z)/(D-z),this.opacityscale)):3===X.length?d.push(X[0],X[1],X[2],this.opacity):(d.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],g.push(Z[0],Z[1]),m.push(R)}q+=1;break;case 3:for(U=0;U<3;++U)for(j=n[W=G[U]],Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t;for(U=0;U<3;++U){var W,X,Z,J;j=n[W=G[2-U]];i.push(j[0],j[1],j[2]),(X=S?S[W]:E?E[R]:L)?this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[W]-z)/(D-z),this.opacityscale)):3===X.length?a.push(X[0],X[1],X[2],this.opacity):(a.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)):a.push(.5,.5,.5,1),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],c.push(Z[0],Z[1]),J=w?w[W]:T[R],l.push(J[0],J[1],J[2]),h.push(R)}V+=1}}this.pointCount=H,this.edgeCount=q,this.triangleCount=V,this.pointPositions.update(v),this.pointColors.update(y),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(g),this.edgeIds.update(new Uint32Array(m)),this.trianglePositions.update(i),this.triangleColors.update(a),this.triangleUVs.update(c),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(h))}},k.drawTransparent=k.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:w.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=c(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);l(u,s.view,s.model),l(u,s.projection,u),c(u,u);for(o=0;o<3;++o)s.eyePosition[o]=u[12+o]/u[15];var f,h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/h}this.triangleCount>0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind());this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind());this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind());this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};((s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0)&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=t.coord[0],s=t.coord[1];if(!this.pickVertex){var l=this.positions[r[0]],c=this.positions[r[1]],u=this.positions[r[2]],f=[(l[0]+c[0]+u[0])/3,(l[1]+c[1]+u[1])/3,(l[2]+c[2]+u[2])/3];return{_cellCenter:!0,position:[o,s],index:e,cell:r,cellId:e,intensity:this.intensity[e],dataCoordinate:f}}var h=g(i,[o*this.pixelRatio,this._resolution[1]-s*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!h)return null;var p=h[2],d=0;for(a=0;a<r.length;++a)d+=p[a]*this.intensity[r[a]];return{position:h[1],index:r[h[0]],cell:r,cellId:e,intensity:d,dataCoordinate:this.positions[r[h[0]]]}},k.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=function(t,e){1===arguments.length&&(t=(e=t).gl);var r=t.getExtension(\"OES_standard_derivatives\")||t.getExtension(\"MOZ_OES_standard_derivatives\")||t.getExtension(\"WEBKIT_OES_standard_derivatives\");if(!r)throw new Error(\"derivatives not supported\");var n=M(t),s=S(t),l=E(t),c=L(t),f=C(t),h=P(t),p=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=i(t),g=i(t),m=i(t),v=i(t),y=i(t),x=a(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:g,type:t.FLOAT,size:4},{buffer:m,type:t.FLOAT,size:2},{buffer:v,type:t.FLOAT,size:3}]),b=i(t),_=i(t),w=i(t),k=i(t),A=a(t,[{buffer:b,type:t.FLOAT,size:3},{buffer:k,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:_,type:t.FLOAT,size:4},{buffer:w,type:t.FLOAT,size:2}]),I=i(t),O=i(t),z=i(t),D=i(t),R=i(t),F=a(t,[{buffer:I,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:O,type:t.FLOAT,size:4},{buffer:z,type:t.FLOAT,size:2},{buffer:D,type:t.FLOAT,size:1}]),B=i(t),N=a(t,[{buffer:B,type:t.FLOAT,size:3}]),j=new T(t,p,n,s,l,c,f,h,d,y,g,m,v,x,b,k,_,w,A,I,R,O,z,D,F,B,N);return j.update(e),j}},{\"./lib/closest-point\":313,\"./lib/shaders\":314,colormap:137,\"gl-buffer\":267,\"gl-mat4/invert\":299,\"gl-mat4/multiply\":301,\"gl-shader\":339,\"gl-texture2d\":356,\"gl-vao\":361,ndarray:483,normals:486,\"simplicial-complex-contour\":557,\"typedarray-pool\":617}],316:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[0,0,0,1,1,0,1,1]),s=i(e,a.boxVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,i){var a=this.plot,o=this.shader,c=a.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=i,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":319,\"gl-buffer\":267,\"gl-shader\":339}],317:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,o.gridVert,o.gridFrag),l=i(e,o.tickVert,o.gridFrag);return new s(t,r,a,l)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"binary-search-bounds\"),o=t(\"./shaders\");function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var c,u,f,h,p,d=s.prototype;d.draw=(c=[0,0],u=[0,0],f=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,i=t.gl,a=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,h=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,g=0;g<2;++g){var m=a[g],v=a[g+2]-m,y=.5*(o[g+2]+o[g]),x=o[g+2]-o[g];u[g]=2*v/x,c[g]=2*(m-y)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=c,r.uniforms.dataScale=u;var b=0;for(g=0;g<2;++g){f[0]=f[1]=0,f[g]=1,r.uniforms.dataAxis=f,r.uniforms.lineWidth=l[g]/(s[g+2]-s[g])*d,r.uniforms.color=h[g];var _=6*n[g].length;p[g]&&_&&i.drawArrays(i.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],i=[0,0],o=[0,0];return function(){for(var s=this.plot,c=this.vbo,u=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,g=s.viewBox,m=s.pixelRatio,v=s.screenBox,y=v[2]-v[0],x=v[3]-v[1],b=g[2]-g[0],_=g[3]-g[1],w=0;w<2;++w){var T=p[w],k=p[w+2]-T,A=.5*(d[w+2]+d[w]),M=d[w+2]-d[w];e[w]=2*k/M,t[w]=2*(T-A)/M}e[0]*=b/y,t[0]*=b/y,e[1]*=_/x,t[1]*=_/x,u.bind(),c.bind(),u.attributes.dataCoord.pointer();var S=u.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,L=s.tickMarkWidth,C=s.tickMarkColor,P=6*f[0].length,I=Math.min(a.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),l),f[0].length),O=Math.min(a.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),l),f[0].length),z=0+6*I,D=6*Math.max(0,O-I),R=Math.min(a.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),l),f[1].length),F=Math.min(a.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),l),f[1].length),B=P+6*R,N=6*Math.max(0,F-R);i[0]=2*(g[0]-E[1])/y-1,i[1]=(g[3]+g[1])/x-1,o[0]=E[1]*m/y,o[1]=L[1]*m/x,N&&(S.color=C[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(g[2]+g[0])/y-1,i[1]=2*(g[1]-E[0])/x-1,o[0]=L[0]*m/y,o[1]=E[0]*m/x,D&&(S.color=C[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,z,D)),i[0]=2*(g[2]+E[3])/y-1,i[1]=(g[3]+g[1])/x-1,o[0]=E[3]*m/y,o[1]=L[3]*m/x,N&&(S.color=C[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(g[2]+g[0])/y-1,i[1]=2*(g[3]+E[2])/x-1,o[0]=L[2]*m/y,o[1]=E[2]*m/x,D&&(S.color=C[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,z,D))}}(),d.update=(h=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),i=(this.plot.zeroLineEnable,0),a=[[],[]],o=0;o<2;++o)for(var s=a[o],l=e[o],c=r[o],u=r[o+2],f=0;f<l.length;++f){var d=(l[f].x-c)/(u-c);s.push(d);for(var g=0;g<6;++g)n[i++]=d,n[i++]=h[g],n[i++]=p[g]}this.ticks=a,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{\"./shaders\":319,\"binary-search-bounds\":103,\"gl-buffer\":267,\"gl-shader\":339}],318:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[-1,-1,-1,1,1,-1,1,1]),s=i(e,a.lineVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,i,a){var o=this.plot,c=this.shader,u=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,c.uniforms.start=s,c.uniforms.end=l,c.uniforms.width=i*o.pixelRatio,c.uniforms.color=a,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":319,\"gl-buffer\":267,\"gl-shader\":339}],319:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\"]);e.exports={lineVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n  return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  vec2 delta = normalize(perp(start - end));\\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\"]),lineFrag:i,textVert:n([\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n  float dataOffset  = textCoordinate.z;\\n  vec2 glyphOffset  = textCoordinate.xy;\\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n    glyphMatrix * glyphOffset * textScale + screenOffset;\\n  gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\"]),textFrag:i,gridVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n  gl_Position = vec4(pos, 0, 1);\\n}\\n\"]),gridFrag:i,boxVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\"]),tickVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"])}},{glslify:321}],320:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,s.textVert,s.textFrag);return new l(t,r,a)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"text-cache\"),o=t(\"binary-search-bounds\"),s=t(\"./shaders\");function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var c,u,f,h,p,d,g=l.prototype;g.drawTicks=(c=[0,0],u=[0,0],f=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],i=this.tickOffset[t],a=e.gl,s=e.viewBox,l=e.dataBox,h=e.screenBox,p=e.pixelRatio,d=e.tickEnable,g=e.tickPad,m=e.tickColor,v=e.tickAngle,y=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],T=this.labelCount[t],k=o.lt(n,l[t]),A=o.le(n,l[t+2]);c[0]=c[1]=0,c[t]=1,u[t]=(s[2+t]+s[t])/(h[2+t]-h[t])-1;var M=2/h[2+(1^t)]-h[1^t];u[1^t]=M*s[1^t]-1,d[t]&&(u[1^t]-=M*p*g[t],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=m[t],r.uniforms.angle=v[t],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),y[t]&&T&&(u[1^t]-=M*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),u[1^t]=M*s[2+(1^t)]-1,d[t+2]&&(u[1^t]+=M*p*g[t+2],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=m[t+2],r.uniforms.angle=v[t+2],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),y[t+2]&&T&&(u[1^t]+=M*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),g.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,c=r.pixelRatio;if(this.titleCount){for(var u=0;u<2;++u)e[u]=2*(o[u]*c-a[u])/(a[2+u]-a[u])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),g.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,c=.5*(n[o+2]+n[o]),u=n[o+2]-n[o],f=a[o],g=a[o+2]-f,m=i[o],v=i[o+2]-m;p[o]=2*l/u*g/v,h[o]=2*(s-c)/u*g/v}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),g.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,c=t.bounds;for(o=0;o<2;++o){var u=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e<h.length;++e){var p=h[e],d=p.x,g=p.text,m=p.font||\"sans-serif\";i=p.fontSize||12;for(var v=1/(c[o+2]-c[o]),y=c[o],x=g.split(\"\\n\"),b=0;b<x.length;b++)for(n=a(m,x[b]).data,r=0;r<n.length;r+=2)s.push(n[r]*i,-n[r+1]*i-b*i*1.2,(d-y)*v);u.push(Math.floor(s.length/3)),f.push(d)}this.tickOffset[o]=u,this.tickX[o]=f}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=a(t.labelFont[o],t.labels[o],{textAlign:\"center\"}).data,i=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=a(t.titleFont,t.title).data,i=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},g.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":319,\"binary-search-bounds\":103,\"gl-buffer\":267,\"gl-shader\":339,\"text-cache\":596}],321:[function(t,e,r){arguments[4][265][0].apply(r,arguments)},{dup:265}],322:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[e.drawingBufferWidth,e.drawingBufferHeight]),c=new l(e,r);return c.grid=i(c),c.text=a(c),c.line=o(c),c.box=s(c),c.update(t),c};var n=t(\"gl-select-static\"),i=t(\"./lib/grid\"),a=t(\"./lib/text\"),o=t(\"./lib/line\"),s=t(\"./lib/box\");function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var c=l.prototype;function u(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function f(t,e){return t.x-e.x}c.setDirty=function(){this.dirty=this.pickDirty=!0},c.setOverlayDirty=function(){this.dirty=!0},c.nextDepthValue=function(){return this._depthCounter++/65536},c.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var c=this.borderColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var u=this.backgroundColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;d<2;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var g=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(g,e[1],g,e[3],p[d],h[d]):o.drawLine(e[0],g,e[2],g,p[d],h[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var m=this.borderLineEnable,v=this.borderLineWidth,y=this.borderLineColor;for(m[1]&&o.drawLine(r[0],r[1]-.5*v[1]*i,r[0],r[3]+.5*v[3]*i,v[1],y[1]),m[0]&&o.drawLine(r[0]-.5*v[0]*i,r[1],r[2]+.5*v[2]*i,r[1],v[0],y[0]),m[3]&&o.drawLine(r[2],r[1]-.5*v[1]*i,r[2],r[3]+.5*v[3]*i,v[3],y[3]),m[2]&&o.drawLine(r[0]-.5*v[0]*i,r[3],r[2]+.5*v[2]*i,r[3],v[2],y[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},c.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl,this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},c.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),c=this.objects,u=0;u<c.length;++u){var f=c[u].pick(a,o,l);if(f)return f}return null}},c.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},c.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},c.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},c.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,i=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/i,10,10/i]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=u(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=u(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=u(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t)||!!t.titleEnable,this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=u(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=u(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=u(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var a=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=a[s].slice(0);0!==l.length&&(l.sort(f),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:a}),this.text.update({bounds:o,ticks:a,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.static=!!t.static,this.setDirty()},c.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},c.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},c.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},c.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},c.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":316,\"./lib/grid\":317,\"./lib/line\":318,\"./lib/text\":320,\"gl-select-static\":338}],323:[function(t,e,r){\"use strict\";e.exports=function(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];\"distanceLimits\"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]);\"zoomMin\"in e&&(r[0]=e.zoomMin);\"zoomMax\"in e&&(r[1]=e.zoomMax);var c=i({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),u=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],f=0,h=t.clientWidth,p=t.clientHeight,d={keyBindingMode:\"rotate\",enableWheel:!0,view:c,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:c.modes,_ortho:e._ortho||e.projection&&\"orthographic\"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,i=e-2*r;c.idle(e-r),c.recalcMatrix(i),c.flush(e-(100+2*r));for(var a=!0,o=c.computedMatrix,s=0;s<16;++s)a=a&&u[s]===o[s],u[s]=o[s];var l=t.clientWidth===h&&t.clientHeight===p;return h=t.clientWidth,p=t.clientHeight,a?!l:(f=Math.exp(c.computedRadius[0]),!0)},lookAt:function(t,e,r){c.lookAt(c.lastT(),t,e,r)},rotate:function(t,e,r){c.rotate(c.lastT(),t,e,r)},pan:function(t,e,r){c.pan(c.lastT(),t,e,r)},translate:function(t,e,r){c.translate(c.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return c.computedMatrix},set:function(t){return c.setMatrix(c.lastT(),t),c.computedMatrix},enumerable:!0},mode:{get:function(){return c.getMode()},set:function(t){var e=c.computedUp.slice(),r=c.computedEye.slice(),i=c.computedCenter.slice();if(c.setMode(t),\"turntable\"===t){var a=n();c._active.lookAt(a,r,i,e),c._active.lookAt(a+500,r,i,[0,0,1]),c._active.flush(a)}return c.getMode()},enumerable:!0},center:{get:function(){return c.computedCenter},set:function(t){return c.lookAt(c.lastT(),null,t),c.computedCenter},enumerable:!0},eye:{get:function(){return c.computedEye},set:function(t){return c.lookAt(c.lastT(),t),c.computedEye},enumerable:!0},up:{get:function(){return c.computedUp},set:function(t){return c.lookAt(c.lastT(),null,null,t),c.computedUp},enumerable:!0},distance:{get:function(){return f},set:function(t){return c.setDistance(c.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return c.getDistanceLimits(r)},set:function(t){return c.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",(function(t){return t.preventDefault(),!1})),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,i,a){var o=d.keyBindingMode;if(!1!==o){var s=\"rotate\"===o,l=\"pan\"===o,u=\"zoom\"===o,h=!!a.control,p=!!a.alt,g=!!a.shift,m=!!(1&e),v=!!(2&e),y=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(i-d._lastY),w=d.flipX?1:-1,T=d.flipY?1:-1,k=Math.PI*d.rotateSpeed,A=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&m&&!h&&!p&&!g||m&&!h&&!p&&g)&&c.rotate(A,w*k*b,-T*k*_,0),(l&&m&&!h&&!p&&!g||v||m&&h&&!p&&!g)&&c.pan(A,-d.translateSpeed*b*f,d.translateSpeed*_*f,0),u&&m&&!h&&!p&&!g||y||m&&!h&&p&&!g)){var M=-d.zoomSpeed*_/window.innerHeight*(A-c.lastT())*100;c.pan(A,0,0,f*(Math.exp(M)-1))}return d._lastX=r,d._lastY=i,d._lastMods=a,!0}}d.mouseListener=a(t,e),t.addEventListener(\"touchstart\",(function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods)}),!!l&&{passive:!0}),t.addEventListener(\"touchmove\",(function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()}),!!l&&{passive:!1}),t.addEventListener(\"touchend\",(function(t){e(0,d._lastX,d._lastY,d._lastMods)}),!!l&&{passive:!0}),d.wheelListener=o(t,(function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,i=d.flipY?1:-1,a=n();if(Math.abs(t)>Math.abs(e))c.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-c.lastT())/20;c.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=t(\"right-now\"),i=t(\"3d-view\"),a=t(\"mouse-change\"),o=t(\"mouse-wheel\"),s=t(\"mouse-event-offset\"),l=t(\"has-passive-events\")},{\"3d-view\":55,\"has-passive-events\":444,\"mouse-change\":470,\"mouse-event-offset\":471,\"mouse-wheel\":473,\"right-now\":542}],324:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n  uv = position;\\n  gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n  vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n  gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},{\"gl-shader\":339,glslify:325}],325:[function(t,e,r){arguments[4][265][0].apply(r,arguments)},{dup:265}],326:[function(t,e,r){\"use strict\";var n=t(\"./camera.js\"),i=t(\"gl-axes3d\"),a=t(\"gl-axes3d/properties\"),o=t(\"gl-spikes3d\"),s=t(\"gl-select-static\"),l=t(\"gl-fbo\"),c=t(\"a-big-triangle\"),u=t(\"mouse-change\"),f=t(\"gl-mat4/perspective\"),h=t(\"gl-mat4/ortho\"),p=t(\"./lib/shader\"),d=t(\"is-mobile\")({tablet:!0,featureDetect:!0});function g(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function m(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}if(e>0){r=Math.round(Math.pow(10,e));return Math.ceil(t/r)*r}return Math.ceil(t)}function v(t){return\"boolean\"!=typeof t||t}e.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;if(!e){if(e=document.createElement(\"canvas\"),t.container)t.container.appendChild(e);else document.body.appendChild(e)}var r=t.gl;r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d}));if(!r)throw new Error(\"webgl not supported\");var y=t.bounds||[[-10,-10,-10],[10,10,10]],x=new g,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:w},k=t.axes||{},A=i(r,k);A.enable=!k.disable;var M=t.spikes||{},S=o(r,M),E=[],L=[],C=[],P=[],I=!0,O=!0,z=new Array(16),D=new Array(16),R={view:null,projection:z,model:D,_ortho:!1},F=(O=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),B=t.cameraObject||n(e,T),N={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:B,axes:A,axesPixels:null,spikes:S,bounds:y,objects:E,shape:F,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:v(t.autoResize),autoBounds:v(t.autoBounds),autoScale:!!t.autoScale,autoCenter:v(t.autoCenter),clipToBounds:v(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:R,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,O=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},j=[r.drawingBufferWidth/N.pixelRatio|0,r.drawingBufferHeight/N.pixelRatio|0];function U(){if(!N._stopped&&N.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*N.pixelRatio),a=0|Math.ceil(n*N.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",I=!0}}}N.autoResize&&U();function V(){for(var t=E.length,e=P.length,n=0;n<e;++n)C[n]=0;t:for(n=0;n<t;++n){var i=E[n],a=i.pickSlots;if(a){for(var o=0;o<e;++o)if(C[o]+a<255){L[n]=o,i.setPickBase(C[o]+1),C[o]+=a;continue t}var l=s(r,F);L[n]=e,P.push(l),C.push(a),i.setPickBase(1),e+=1}else L[n]=-1}for(;e>0&&0===C[e-1];)C.pop(),P.pop().dispose()}function q(){if(N.contextLost)return!0;r.isContextLost()&&(N.contextLost=!0,N.mouseListener.enabled=!1,N.selection.object=null,N.oncontextloss&&N.oncontextloss())}window.addEventListener(\"resize\",U),N.update=function(t){N._stopped||(t=t||{},I=!0,O=!0)},N.add=function(t){N._stopped||(t.axes=A,E.push(t),L.push(-1),I=!0,O=!0,V())},N.remove=function(t){if(!N._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),L.pop(),I=!0,O=!0,V())}},N.dispose=function(){if(!N._stopped&&(N._stopped=!0,window.removeEventListener(\"resize\",U),e.removeEventListener(\"webglcontextlost\",q),N.mouseListener.enabled=!1,!N.contextLost)){A.dispose(),S.dispose();for(var t=0;t<E.length;++t)E[t].dispose();b.dispose();for(t=0;t<P.length;++t)P[t].dispose();_.dispose(),r=null,A=null,S=null,E=[]}},N._mouseRotating=!1,N._prevButtons=0,N.enableMouseListeners=function(){N.mouseListener=u(e,(function(t,e,r){if(!N._stopped){var n=P.length,i=E.length,a=x.object;x.distance=1/0,x.mouse[0]=e,x.mouse[1]=r,x.object=null,x.screen=null,x.dataCoordinate=x.dataPosition=null;var o=!1;if(t&&N._prevButtons)N._mouseRotating=!0;else{N._mouseRotating&&(O=!0),N._mouseRotating=!1;for(var s=0;s<n;++s){var l=P[s].query(e,j[1]-r-1,N.pickRadius);if(l){if(l.distance>x.distance)continue;for(var c=0;c<i;++c){var u=E[c];if(L[c]===s){var f=u.pick(l);f&&(x.buttons=t,x.screen=l.coord,x.distance=l.distance,x.object=u,x.index=f.distance,x.dataPosition=f.position,x.dataCoordinate=f.dataCoordinate,x.data=f,o=!0)}}}}}a&&a!==x.object&&(a.highlight&&a.highlight(null),I=!0),x.object&&(x.object.highlight&&x.object.highlight(x.data),I=!0),(o=o||x.object!==a)&&N.onselect&&N.onselect(x),1&t&&!(1&N._prevButtons)&&N.onclick&&N.onclick(x),N._prevButtons=t}}))},e.addEventListener(\"webglcontextlost\",q);var H=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],G=[H[0].slice(),H[1].slice()];function Y(){if(!q()){U();var t=N.camera.tick();R.view=N.camera.matrix,I=I||t,O=O||t,A.pixelRatio=N.pixelRatio,S.pixelRatio=N.pixelRatio;var e=E.length,n=H[0],i=H[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-1/0;for(var o=0;o<e;++o){(C=E[o]).pixelRatio=N.pixelRatio,C.axes=N.axes,I=I||!!C.dirty,O=O||!!C.dirty;var s=C.bounds;if(s)for(var l=s[0],u=s[1],p=0;p<3;++p)n[p]=Math.min(n[p],l[p]),i[p]=Math.max(i[p],u[p])}var d=N.bounds;if(N.autoBounds)for(p=0;p<3;++p){if(i[p]<n[p])n[p]=-1,i[p]=1;else{n[p]===i[p]&&(n[p]-=1,i[p]+=1);var g=.05*(i[p]-n[p]);n[p]=n[p]-g,i[p]=i[p]+g}d[0][p]=n[p],d[1][p]=i[p]}var v=!1;for(p=0;p<3;++p)v=v||G[0][p]!==d[0][p]||G[1][p]!==d[1][p],G[0][p]=d[0][p],G[1][p]=d[1][p];if(O=O||v,I=I||v){if(v){var y=[0,0,0];for(o=0;o<3;++o)y[o]=m((d[1][o]-d[0][o])/10);A.autoTicks?A.update({bounds:d,tickSpacing:y}):A.update({bounds:d})}var T=r.drawingBufferWidth,k=r.drawingBufferHeight;F[0]=T,F[1]=k,j[0]=0|Math.max(T/N.pixelRatio,1),j[1]=0|Math.max(k/N.pixelRatio,1),function(t,e){var r=t.bounds,n=t.cameraParams,i=n.projection,a=n.model,o=t.gl.drawingBufferWidth,s=t.gl.drawingBufferHeight,l=t.zNear,c=t.zFar,u=t.fovy,p=o/s;e?(h(i,-p,p,-1,1,l,c),n._ortho=!0):(f(i,u,p,l,c),n._ortho=!1);for(var d=0;d<16;++d)a[d]=0;a[15]=1;var g=0;for(d=0;d<3;++d)g=Math.max(g,r[1][d]-r[0][d]);for(d=0;d<3;++d)t.autoScale?a[5*d]=t.aspect[d]/(r[1][d]-r[0][d]):a[5*d]=1/g,t.autoCenter&&(a[12+d]=.5*-a[5*d]*(r[0][d]+r[1][d]))}(N,w);for(o=0;o<e;++o){(C=E[o]).axesBounds=d,N.clipToBounds&&(C.clipBounds=d)}x.object&&(N.snapToData?S.position=x.dataCoordinate:S.position=x.dataPosition,S.bounds=d),O&&(O=!1,function(){if(!q()){r.colorMask(!0,!0,!0,!0),r.depthMask(!0),r.disable(r.BLEND),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL);for(var t=E.length,e=P.length,n=0;n<e;++n){var i=P[n];i.shape=j,i.begin();for(var a=0;a<t;++a)if(L[a]===n){var o=E[a];o.drawPick&&(o.pixelRatio=1,o.drawPick(R))}i.end()}}}()),N.axesPixels=a(N.axes,R,T,k),N.onrender&&N.onrender(),r.bindFramebuffer(r.FRAMEBUFFER,null),r.viewport(0,0,T,k),N.clearRGBA(),r.depthMask(!0),r.colorMask(!0,!0,!0,!0),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL),r.disable(r.BLEND),r.disable(r.CULL_FACE);var M=!1;A.enable&&(M=M||A.isTransparent(),A.draw(R)),S.axes=A,x.object&&S.draw(R),r.disable(r.CULL_FACE);for(o=0;o<e;++o){(C=E[o]).axes=A,C.pixelRatio=N.pixelRatio,C.isOpaque&&C.isOpaque()&&C.draw(R),C.isTransparent&&C.isTransparent()&&(M=!0)}if(M){b.shape=F,b.bind(),r.clear(r.DEPTH_BUFFER_BIT),r.colorMask(!1,!1,!1,!1),r.depthMask(!0),r.depthFunc(r.LESS),A.enable&&A.isTransparent()&&A.drawTransparent(R);for(o=0;o<e;++o){(C=E[o]).isOpaque&&C.isOpaque()&&C.draw(R)}r.enable(r.BLEND),r.blendEquation(r.FUNC_ADD),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.colorMask(!0,!0,!0,!0),r.depthMask(!1),r.clearColor(0,0,0,0),r.clear(r.COLOR_BUFFER_BIT),A.isTransparent()&&A.drawTransparent(R);for(o=0;o<e;++o){var C;(C=E[o]).isTransparent&&C.isTransparent()&&C.drawTransparent(R)}r.bindFramebuffer(r.FRAMEBUFFER,null),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.disable(r.DEPTH_TEST),_.bind(),b.color[0].bind(0),_.uniforms.accumBuffer=0,c(r),r.disable(r.BLEND)}I=!1;for(o=0;o<e;++o)E[o].dirty=!1}}}return N.enableMouseListeners(),function t(){if(N._stopped||N.contextLost)return;Y(),requestAnimationFrame(t)}(),N.redraw=function(){N._stopped||(I=!0,Y())},N},createCamera:n}},{\"./camera.js\":323,\"./lib/shader\":324,\"a-big-triangle\":70,\"gl-axes3d\":258,\"gl-axes3d/properties\":266,\"gl-fbo\":276,\"gl-mat4/ortho\":302,\"gl-mat4/perspective\":303,\"gl-select-static\":338,\"gl-spikes3d\":349,\"is-mobile\":455,\"mouse-change\":470}],327:[function(t,e,r){var n=t(\"glslify\");r.pointVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n  highp float a = 12.9898;\\n  highp float b = 78.233;\\n  highp float c = 43758.5453;\\n  highp float d = dot(co.xy, vec2(a, b));\\n  highp float e = mod(d, 3.14);\\n  return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n    // if we don't jitter the point size a bit, overall point cloud\\n    // saturation 'jumps' on zooming, which is disturbing and confusing\\n  gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    // get the same square surface as circle would be\\n    gl_PointSize *= 0.886;\\n  }\\n}\"]),r.pointFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n  float radius;\\n  vec4 baseColor;\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    if(centerFraction == 1.0) {\\n      gl_FragColor = color;\\n    } else {\\n      gl_FragColor = mix(borderColor, color, centerFraction);\\n    }\\n  } else {\\n    radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n    if(radius > 1.0) {\\n      discard;\\n    }\\n    baseColor = mix(borderColor, color, step(radius, centerFraction));\\n    gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n  }\\n}\\n\"]),r.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\"]),r.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"])},{glslify:442}],328:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"typedarray-pool\"),o=t(\"./lib/shader\");function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}e.exports=function(t,e){var r=t.gl,a=i(r),l=i(r),c=n(r,o.pointVertex,o.pointFragment),u=n(r,o.pickVertex,o.pickFragment),f=new s(t,a,l,c,u);return f.update(e),t.addObject(f),f};var l,c,u=s.prototype;u.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},u.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),c=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e<n;e++)c[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(c),i||a.free(l),o||a.free(c),this.pointCount=n,this.pickOffset=0},u.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],c=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,i=this.plot.dataBox;if(0===this.pointCount)return t;var a=i[2]-i[0],o=i[3]-i[1],s=function(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),u=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=u<5,r.uniforms.pointSize=u,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(c[0]=255&t,c[1]=t>>8&255,c[2]=t>>16&255,c[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=c,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),u.draw=u.unifiedDraw,u.drawPick=u.unifiedDraw,u.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":327,\"gl-buffer\":267,\"gl-shader\":339,\"typedarray-pool\":617}],329:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c=e[0],u=e[1],f=e[2],h=e[3],p=r[0],d=r[1],g=r[2],m=r[3];(a=c*p+u*d+f*g+h*m)<0&&(a=-a,p=-p,d=-d,g=-g,m=-m);1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n);return t[0]=s*c+l*p,t[1]=s*u+l*d,t[2]=s*f+l*g,t[3]=s*h+l*m,t}},{}],330:[function(t,e,r){\"use strict\";e.exports=function(t){return t||0===t?t.toString():\"\"}},{}],331:[function(t,e,r){\"use strict\";var n=t(\"vectorize-text\");e.exports=function(t,e,r){var a=i[e];a||(a=i[e]={});if(t in a)return a[t];var o={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,c,u=n(t,o);if(r&&1!==r){for(l=0;l<s.positions.length;++l)for(c=0;c<s.positions[l].length;++c)s.positions[l][c]/=r;for(l=0;l<u.positions.length;++l)for(c=0;c<u.positions[l].length;++c)u.positions[l][c]/=r}var f=[[1/0,1/0],[-1/0,-1/0]],h=u.positions.length;for(l=0;l<h;++l){var p=u.positions[l];for(c=0;c<2;++c)f[0][c]=Math.min(f[0][c],p[c]),f[1][c]=Math.max(f[1][c],p[c])}return a[t]=[s,u,f]};var i={}},{\"vectorize-text\":623}],332:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n\\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (\\n    outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n    interpColor.a * opacity == 0.\\n  ) discard;\\n  gl_FragColor = interpColor * opacity;\\n}\\n\"]),c=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n  gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),u=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:u},h={vertex:o,fragment:l,attributes:u},p={vertex:s,fragment:l,attributes:u},d={vertex:a,fragment:c,attributes:u},g={vertex:o,fragment:c,attributes:u},m={vertex:s,fragment:c,attributes:u};function v(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}r.createPerspective=function(t){return v(t,f)},r.createOrtho=function(t){return v(t,h)},r.createProject=function(t){return v(t,p)},r.createPickPerspective=function(t){return v(t,d)},r.createPickOrtho=function(t){return v(t,g)},r.createPickProject=function(t){return v(t,m)}},{\"gl-shader\":339,glslify:333}],333:[function(t,e,r){arguments[4][265][0].apply(r,arguments)},{dup:265}],334:[function(t,e,r){\"use strict\";var n=t(\"is-string-blank\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"typedarray-pool\"),s=t(\"gl-mat4/multiply\"),l=t(\"./lib/shaders\"),c=t(\"./lib/glyphs\"),u=t(\"./lib/get-simple-string\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function g(t){return!0===t||t>1?1:t}function m(t,e,r,n,i,a,o,s,l,c,u,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=u,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}e.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),c=l.createPickOrtho(e),u=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),g=a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),v=new m(e,r,n,o,f,h,p,d,g,s,c,u);return v.update(t),v};var v=m.prototype;v.pickSlots=1,v.setPickBase=function(t){this.pickId=t},v.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},v.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var y=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],A=[[0,0,0],[0,0,0]];function M(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function L(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,c=r.model||f,u=r.view||f,h=r.projection||f,d=e.axesBounds,g=function(t){for(var e=A,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],y[0]=2/o.drawingBufferWidth,y[1]=2/o.drawingBufferHeight,t.bind(),l.view=u,l.projection=h,l.screenSize=y,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=g,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var m=0;m<3;++m)if(a[m]){l.scale=e.projectScale[m],l.opacity=e.projectOpacity[m];for(var v=T,L=0;L<16;++L)v[L]=0;for(L=0;L<4;++L)v[5*L]=1;v[5*m]=0,i[m]<0?v[12+m]=d[0][m]:v[12+m]=d[1][m],s(v,c,v),l.model=v;var C=(m+1)%3,P=(m+2)%3,I=M(x),O=M(b);I[C]=1,O[P]=1;var z=p(0,0,0,S(_,I)),D=p(0,0,0,S(w,O));if(Math.abs(z[1])>Math.abs(D[1])){var R=z;z=D,D=R,R=I,I=O,O=R;var F=C;C=P,P=F}z[0]<0&&(I[C]=-1),D[1]>0&&(O[P]=-1);var B=0,N=0;for(L=0;L<4;++L)B+=Math.pow(c[4*C+L],2),N+=Math.pow(c[4*P+L],2);I[C]/=Math.sqrt(B),O[P]/=Math.sqrt(N),l.axes[0]=I,l.axes[1]=O,l.fragClipBounds[0]=E(k,g[0],m,-1e8),l.fragClipBounds[1]=E(k,g[1],m,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}var C=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function P(t,e,r,n,i,a,o){var s=r.gl;if((a===r.projectHasAlpha||o)&&L(e,r,n,i),a===r.hasAlpha||o){t.bind();var l=t.uniforms;l.model=n.model||f,l.view=n.view||f,l.projection=n.projection||f,y[0]=2/s.drawingBufferWidth,y[1]=2/s.drawingBufferHeight,l.screenSize=y,l.highlightId=r.highlightId,l.highlightScale=r.highlightScale,l.fragClipBounds=C,l.clipBounds=r.axes.bounds,l.opacity=r.opacity,l.pickGroup=r.pickId/255,l.pixelRatio=i,r.vao.bind(),r.vao.draw(s.TRIANGLES,r.vertexCount),r.lineWidth>0&&(s.lineWidth(r.lineWidth*i),r.vao.draw(s.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function I(t,e,r,i){var a;a=Array.isArray(t)?e<t.length?t[e]:void 0:t,a=u(a);var o=!0;n(a)&&(a=\"\\u25bc\",o=!1);var s=c(a,r,i);return{mesh:s[0],lines:s[1],bounds:s[2],visible:o}}v.draw=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!1,!1)},v.drawTransparent=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!0,!1)},v.drawPick=function(t){P(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,1,!0,!0)},v.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},v.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},v.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,\"projectOpacity\"in t){if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{r=+t.projectOpacity;this.projectOpacity=[r,r,r]}for(var n=0;n<3;++n)this.projectOpacity[n]=g(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=g(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var i,a,s=t.position,l=t.font||\"normal\",c=t.alignment||[0,0];if(2===c.length)i=c[0],a=c[1];else{i=[],a=[];for(n=0;n<c.length;++n)i[n]=c[n][0],a[n]=c[n][1]}var u=[1/0,1/0,1/0],f=[-1/0,-1/0,-1/0],h=t.glyph,p=t.color,d=t.size,m=t.angle,v=t.lineColor,y=-1,x=0,b=0,_=0;if(s.length){_=s.length;t:for(n=0;n<_;++n){for(var w=s[n],T=0;T<3;++T)if(isNaN(w[T])||!isFinite(w[T]))continue t;var k=(N=I(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;x+=3*k.cells.length,b+=2*A.edges.length}}var S=x+b,E=o.mallocFloat(3*S),L=o.mallocFloat(4*S),C=o.mallocFloat(2*S),P=o.mallocUint32(S);if(S>0){var O=0,z=x,D=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(v)&&Array.isArray(v[0]);t:for(n=0;n<_;++n){y+=1;for(w=s[n],T=0;T<3;++T){if(isNaN(w[T])||!isFinite(w[T]))continue t;f[T]=Math.max(f[T],w[T]),u[T]=Math.min(u[T],w[T])}k=(N=I(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(U=F?n<p.length?p[n]:[0,0,0,0]:p).length){for(T=0;T<3;++T)D[T]=U[T];D[3]=1}else if(4===U.length){for(T=0;T<4;++T)D[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else D[0]=D[1]=D[2]=0,D[3]=1;else D=[1,1,1,0];if(j)if(Array.isArray(v)){var U;if(3===(U=B?n<v.length?v[n]:[0,0,0,0]:v).length){for(T=0;T<3;++T)R[T]=U[T];R[T]=1}else if(4===U.length){for(T=0;T<4;++T)R[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else R[0]=R[1]=R[2]=0,R[3]=1;else R=[1,1,1,0];var V=.5;j?Array.isArray(d)?V=n<d.length?+d[n]:12:d?V=+d:this.useOrtho&&(V=12):V=0;var q=0;Array.isArray(m)?q=n<m.length?+m[n]:0:m&&(q=+m);var H=Math.cos(q),G=Math.sin(q);for(w=s[n],T=0;T<3;++T)f[T]=Math.max(f[T],w[T]),u[T]=Math.min(u[T],w[T]);var Y=i,W=a;Y=0;Array.isArray(i)?Y=n<i.length?i[n]:0:i&&(Y=i);W=0;Array.isArray(a)?W=n<a.length?a[n]:0:a&&(W=a);var X=[Y*=Y>0?1-M[0][0]:Y<0?1+M[1][0]:1,W*=W>0?1-M[0][1]:W<0?1+M[1][1]:1],Z=k.cells||[],J=k.positions||[];for(T=0;T<Z.length;++T)for(var K=Z[T],Q=0;Q<3;++Q){for(var $=0;$<3;++$)E[3*O+$]=w[$];for($=0;$<4;++$)L[4*O+$]=D[$];P[O]=y;var tt=J[K[Q]];C[2*O]=V*(H*tt[0]-G*tt[1]+X[0]),C[2*O+1]=V*(G*tt[0]+H*tt[1]+X[1]),O+=1}for(Z=A.edges,J=A.positions,T=0;T<Z.length;++T)for(K=Z[T],Q=0;Q<2;++Q){for($=0;$<3;++$)E[3*z+$]=w[$];for($=0;$<4;++$)L[4*z+$]=R[$];P[z]=y;tt=J[K[Q]];C[2*z]=V*(H*tt[0]-G*tt[1]+X[0]),C[2*z+1]=V*(G*tt[0]+H*tt[1]+X[1]),z+=1}}}this.bounds=[u,f],this.points=s,this.pointCount=s.length,this.vertexCount=x,this.lineVertexCount=b,this.pointBuffer.update(E),this.colorBuffer.update(L),this.glyphBuffer.update(C),this.idBuffer.update(P),o.free(E),o.free(L),o.free(C),o.free(P)},v.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/get-simple-string\":330,\"./lib/glyphs\":331,\"./lib/shaders\":332,\"gl-buffer\":267,\"gl-mat4/multiply\":301,\"gl-vao\":361,\"is-string-blank\":458,\"typedarray-pool\":617}],335:[function(t,e,r){\"use strict\";var n=t(\"glslify\");r.boxVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\"]),r.boxFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"])},{glslify:336}],336:[function(t,e,r){arguments[4][265][0].apply(r,arguments)},{dup:265}],337:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"./lib/shaders\");function o(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-1/0,-1/0],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}e.exports=function(t,e){var r=t.gl,s=i(r,[0,0,0,1,1,0,1,1]),l=n(r,a.boxVertex,a.boxFragment),c=new o(t,s,l);return c.update(e),t.addOverlay(c),c};var s=o.prototype;s.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,c=t.viewBox,u=t.pixelRatio,f=(e[0]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],h=(e[1]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1],p=(e[2]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],d=(e[3]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1];if(f=Math.max(f,c[0]),h=Math.max(h,c[1]),p=Math.min(p,c[2]),d=Math.min(d,c[3]),!(p<f||d<h)){o.bind();var g=s[2]-s[0],m=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,g,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,g,m,i),o.drawBox(p,h,g,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var v=r*u;o.drawBox(f-v,h-v,p+v,h+v,a),o.drawBox(f-v,d-v,p+v,d+v,a),o.drawBox(f-v,h-v,f+v,d+v,a),o.drawBox(p-v,h-v,p+v,d+v,a)}}}},s.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},s.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":335,\"gl-buffer\":267,\"gl-shader\":339}],338:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=e[0],a=e[1],o=n(t,r,a,{}),s=i.mallocUint8(r*a*4);return new l(t,o,s)};var n=t(\"gl-fbo\"),i=t(\"typedarray-pool\"),a=t(\"ndarray\"),o=t(\"bit-twiddle\").nextPow2;function s(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function 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a=[t.id,e.id,r.join(\":\"),i.join(\":\")].join(\"@\"),o=this.programs[a];return o&&this.gl.isProgram(o)||(this.programs[a]=o=function(t,e,r,i,a){var o=t.createProgram();t.attachShader(o,e),t.attachShader(o,r);for(var s=0;s<i.length;++s)t.bindAttribLocation(o,a[s],i[s]);if(t.linkProgram(o),!t.getProgramParameter(o,t.LINK_STATUS)){var l=t.getProgramInfoLog(o);throw new n(l,\"Error linking program: \"+l)}return o}(this.gl,t.shader,e.shader,r,i),t.programs.push(a),e.programs.push(a)),o}},{\"./GLError\":340,\"gl-format-compiler-error\":277,\"weakmap-shim\":628}],346:[function(t,e,r){\"use strict\";function n(t){this.plot=t,this.enable=[!0,!0,!1,!1],this.width=[1,1,1,1],this.color=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.center=[1/0,1/0]}e.exports=function(t,e){var r=new n(t);return r.update(e),t.addOverlay(r),r};var 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1\\n\\nattribute vec3 position, color;\\nattribute float weight;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 coordinates[3];\\nuniform vec4 colors[3];\\nuniform vec2 screenShape;\\nuniform float lineWidth;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vertexPosition = mix(coordinates[0],\\n    mix(coordinates[2], coordinates[1], 0.5 * (position + 1.0)), abs(position));\\n\\n  vec4 clipPos = projection * view * model * vec4(vertexPosition, 1.0);\\n  vec2 clipOffset = (projection * view * model * vec4(color, 0.0)).xy;\\n  vec2 delta = weight * clipOffset * screenShape;\\n  vec2 lineOffset = normalize(vec2(delta.y, -delta.x)) / screenShape;\\n\\n  gl_Position   = vec4(clipPos.xy + clipPos.w * 0.5 * lineWidth * lineOffset, clipPos.z, clipPos.w);\\n  fragColor     = color.x * colors[0] + color.y * colors[1] + color.z * colors[2];\\n}\\n\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec3\"},{name:\"weight\",type:\"float\"}])}},{\"gl-shader\":339,glslify:347}],349:[function(t,e,r){\"use strict\";var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders/index\");e.exports=function(t,e){var r=[];function o(t,e,n,i,a,o){var s=[t,e,n,0,0,0,1];s[i+3]=1,s[i]=a,r.push.apply(r,s),s[6]=-1,r.push.apply(r,s),s[i]=o,r.push.apply(r,s),r.push.apply(r,s),s[6]=1,r.push.apply(r,s),s[i]=a,r.push.apply(r,s)}o(0,0,0,0,0,1),o(0,0,0,1,0,1),o(0,0,0,2,0,1),o(1,0,0,1,-1,1),o(1,0,0,2,-1,1),o(0,1,0,0,-1,1),o(0,1,0,2,-1,1),o(0,0,1,0,-1,1),o(0,0,1,1,-1,1);var l=n(t,r),c=i(t,[{type:t.FLOAT,buffer:l,size:3,offset:0,stride:28},{type:t.FLOAT,buffer:l,size:3,offset:12,stride:28},{type:t.FLOAT,buffer:l,size:1,offset:24,stride:28}]),u=a(t);u.attributes.position.location=0,u.attributes.color.location=1,u.attributes.weight.location=2;var f=new s(t,l,c,u);return f.update(e),f};var o=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function s(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n,this.pixelRatio=1,this.bounds=[[-1e3,-1e3,-1e3],[1e3,1e3,1e3]],this.position=[0,0,0],this.lineWidth=[2,2,2],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.enabled=[!0,!0,!0],this.drawSides=[!0,!0,!0],this.axes=null}var l=s.prototype,c=[0,0,0],u=[0,0,0],f=[0,0];l.isTransparent=function(){return!1},l.drawTransparent=function(t){},l.draw=function(t){var e=this.gl,r=this.vao,n=this.shader;r.bind(),n.bind();var i,a=t.model||o,s=t.view||o,l=t.projection||o;this.axes&&(i=this.axes.lastCubeProps.axis);for(var h=c,p=u,d=0;d<3;++d)i&&i[d]<0?(h[d]=this.bounds[0][d],p[d]=this.bounds[1][d]):(h[d]=this.bounds[1][d],p[d]=this.bounds[0][d]);f[0]=e.drawingBufferWidth,f[1]=e.drawingBufferHeight,n.uniforms.model=a,n.uniforms.view=s,n.uniforms.projection=l,n.uniforms.coordinates=[this.position,h,p],n.uniforms.colors=this.colors,n.uniforms.screenShape=f;for(d=0;d<3;++d)n.uniforms.lineWidth=this.lineWidth[d]*this.pixelRatio,this.enabled[d]&&(r.draw(e.TRIANGLES,6,6*d),this.drawSides[d]&&r.draw(e.TRIANGLES,12,18+12*d));r.unbind()},l.update=function(t){t&&(\"bounds\"in t&&(this.bounds=t.bounds),\"position\"in t&&(this.position=t.position),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"colors\"in t&&(this.colors=t.colors),\"enabled\"in t&&(this.enabled=t.enabled),\"drawSides\"in t&&(this.drawSides=t.drawSides))},l.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders/index\":348,\"gl-buffer\":267,\"gl-vao\":361}],350:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * tubePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(tubePosition, 1.0);\\n  vec4 t_position  = view * tubePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = tubePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float tubeScale;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  gl_Position = projection * view * tubePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec4\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec4\"}]}},{glslify:351}],351:[function(t,e,r){arguments[4][265][0].apply(r,arguments)},{dup:265}],352:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\"),i=t(\"gl-vec4\"),a=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"],o=function(t,e,r,a){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,c=0;c<l.length;c++)o=Math.max(o,n.length(l[c]));var u=t.map((function(t){return function(t,e,r,a){for(var o=t.points,s=t.velocities,l=t.divergences,c=[],u=[],f=[],h=[],p=[],d=[],g=0,m=0,v=i.create(),y=i.create(),x=0;x<o.length;x++){var b=o[x],_=s[x],w=l[x];0===e&&(w=.05*r),m=n.length(_)/a,v=i.create(),n.copy(v,_),v[3]=w;for(var T=0;T<8;T++)p[T]=[b[0],b[1],b[2],T];if(h.length>0)for(T=0;T<8;T++){var k=(T+1)%8;c.push(h[T],p[T],p[k],p[k],h[k],h[T]),f.push(y,v,v,v,y,y),d.push(g,m,m,m,g,g);var A=c.length;u.push([A-6,A-5,A-4],[A-3,A-2,A-1])}var M=h;h=p,p=M;var S=y;y=v,v=S;var E=g;g=m,m=E}return{positions:c,cells:u,vectors:f,vertexIntensity:d}}(t,r,a,o)})),f=[],h=[],p=[],d=[];for(s=0;s<u.length;s++){var g=u[s],m=f.length;f=f.concat(g.positions),p=p.concat(g.vectors),d=d.concat(g.vertexIntensity);for(c=0;c<g.cells.length;c++){var v=g.cells[c],y=[];h.push(y);for(var x=0;x<v.length;x++)y.push(v[x]+m)}}return{positions:f,cells:h,vectors:p,vertexIntensity:d,colormap:e}},s=function(t,e){var r,n=t.length;for(r=0;r<n;r++){var i=t[r];if(i===e)return r;if(i>e)return r-1}return r},l=function(t,e,r){return t<e?e:t>r?r:t},c=function(t){var e=1/0;t.sort((function(t,e){return t-e}));for(var r=t.length,n=1;n<r;n++){var i=Math.abs(t[n]-t[n-1]);i<e&&(e=i)}return e};e.exports=function(t,e){var r=t.startingPositions,i=t.maxLength||1e3,u=t.tubeSize||1,f=t.absoluteTubeSize,h=t.gridFill||\"+x+y+z\",p={};-1!==h.indexOf(\"-x\")&&(p.reversedX=!0),-1!==h.indexOf(\"-y\")&&(p.reversedY=!0),-1!==h.indexOf(\"-z\")&&(p.reversedZ=!0),p.filled=a.indexOf(h.replace(/-/g,\"\").replace(/\\+/g,\"\"));var d=t.getVelocity||function(e){return function(t,e,r){var i=e.vectors,a=e.meshgrid,o=t[0],c=t[1],u=t[2],f=a[0].length,h=a[1].length,p=a[2].length,d=s(a[0],o),g=s(a[1],c),m=s(a[2],u),v=d+1,y=g+1,x=m+1;if(d=l(d,0,f-1),v=l(v,0,f-1),g=l(g,0,h-1),y=l(y,0,h-1),m=l(m,0,p-1),x=l(x,0,p-1),d<0||g<0||m<0||v>f-1||y>h-1||x>p-1)return n.create();var b,_,w,T,k,A,M=a[0][d],S=a[0][v],E=a[1][g],L=a[1][y],C=a[2][m],P=(o-M)/(S-M),I=(c-E)/(L-E),O=(u-C)/(a[2][x]-C);switch(isFinite(P)||(P=.5),isFinite(I)||(I=.5),isFinite(O)||(O=.5),r.reversedX&&(d=f-1-d,v=f-1-v),r.reversedY&&(g=h-1-g,y=h-1-y),r.reversedZ&&(m=p-1-m,x=p-1-x),r.filled){case 5:k=m,A=x,w=g*p,T=y*p,b=d*p*h,_=v*p*h;break;case 4:k=m,A=x,b=d*p,_=v*p,w=g*p*f,T=y*p*f;break;case 3:w=g,T=y,k=m*h,A=x*h,b=d*h*p,_=v*h*p;break;case 2:w=g,T=y,b=d*h,_=v*h,k=m*h*f,A=x*h*f;break;case 1:b=d,_=v,k=m*f,A=x*f,w=g*f*p,T=y*f*p;break;default:b=d,_=v,w=g*f,T=y*f,k=m*f*h,A=x*f*h}var z=i[b+w+k],D=i[b+w+A],R=i[b+T+k],F=i[b+T+A],B=i[_+w+k],N=i[_+w+A],j=i[_+T+k],U=i[_+T+A],V=n.create(),q=n.create(),H=n.create(),G=n.create();n.lerp(V,z,B,P),n.lerp(q,D,N,P),n.lerp(H,R,j,P),n.lerp(G,F,U,P);var Y=n.create(),W=n.create();n.lerp(Y,V,H,I),n.lerp(W,q,G,I);var X=n.create();return n.lerp(X,Y,W,O),X}(e,t,p)},g=t.getDivergence||function(t,e){var r=n.create(),i=1e-4;n.add(r,t,[i,0,0]);var a=d(r);n.subtract(a,a,e),n.scale(a,a,1/i),n.add(r,t,[0,i,0]);var o=d(r);n.subtract(o,o,e),n.scale(o,o,1/i),n.add(r,t,[0,0,i]);var s=d(r);return n.subtract(s,s,e),n.scale(s,s,1/i),n.add(r,a,o),n.add(r,r,s),r},m=[],v=e[0][0],y=e[0][1],x=e[0][2],b=e[1][0],_=e[1][1],w=e[1][2],T=function(t){var e=t[0],r=t[1],n=t[2];return!(e<v||e>b||r<y||r>_||n<x||n>w)},k=10*n.distance(e[0],e[1])/i,A=k*k,M=1,S=0,E=r.length;E>1&&(M=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=t.length,l=0;l<s;l++){var u=t[l],f=u[0],h=u[1],p=u[2];i[f]||(e.push(f),i[f]=!0),a[h]||(r.push(h),a[h]=!0),o[p]||(n.push(p),o[p]=!0)}var d=c(e),g=c(r),m=c(n),v=Math.min(d,g,m);return isFinite(v)?v:1}(r));for(var L=0;L<E;L++){var C=n.create();n.copy(C,r[L]);var P=[C],I=[],O=d(C),z=C;I.push(O);var D=[],R=g(C,O),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F),m.push({points:P,velocities:I,divergences:D});for(var B=0;B<100*i&&P.length<i&&T(C);){B++;var N=n.clone(O),j=n.squaredLength(N);if(0===j)break;if(j>A&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,C),O=d(N),n.squaredDistance(z,N)-A>-1e-4*A){P.push(N),z=N,I.push(O);R=g(N,O),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F)}C=N}}var U=o(m,t.colormap,S,M);return f?U.tubeScale=f:(0===S&&(S=1),U.tubeScale=.5*u*M/S),U};var u=t(\"./lib/shaders\"),f=t(\"gl-cone3d\").createMesh;e.exports.createTubeMesh=function(t,e){return f(t,e,{shaders:u,traceType:\"streamtube\"})}},{\"./lib/shaders\":350,\"gl-cone3d\":268,\"gl-vec3\":380,\"gl-vec4\":416}],353:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform vec3 objectOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 localCoordinate = vec3(uv.zw, f.x);\\n  worldCoordinate = objectOffset + localCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  kill = f.y;\\n  value = f.z;\\n  planeCoordinate = uv.xy;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat beckmannSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  if (\\n    kill > 0.0 ||\\n    vColor.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\\n  ) discard;\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  //decide how to interpolate color \\u2014 in vertex or in fragment\\n  vec4 surfaceColor =\\n    step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\\n    step(.5, vertexColor) * vColor;\\n\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform vec3 objectOffset;\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n  worldCoordinate = objectOffset + dataCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z += zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = f + objectOffset.z;\\n  kill = -1.0;\\n  planeCoordinate = uv.zw;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Don't do lighting for contours\\n  surfaceNormal   = vec3(1,0,0);\\n  eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if ((kill > 0.0) ||\\n      (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);r.createShader=function(t){var e=n(t,a,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},r.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},{\"gl-shader\":339,glslify:442}],354:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=y(e),n=b(e),s=x(e),l=_(e),c=i(e),u=a(e,[{buffer:c,size:4,stride:40,offset:0},{buffer:c,size:3,stride:40,offset:16},{buffer:c,size:3,stride:40,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),g=o(e,1,256,e.RGBA,e.UNSIGNED_BYTE);g.minFilter=e.LINEAR,g.magFilter=e.LINEAR;var m=new M(e,[0,0],[[0,0,0],[0,0,0]],r,n,c,u,g,s,l,f,h,p,d,[0,0,0]),v={levels:[[],[],[]]};for(var w in t)v[w]=t[w];return v.colormap=v.colormap||\"jet\",m.update(v),m};var n=t(\"bit-twiddle\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"typedarray-pool\"),l=t(\"colormap\"),c=t(\"ndarray-ops\"),u=t(\"ndarray-pack\"),f=t(\"ndarray\"),h=t(\"surface-nets\"),p=t(\"gl-mat4/multiply\"),d=t(\"gl-mat4/invert\"),g=t(\"binary-search-bounds\"),m=t(\"ndarray-gradient\"),v=t(\"./lib/shaders\"),y=v.createShader,x=v.createContourShader,b=v.createPickShader,_=v.createPickContourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],T=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],k=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function A(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=k[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();function M(t,e,r,n,i,a,o,l,c,u,h,p,d,g,m){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=m,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=c,this._contourPickShader=u,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new A([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=g,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var S=M.prototype;S.genColormap=function(t,e){var r=!1,n=u([l({colormap:t,nshades:256,format:\"rgba\"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return c.divseq(n,255),this.hasAlphaScale=r,n},S.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},S.isOpaque=function(){return!this.isTransparent()},S.pickSlots=1,S.setPickBase=function(t){this.pickId=t};var E=[0,0,0],L={showSurface:!1,showContour:!1,projections:[w.slice(),w.slice(),w.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function C(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||E,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=L.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var c=L.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)c[i][n]=t.clipBounds[i][n];c[0][r]=-1e8,c[1][r]=1e8}return L.showSurface=o,L.showContour=s,L}var P={model:w,view:w,projection:w,inverseModel:w.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},I=w.slice(),O=[1,0,0,0,1,0,0,0,1];function z(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=P;n.model=t.model||w,n.view=t.view||w,n.projection=t.projection||w,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=O,n.vertexColor=this.vertexColor;var s=I;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var c=s[12+i];for(o=0;o<3;++o)c+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=c/l}var u=C(n,this);if(u.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=u.projections[i],this._shader.uniforms.clipBounds=u.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(u.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=k[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o<this.contourLevels[i].length;++o)o===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==o&&o-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),this._contourCounts[i][o]&&(f.uniforms.height=this.contourLevels[i][o],h.draw(r.LINES,this._contourCounts[i][o],this._contourOffsets[i][o]));for(i=0;i<3;++i)for(f.uniforms.model=u.projections[i],f.uniforms.clipBounds=u.clipBounds[i],o=0;o<3;++o)if(this.contourProject[i][o]){f.uniforms.permutation=k[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var g=0;g<this.contourLevels[o].length;++g)g===this.highlightLevel[o]?(f.uniforms.contourColor=this.highlightColor[o],f.uniforms.contourTint=this.highlightTint[o]):0!==g&&g-1!==this.highlightLevel[o]||(f.uniforms.contourColor=this.contourColor[o],f.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][g]&&(f.uniforms.height=this.contourLevels[o][g],h.draw(r.LINES,this._contourCounts[o][g],this._contourOffsets[o][g]))}for(h.unbind(),(h=this._dynamicVAO).bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=k[i],r.lineWidth(this.dynamicWidth[i]*this.pixelRatio),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),o=0;o<3;++o)this.contourProject[o][i]&&(f.uniforms.model=u.projections[o],f.uniforms.clipBounds=u.clipBounds[o],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));h.unbind()}}S.draw=function(t){return z.call(this,t,!1)},S.drawTransparent=function(t){return z.call(this,t,!0)};var D={model:w,view:w,projection:w,inverseModel:w,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function R(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function F(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function B(t){if(Array.isArray(t)){if(Array.isArray(t))return[F(t[0]),F(t[1]),F(t[2])];var e=F(t);return[e.slice(),e.slice(),e.slice()]}}S.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=D;r.model=t.model||w,r.view=t.view||w,r.projection=t.projection||w,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=O;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var o=C(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]*this.pixelRatio),s.uniforms.permutation=k[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(s.uniforms.height=this.contourLevels[a][n],l.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){s.uniforms.permutation=k[a],e.lineWidth(this.contourWidth[a]*this.pixelRatio);for(var c=0;c<this.contourLevels[a].length;++c)this._contourCounts[a][c]&&(s.uniforms.height=this.contourLevels[a][c],l.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c]))}l.unbind()}},S.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var c=r.position;c[0]=c[1]=c[2]=0;for(var u=0;u<2;++u)for(var f=u?a:1-a,h=0;h<2;++h)for(var p=i+u,d=s+h,m=f*(h?l:1-l),v=0;v<3;++v)c[v]+=this._field[v].get(p,d)*m;for(var y=this._pickResult.level,x=0;x<3;++x)if(y[x]=g.le(this.contourLevels[x],c[x]),y[x]<0)this.contourLevels[x].length>0&&(y[x]=0);else if(y[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][y[x]],_=this.contourLevels[x][y[x]+1];Math.abs(b-c[x])>Math.abs(_-c[x])&&(y[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],v=0;v<3;++v)r.dataCoordinate[v]=this._field[v].get(r.index[0],r.index[1]);return r},S.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();c.assign(t.lo(1,1).hi(r[0],r[1]),e),c.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),c.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),c.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),c.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},S.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=R(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=R(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=R(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=B(t.contourColor)),\"contourProject\"in t&&(this.contourProject=R(t.contourProject,(function(t){return R(t,Boolean)}))),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=B(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=R(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=R(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0),\"colormap\"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var c=l[o];for(v=0;v<2;++v)if(c.shape[v]!==a[v])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],c)}}else if(t.ticks){var u=t.ticks;if(!Array.isArray(u)||2!==u.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=u[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var g=[0,0];g[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],g,0)}this._field[0].set(0,0,0);for(var v=0;v<a[0];++v)this._field[0].set(v+1,0,v);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),v=0;v<a[1];++v)this._field[1].set(0,v+1,v);this._field[1].set(0,a[1]+1,a[1]-1)}var y=this._field,x=f(s.mallocFloat(3*y[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)m(x.pick(o),y[o],\"mirror\");var b=f(s.mallocFloat(3*y[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(v=0;v<a[1]+2;++v){var _=x.get(0,o,v,0),w=x.get(0,o,v,1),k=x.get(1,o,v,0),A=x.get(1,o,v,1),M=x.get(2,o,v,0),S=x.get(2,o,v,1),E=k*S-A*M,L=M*w-S*_,C=_*A-w*k,P=Math.sqrt(E*E+L*L+C*C);P<1e-8?(P=Math.max(Math.abs(E),Math.abs(L),Math.abs(C)))<1e-8?(C=1,L=E=0,P=1):P=1/P:P=1/Math.sqrt(P),b.set(o,v,0,E*P),b.set(o,v,1,L*P),b.set(o,v,2,C*P)}s.free(x.data);var I=[1/0,1/0,1/0],O=[-1/0,-1/0,-1/0],z=1/0,D=-1/0,F=(a[0]-1)*(a[1]-1)*6,N=s.mallocFloat(n.nextPow2(10*F)),j=0,U=0;for(o=0;o<a[0]-1;++o)t:for(v=0;v<a[1]-1;++v){for(var V=0;V<2;++V)for(var q=0;q<2;++q)for(var H=0;H<3;++H){var G=this._field[H].get(1+o+V,1+v+q);if(isNaN(G)||!isFinite(G))continue t}for(H=0;H<6;++H){var Y=o+T[H][0],W=v+T[H][1],X=this._field[0].get(Y+1,W+1),Z=this._field[1].get(Y+1,W+1);G=this._field[2].get(Y+1,W+1),E=b.get(Y+1,W+1,0),L=b.get(Y+1,W+1,1),C=b.get(Y+1,W+1,2),t.intensity&&(J=t.intensity.get(Y,W));var J=t.intensity?t.intensity.get(Y,W):G+this.objectOffset[2];N[j++]=Y,N[j++]=W,N[j++]=X,N[j++]=Z,N[j++]=G,N[j++]=0,N[j++]=J,N[j++]=E,N[j++]=L,N[j++]=C,I[0]=Math.min(I[0],X+this.objectOffset[0]),I[1]=Math.min(I[1],Z+this.objectOffset[1]),I[2]=Math.min(I[2],G+this.objectOffset[2]),z=Math.min(z,J),O[0]=Math.max(O[0],X+this.objectOffset[0]),O[1]=Math.max(O[1],Z+this.objectOffset[1]),O[2]=Math.max(O[2],G+this.objectOffset[2]),D=Math.max(D,J),U+=1}}for(t.intensityBounds&&(z=+t.intensityBounds[0],D=+t.intensityBounds[1]),o=6;o<j;o+=10)N[o]=(N[o]-z)/(D-z);this._vertexCount=U,this._coordinateBuffer.update(N.subarray(0,j)),s.freeFloat(N),s.free(b.data),this.bounds=[I,O],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===z&&this.intensityBounds[1]===D||(r=!0),this.intensityBounds=[z,D]}if(\"levels\"in t){var K=t.levels;for(K=Array.isArray(K[0])?K.slice():[[],[],K],o=0;o<3;++o)K[o]=K[o].slice(),K[o].sort((function(t,e){return t-e}));for(o=0;o<3;++o)for(v=0;v<K[o].length;++v)K[o][v]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(K[o].length!==this.contourLevels[o].length){r=!0;break}for(v=0;v<K[o].length;++v)if(K[o][v]!==this.contourLevels[o][v]){r=!0;break t}}this.contourLevels=K}if(r){y=this._field,a=this.shape;for(var Q=[],$=0;$<3;++$){var tt=this.contourLevels[$],et=[],rt=[],nt=[0,0,0];for(o=0;o<tt.length;++o){var it=h(this._field[$],tt[o]);et.push(Q.length/5|0),U=0;t:for(v=0;v<it.cells.length;++v){var at=it.cells[v];for(H=0;H<2;++H){var ot=it.positions[at[H]],st=ot[0],lt=0|Math.floor(st),ct=st-lt,ut=ot[1],ft=0|Math.floor(ut),ht=ut-ft,pt=!1;e:for(var dt=0;dt<3;++dt){nt[dt]=0;var gt=($+dt+1)%3;for(V=0;V<2;++V){var mt=V?ct:1-ct;for(Y=0|Math.min(Math.max(lt+V,0),a[0]),q=0;q<2;++q){var vt=q?ht:1-ht;if(W=0|Math.min(Math.max(ft+q,0),a[1]),G=dt<2?this._field[gt].get(Y,W):(this.intensity.get(Y,W)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(G)||isNaN(G)){pt=!0;break e}var yt=mt*vt;nt[dt]+=yt*G}}}if(pt){if(H>0){for(var xt=0;xt<5;++xt)Q.pop();U-=1}continue t}Q.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[$]=et,this._contourCounts[$]=rt}var bt=s.mallocFloat(Q.length);for(o=0;o<Q.length;++o)bt[o]=Q[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},S.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},S.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,c=(o+2)%3,u=this._field[o],f=this._field[l],p=this._field[c],d=h(u,r[o]),g=d.cells,m=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<g.length;++e)for(var v=g[e],y=0;y<2;++y){var x=m[v[y]],b=+x[0],_=0|b,w=0|Math.min(_+1,i[0]),T=b-_,k=1-T,A=+x[1],M=0|A,S=0|Math.min(M+1,i[1]),E=A-M,L=1-E,C=k*L,P=k*E,I=T*L,O=T*E,z=C*f.get(_,M)+P*f.get(_,S)+I*f.get(w,M)+O*f.get(w,S),D=C*p.get(_,M)+P*p.get(_,S)+I*p.get(w,M)+O*p.get(w,S);if(isNaN(z)||isNaN(D)){y&&(n-=1);break}a[2*n+0]=z,a[2*n+1]=D,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),s.freeFloat(a)}}},{\"./lib/shaders\":353,\"binary-search-bounds\":103,\"bit-twiddle\":104,colormap:137,\"gl-buffer\":267,\"gl-mat4/invert\":299,\"gl-mat4/multiply\":301,\"gl-texture2d\":356,\"gl-vao\":361,ndarray:483,\"ndarray-gradient\":476,\"ndarray-ops\":478,\"ndarray-pack\":479,\"surface-nets\":591,\"typedarray-pool\":617}],355:[function(t,e,r){\"use strict\";var n=t(\"css-font\"),i=t(\"pick-by-alias\"),a=t(\"regl\"),o=t(\"gl-util/context\"),s=t(\"es6-weak-map\"),l=t(\"color-normalize\"),c=t(\"font-atlas\"),u=t(\"typedarray-pool\"),f=t(\"parse-rect\"),h=t(\"is-plain-obj\"),p=t(\"parse-unit\"),d=t(\"to-px\"),g=t(\"detect-kerning\"),m=t(\"object-assign\"),v=t(\"font-measure\"),y=t(\"flatten-vertex-data\"),x=t(\"bit-twiddle\").nextPow2,b=new s,_=!1;if(document.body){var w=document.body.appendChild(document.createElement(\"div\"));w.style.font=\"italic small-caps bold condensed 16px/2 cursive\",getComputedStyle(w).fontStretch&&(_=!0),document.body.removeChild(w)}var T=function(t){!function(t){return\"function\"==typeof t&&t._gl&&t.prop&&t.texture&&t.buffer}(t)?this.gl=o(t):(t={regl:t},this.gl=t.regl._gl),this.shader=b.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||a({gl:this.gl}),this.charBuffer=this.regl.buffer({type:\"uint8\",usage:\"stream\"}),this.sizeBuffer=this.regl.buffer({type:\"float\",usage:\"stream\"}),this.shader||(this.shader=this.createShader(),b.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(h(t)?t:{})};T.prototype.createShader=function(){var t=this.regl,e=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},stencil:{enable:!1},depth:{enable:!1},count:t.prop(\"count\"),offset:t.prop(\"offset\"),attributes:{charOffset:{offset:4,stride:8,buffer:t.this(\"sizeBuffer\")},width:{offset:0,stride:8,buffer:t.this(\"sizeBuffer\")},char:t.this(\"charBuffer\"),position:t.this(\"position\")},uniforms:{atlasSize:function(t,e){return[e.atlas.width,e.atlas.height]},atlasDim:function(t,e){return[e.atlas.cols,e.atlas.rows]},atlas:function(t,e){return e.atlas.texture},charStep:function(t,e){return e.atlas.step},em:function(t,e){return e.atlas.em},color:t.prop(\"color\"),opacity:t.prop(\"opacity\"),viewport:t.this(\"viewportArray\"),scale:t.this(\"scale\"),align:t.prop(\"align\"),baseline:t.prop(\"baseline\"),translate:t.this(\"translate\"),positionOffset:t.prop(\"positionOffset\")},primitive:\"points\",viewport:t.this(\"viewport\"),vert:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tattribute float width, charOffset, char;\\n\\t\\t\\tattribute vec2 position;\\n\\t\\t\\tuniform float fontSize, charStep, em, align, baseline;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform vec4 color;\\n\\t\\t\\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\t\"+(T.normalViewport?\"\":\"vec2 positionOffset = vec2(positionOffset.x,- positionOffset.y);\")+\"\\n\\n\\t\\t\\t\\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\\n\\t\\t\\t\\t\\t+ positionOffset))\\n\\t\\t\\t\\t\\t/ (viewport.zw * scale.xy);\\n\\n\\t\\t\\t\\tvec2 position = (position + translate) * scale;\\n\\t\\t\\t\\tposition += offset * scale;\\n\\n\\t\\t\\t\\t\"+(T.normalViewport?\"position.y = 1. - position.y;\":\"\")+\"\\n\\n\\t\\t\\t\\tcharCoord = position * viewport.zw + viewport.xy;\\n\\n\\t\\t\\t\\tgl_Position = vec4(position * 2. - 1., 0, 1);\\n\\n\\t\\t\\t\\tgl_PointSize = charStep;\\n\\n\\t\\t\\t\\tcharId.x = mod(char, atlasDim.x);\\n\\t\\t\\t\\tcharId.y = floor(char / atlasDim.x);\\n\\n\\t\\t\\t\\tcharWidth = width * em;\\n\\n\\t\\t\\t\\tfontColor = color / 255.;\\n\\t\\t\\t}\",frag:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tuniform sampler2D atlas;\\n\\t\\t\\tuniform float fontSize, charStep, opacity;\\n\\t\\t\\tuniform vec2 atlasSize;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\n\\t\\t\\tfloat lightness(vec4 color) {\\n\\t\\t\\t\\treturn color.r * 0.299 + color.g * 0.587 + color.b * 0.114;\\n\\t\\t\\t}\\n\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 uv = gl_FragCoord.xy - charCoord + charStep * .5;\\n\\t\\t\\t\\tfloat halfCharStep = floor(charStep * .5 + .5);\\n\\n\\t\\t\\t\\t// invert y and shift by 1px (FF expecially needs that)\\n\\t\\t\\t\\tuv.y = charStep - uv.y;\\n\\n\\t\\t\\t\\t// ignore points outside of character bounding box\\n\\t\\t\\t\\tfloat halfCharWidth = ceil(charWidth * .5);\\n\\t\\t\\t\\tif (floor(uv.x) > halfCharStep + halfCharWidth ||\\n\\t\\t\\t\\t\\tfloor(uv.x) < halfCharStep - halfCharWidth) return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},T.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=i(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign textbaseline\",baseline:\"baseline textBaseline textbaseline\",direction:\"dir direction textDirection\",color:\"color colour fill fill-color fillColor textColor textcolor\",kerning:\"kerning kern\",range:\"range dataBox\",viewport:\"vp viewport viewBox viewbox viewPort\",opacity:\"opacity alpha transparency visible visibility opaque\",offset:\"offset positionOffset padding shift indent indentation\"},!0)).opacity&&(Array.isArray(t.opacity)?this.opacity=t.opacity.map((function(t){return parseFloat(t)})):this.opacity=parseFloat(t.opacity)),null!=t.viewport&&(this.viewport=f(t.viewport),T.normalViewport&&(this.viewport.y=this.canvas.height-this.viewport.y-this.viewport.height),this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null==this.viewport&&(this.viewport={x:0,y:0,width:this.gl.drawingBufferWidth,height:this.gl.drawingBufferHeight},this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null!=t.kerning&&(this.kerning=t.kerning),null!=t.offset&&(\"number\"==typeof t.offset&&(t.offset=[t.offset,0]),this.positionOffset=y(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=T.baseFontSize+\"px sans-serif\");var r,a=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach((function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(T.baseFontSize+\"px \"+t)}else t=n.parse(n.stringify(t));var i=n.stringify({size:T.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&i==e.font[r].baseString||(a=!0,e.font[r]=T.fonts[i],e.font[r]))){var c=t.family.join(\", \"),u=[t.style];t.style!=t.variant&&u.push(t.variant),t.variant!=t.weight&&u.push(t.weight),_&&t.weight!=t.stretch&&u.push(t.stretch),e.font[r]={baseString:i,family:c,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:v(c,{origin:\"top\",fontSize:T.baseFontSize,fontStyle:u.join(\" \")})},T.fonts[i]=e.font[r]}})),(a||o)&&this.font.forEach((function(r,i){var a=n.stringify({size:e.fontSize[i],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[i]=e.shader.atlas[a],!e.fontAtlas[i]){var o=r.metrics;e.shader.atlas[a]=e.fontAtlas[i]={fontString:a,step:2*Math.ceil(e.fontSize[i]*o.bottom*.5),em:e.fontSize[i],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)})),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),h=0;h<s.length;h++)s[h]=t.text;t.text=s}if(null!=t.text||a){if(this.textOffsets=[0],Array.isArray(t.text)){this.count=t.text[0].length,this.counts=[this.count];for(var b=1;b<t.text.length;b++)this.textOffsets[b]=this.textOffsets[b-1]+t.text[b-1].length,this.count+=t.text[b].length,this.counts.push(t.text[b].length);this.text=t.text.join(\"\")}else this.text=t.text,this.count=this.text.length,this.counts=[this.count];r=[],this.font.forEach((function(t,n){T.atlasContext.font=t.baseString;for(var i=e.fontAtlas[n],a=0;a<e.text.length;a++){var o=e.text.charAt(a);if(null==i.ids[o]&&(i.ids[o]=i.chars.length,i.chars.push(o),r.push(o)),null==t.width[o]&&(t.width[o]=T.atlasContext.measureText(o).width/T.baseFontSize,e.kerning)){var s=[];for(var l in t.width)s.push(l+o,o+l);m(t.kerning,g(t.family,{pairs:s}))}}}))}if(t.position)if(t.position.length>2){for(var w=!t.position[0].length,k=u.mallocFloat(2*this.count),A=0,M=0;A<this.counts.length;A++){var S=this.counts[A];if(w)for(var E=0;E<S;E++)k[M++]=t.position[2*A],k[M++]=t.position[2*A+1];else for(var L=0;L<S;L++)k[M++]=t.position[A][0],k[M++]=t.position[A][1]}this.position.call?this.position({type:\"float\",data:k}):this.position=this.regl.buffer({type:\"float\",data:k}),u.freeFloat(k)}else this.position.destroy&&this.position.destroy(),this.position={constant:t.position};if(t.text||a){var C=u.mallocUint8(this.count),P=u.mallocFloat(2*this.count);this.textWidth=[];for(var I=0,O=0;I<this.counts.length;I++){for(var z=this.counts[I],D=this.font[I]||this.font[0],R=this.fontAtlas[I]||this.fontAtlas[0],F=0;F<z;F++){var B=this.text.charAt(O),N=this.text.charAt(O-1);if(C[O]=R.ids[B],P[2*O]=D.width[B],F){var j=P[2*O-2],U=P[2*O],V=P[2*O-1]+.5*j+.5*U;if(this.kerning){var q=D.kerning[N+B];q&&(V+=.001*q)}P[2*O+1]=V}else P[2*O+1]=.5*P[2*O];O++}this.textWidth.push(P.length?.5*P[2*O-2]+P[2*O-1]:0)}t.align||(t.align=this.align),this.charBuffer({data:C,type:\"uint8\",usage:\"stream\"}),this.sizeBuffer({data:P,type:\"float\",usage:\"stream\"}),u.freeUint8(C),u.freeFloat(P),r.length&&this.font.forEach((function(t,r){var n=e.fontAtlas[r],i=n.step,a=Math.floor(T.maxAtlasSize/i),o=Math.min(a,n.chars.length),s=Math.ceil(n.chars.length/o),l=x(o*i),u=x(s*i);n.width=l,n.height=u,n.rows=s,n.cols=o,n.em&&n.texture({data:c({canvas:T.atlasCanvas,font:n.fontString,chars:n.chars,shape:[l,u],step:[i,i]})})}))}if(t.align&&(this.align=t.align,this.alignOffset=this.textWidth.map((function(t,r){var n=Array.isArray(e.align)?e.align.length>1?e.align[r]:e.align[0]:e.align;if(\"number\"==typeof n)return n;switch(n){case\"right\":case\"end\":return-t;case\"center\":case\"centre\":case\"middle\":return.5*-t}return 0}))),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map((function(t,r){var n=(e.font[r]||e.font[0]).metrics,i=0;return i+=.5*n.bottom,i+=\"number\"==typeof t?t-n.baseline:-n[t],T.normalViewport||(i*=-1),i}))),null!=t.color)if(t.color||(t.color=\"transparent\"),\"string\"!=typeof t.color&&isNaN(t.color)){var H;if(\"number\"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;H=u.mallocUint8(G);for(var Y=(t.color.subarray||t.color.slice).bind(t.color),W=0;W<G;W+=4)H.set(l(Y(W,W+4),\"uint8\"),W)}else{var X=t.color.length;H=u.mallocUint8(4*X);for(var Z=0;Z<X;Z++)H.set(l(t.color[Z]||0,\"uint8\"),4*Z)}this.color=H}else this.color=l(t.color,\"uint8\");if(t.position||t.text||t.color||t.baseline||t.align||t.font||t.offset||t.opacity)if(this.color.length>4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var J=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array(J);for(var K=0;K<this.batch.length;K++)this.batch[K]={count:this.counts.length>1?this.counts[K]:this.counts[0],offset:this.textOffsets.length>1?this.textOffsets[K]:this.textOffsets[0],color:this.color?this.color.length<=4?this.color:this.color.subarray(4*K,4*K+4):[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[K]:this.opacity,baseline:null!=this.baselineOffset[K]?this.baselineOffset[K]:this.baselineOffset[0],align:this.align?null!=this.alignOffset[K]?this.alignOffset[K]:this.alignOffset[0]:0,atlas:this.fontAtlas[K]||this.fontAtlas[0],positionOffset:this.positionOffset.length>2?this.positionOffset.subarray(2*K,2*K+2):this.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},T.prototype.destroy=function(){},T.prototype.kerning=!0,T.prototype.position={constant:new Float32Array(2)},T.prototype.translate=null,T.prototype.scale=null,T.prototype.font=null,T.prototype.text=\"\",T.prototype.positionOffset=[0,0],T.prototype.opacity=1,T.prototype.color=new Uint8Array([0,0,0,255]),T.prototype.alignOffset=[0,0],T.normalViewport=!1,T.maxAtlasSize=1024,T.atlasCanvas=document.createElement(\"canvas\"),T.atlasContext=T.atlasCanvas.getContext(\"2d\",{alpha:!1}),T.baseFontSize=64,T.fonts={},e.exports=T},{\"bit-twiddle\":104,\"color-normalize\":131,\"css-font\":150,\"detect-kerning\":181,\"es6-weak-map\":241,\"flatten-vertex-data\":252,\"font-atlas\":253,\"font-measure\":254,\"gl-util/context\":357,\"is-plain-obj\":457,\"object-assign\":487,\"parse-rect\":492,\"parse-unit\":494,\"pick-by-alias\":498,regl:540,\"to-px\":600,\"typedarray-pool\":617}],356:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),i=t(\"ndarray-ops\"),a=t(\"typedarray-pool\");e.exports=function(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");o||c(t);if(\"number\"==typeof arguments[1])return v(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return v(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(\"object\"==typeof arguments[1]){var e=arguments[1],r=u(e)?e:e.raw;if(r)return y(t,r,0|e.width,0|e.height,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return x(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function c(t){o=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],s=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],l=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}function u(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var f=function(t,e){i.muls(t,e,255)};function h(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function p(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var d=p.prototype;function g(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function m(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function v(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=m(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new p(t,o,e,r,n,i)}function y(t,e,r,n,i,a){var o=m(t);return t.texImage2D(t.TEXTURE_2D,0,i,i,a,e),new p(t,o,r,n,i,a)}function x(t,e){var r=e.dtype,o=e.shape.slice(),s=t.getParameter(t.MAX_TEXTURE_SIZE);if(o[0]<0||o[0]>s||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=g(o,e.stride.slice()),c=0;\"float32\"===r?c=t.FLOAT:\"float64\"===r?(c=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?c=t.UNSIGNED_BYTE:(c=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var u,h,d=0;if(2===o.length)d=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])d=t.ALPHA;else if(2===o[2])d=t.LUMINANCE_ALPHA;else if(3===o[2])d=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");d=t.RGBA}}c!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(c=t.UNSIGNED_BYTE,l=!1);var v=e.size;if(l)u=0===e.offset&&e.data.length===v?e.data:e.data.subarray(e.offset,e.offset+v);else{var y=[o[2],o[2]*o[0],1];h=a.malloc(v,r);var 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f(this.rightPoints,t,e)}return h(this.leftPoints,e)},a.queryInterval=function(t,e,r){var n;if(t<this.mid&&this.left&&(n=this.left.queryInterval(t,e,r)))return n;if(e>this.mid&&this.right&&(n=this.right.queryInterval(t,e,r)))return n;return e<this.mid?u(this.leftPoints,e,r):t>this.mid?f(this.rightPoints,t,r):h(this.leftPoints,r)};var y=v.prototype;y.insert=function(t){this.root?this.root.insert(t):this.root=new i(t[0],null,null,[t],[t])},y.remove=function(t){if(this.root){var e=this.root.remove(t);return 2===e&&(this.root=null),0!==e}return!1},y.queryPoint=function(t,e){if(this.root)return this.root.queryPoint(t,e)},y.queryInterval=function(t,e,r){if(t<=e&&this.root)return this.root.queryInterval(t,e,r)},Object.defineProperty(y,\"count\",{get:function(){return this.root?this.root.count:0}}),Object.defineProperty(y,\"intervals\",{get:function(){return this.root?this.root.intervals([]):[]}})},{\"binary-search-bounds\":449}],449:[function(t,e,r){arguments[4][251][0].apply(r,arguments)},{dup:251}],450:[function(t,e,r){\"use strict\";e.exports=function(t,e){e=e||new Array(t.length);for(var r=0;r<t.length;++r)e[t[r]]=r;return e}},{}],451:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=new Array(t),r=0;r<t;++r)e[r]=r;return e}},{}],452:[function(t,e,r){e.exports=!0},{}],453:[function(t,e,r){function n(t){return!!t.constructor&&\"function\"==typeof t.constructor.isBuffer&&t.constructor.isBuffer(t)}\n",
+       "/*!\n",
+       " * Determine if an object is a Buffer\n",
+       " *\n",
+       " * @author   Feross Aboukhadijeh <https://feross.org>\n",
+       " * @license  MIT\n",
+       " */\n",
+       "e.exports=function(t){return null!=t&&(n(t)||function(t){return\"function\"==typeof t.readFloatLE&&\"function\"==typeof t.slice&&n(t.slice(0,0))}(t)||!!t._isBuffer)}},{}],454:[function(t,e,r){\"use strict\";e.exports=\"undefined\"!=typeof navigator&&(/MSIE/.test(navigator.userAgent)||/Trident\\//.test(navigator.appVersion))},{}],455:[function(t,e,r){\"use strict\";e.exports=a,e.exports.isMobile=a,e.exports.default=a;var n=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino/i,i=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino|android|ipad|playbook|silk/i;function a(t){t||(t={});var e=t.ua;if(e||\"undefined\"==typeof navigator||(e=navigator.userAgent),e&&e.headers&&\"string\"==typeof e.headers[\"user-agent\"]&&(e=e.headers[\"user-agent\"]),\"string\"!=typeof e)return!1;var r=t.tablet?i.test(e):n.test(e);return!r&&t.tablet&&t.featureDetect&&navigator&&navigator.maxTouchPoints>1&&-1!==e.indexOf(\"Macintosh\")&&-1!==e.indexOf(\"Safari\")&&(r=!0),r}},{}],456:[function(t,e,r){\"use strict\";e.exports=function(t){var e=typeof t;return null!==t&&(\"object\"===e||\"function\"===e)}},{}],457:[function(t,e,r){\"use strict\";var n=Object.prototype.toString;e.exports=function(t){var e;return\"[object Object]\"===n.call(t)&&(null===(e=Object.getPrototypeOf(t))||e===Object.getPrototypeOf({}))}},{}],458:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e,r=t.length,n=0;n<r;n++)if(((e=t.charCodeAt(n))<9||e>13)&&32!==e&&133!==e&&160!==e&&5760!==e&&6158!==e&&(e<8192||e>8205)&&8232!==e&&8233!==e&&8239!==e&&8287!==e&&8288!==e&&12288!==e&&65279!==e)return!1;return!0}},{}],459:[function(t,e,r){\"use strict\";e.exports=function(t){return\"string\"==typeof t&&(t=t.trim(),!!(/^[mzlhvcsqta]\\s*[-+.0-9][^mlhvzcsqta]+/i.test(t)&&/[\\dz]$/i.test(t)&&t.length>4))}},{}],460:[function(t,e,r){e.exports=function(t,e,r){return t*(1-r)+e*r}},{}],461:[function(t,e,r){!function(t,n){\"object\"==typeof r&&void 0!==e?e.exports=n():(t=t||self).mapboxgl=n()}(this,(function(){\"use strict\";var t,e,r;function n(n,i){if(t)if(e){var a=\"var sharedChunk = {}; (\"+t+\")(sharedChunk); (\"+e+\")(sharedChunk);\",o={};t(o),(r=i(o)).workerUrl=window.URL.createObjectURL(new Blob([a],{type:\"text/javascript\"}))}else e=i;else t=i}return n(0,(function(t){function e(t,e){return t(e={exports:{}},e.exports),e.exports}var r=n;function n(t,e,r,n){this.cx=3*t,this.bx=3*(r-t)-this.cx,this.ax=1-this.cx-this.bx,this.cy=3*e,this.by=3*(n-e)-this.cy,this.ay=1-this.cy-this.by,this.p1x=t,this.p1y=n,this.p2x=r,this.p2y=n}n.prototype.sampleCurveX=function(t){return((this.ax*t+this.bx)*t+this.cx)*t},n.prototype.sampleCurveY=function(t){return((this.ay*t+this.by)*t+this.cy)*t},n.prototype.sampleCurveDerivativeX=function(t){return(3*this.ax*t+2*this.bx)*t+this.cx},n.prototype.solveCurveX=function(t,e){var r,n,i,a,o;for(void 0===e&&(e=1e-6),i=t,o=0;o<8;o++){if(a=this.sampleCurveX(i)-t,Math.abs(a)<e)return i;var s=this.sampleCurveDerivativeX(i);if(Math.abs(s)<1e-6)break;i-=a/s}if((i=t)<(r=0))return r;if(i>(n=1))return n;for(;r<n;){if(a=this.sampleCurveX(i),Math.abs(a-t)<e)return i;t>a?r=i:n=i,i=.5*(n-r)+r}return i},n.prototype.solve=function(t,e){return this.sampleCurveY(this.solveCurveX(t,e))};var i=a;function a(t,e){this.x=t,this.y=e}function o(t,e,n,i){var a=new r(t,e,n,i);return function(t){return a.solve(t)}}a.prototype={clone:function(){return new a(this.x,this.y)},add:function(t){return this.clone()._add(t)},sub:function(t){return this.clone()._sub(t)},multByPoint:function(t){return this.clone()._multByPoint(t)},divByPoint:function(t){return this.clone()._divByPoint(t)},mult:function(t){return this.clone()._mult(t)},div:function(t){return this.clone()._div(t)},rotate:function(t){return this.clone()._rotate(t)},rotateAround:function(t,e){return this.clone()._rotateAround(t,e)},matMult:function(t){return this.clone()._matMult(t)},unit:function(){return this.clone()._unit()},perp:function(){return this.clone()._perp()},round:function(){return this.clone()._round()},mag:function(){return Math.sqrt(this.x*this.x+this.y*this.y)},equals:function(t){return this.x===t.x&&this.y===t.y},dist:function(t){return Math.sqrt(this.distSqr(t))},distSqr:function(t){var e=t.x-this.x,r=t.y-this.y;return e*e+r*r},angle:function(){return Math.atan2(this.y,this.x)},angleTo:function(t){return Math.atan2(this.y-t.y,this.x-t.x)},angleWith:function(t){return this.angleWithSep(t.x,t.y)},angleWithSep:function(t,e){return Math.atan2(this.x*e-this.y*t,this.x*t+this.y*e)},_matMult:function(t){var e=t[0]*this.x+t[1]*this.y,r=t[2]*this.x+t[3]*this.y;return this.x=e,this.y=r,this},_add:function(t){return this.x+=t.x,this.y+=t.y,this},_sub:function(t){return this.x-=t.x,this.y-=t.y,this},_mult:function(t){return this.x*=t,this.y*=t,this},_div:function(t){return this.x/=t,this.y/=t,this},_multByPoint:function(t){return this.x*=t.x,this.y*=t.y,this},_divByPoint:function(t){return this.x/=t.x,this.y/=t.y,this},_unit:function(){return this._div(this.mag()),this},_perp:function(){var t=this.y;return this.y=this.x,this.x=-t,this},_rotate:function(t){var e=Math.cos(t),r=Math.sin(t),n=e*this.x-r*this.y,i=r*this.x+e*this.y;return this.x=n,this.y=i,this},_rotateAround:function(t,e){var r=Math.cos(t),n=Math.sin(t),i=e.x+r*(this.x-e.x)-n*(this.y-e.y),a=e.y+n*(this.x-e.x)+r*(this.y-e.y);return this.x=i,this.y=a,this},_round:function(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this}},a.convert=function(t){return t instanceof a?t:Array.isArray(t)?new a(t[0],t[1]):t};var s=o(.25,.1,.25,1);function l(t,e,r){return Math.min(r,Math.max(e,t))}function c(t,e,r){var n=r-e,i=((t-e)%n+n)%n+e;return i===e?r:i}function u(t){for(var e=[],r=arguments.length-1;r-- >0;)e[r]=arguments[r+1];for(var n=0,i=e;n<i.length;n+=1){var a=i[n];for(var o in a)t[o]=a[o]}return t}var f=1;function h(){return f++}function p(){return function t(e){return e?(e^16*Math.random()>>e/4).toString(16):([1e7]+-[1e3]+-4e3+-8e3+-1e11).replace(/[018]/g,t)}()}function d(t){return!!t&&/^[0-9a-f]{8}-[0-9a-f]{4}-[4][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$/i.test(t)}function g(t,e){t.forEach((function(t){e[t]&&(e[t]=e[t].bind(e))}))}function m(t,e){return-1!==t.indexOf(e,t.length-e.length)}function v(t,e,r){var n={};for(var i in t)n[i]=e.call(r||this,t[i],i,t);return n}function y(t,e,r){var n={};for(var i 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Date.now()>this._skuTokenExpiresAt},q.prototype.transformRequest=function(t,e){return this._transformRequestFn&&this._transformRequestFn(t,e)||{url:t}},q.prototype.normalizeStyleURL=function(t,e){if(!H(t))return t;var r=X(t);return r.path=\"/styles/v1\"+r.path,this._makeAPIURL(r,this._customAccessToken||e)},q.prototype.normalizeGlyphsURL=function(t,e){if(!H(t))return t;var r=X(t);return r.path=\"/fonts/v1\"+r.path,this._makeAPIURL(r,this._customAccessToken||e)},q.prototype.normalizeSourceURL=function(t,e){if(!H(t))return t;var r=X(t);return r.path=\"/v4/\"+r.authority+\".json\",r.params.push(\"secure\"),this._makeAPIURL(r,this._customAccessToken||e)},q.prototype.normalizeSpriteURL=function(t,e,r,n){var i=X(t);return H(t)?(i.path=\"/styles/v1\"+i.path+\"/sprite\"+e+r,this._makeAPIURL(i,this._customAccessToken||n)):(i.path+=\"\"+e+r,Z(i))},q.prototype.normalizeTileURL=function(t,e){if(this._isSkuTokenExpired()&&this._createSkuToken(),t&&!H(t))return t;var r=X(t),n=R.devicePixelRatio>=2||512===e?\"@2x\":\"\",i=B.supported?\".webp\":\"$1\";r.path=r.path.replace(/(\\.(png|jpg)\\d*)(?=$)/,\"\"+n+i),r.path=r.path.replace(/^.+\\/v4\\//,\"/\"),r.path=\"/v4\"+r.path;var a=this._customAccessToken||function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e].match(/^access_token=(.*)$/);if(n)return n[1]}return null}(r.params)||F.ACCESS_TOKEN;return F.REQUIRE_ACCESS_TOKEN&&a&&this._skuToken&&r.params.push(\"sku=\"+this._skuToken),this._makeAPIURL(r,a)},q.prototype.canonicalizeTileURL=function(t,e){var r=X(t);if(!r.path.match(/(^\\/v4\\/)/)||!r.path.match(/\\.[\\w]+$/))return t;var n=\"mapbox://tiles/\";n+=r.path.replace(\"/v4/\",\"\");var i=r.params;return e&&(i=i.filter((function(t){return!t.match(/^access_token=/)}))),i.length&&(n+=\"?\"+i.join(\"&\")),n},q.prototype.canonicalizeTileset=function(t,e){for(var r=!!e&&H(e),n=[],i=0,a=t.tiles||[];i<a.length;i+=1){var o=a[i];Y(o)?n.push(this.canonicalizeTileURL(o,r)):n.push(o)}return 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r=e.parse(t[1],1,Bt);if(!r)return null;var n=[],i=null;e.expectedType&&\"value\"!==e.expectedType.kind&&(i=e.expectedType);for(var a=1;a<t.length;a+=2){var o=1===a?-1/0:t[a],s=t[a+1],l=a,c=a+1;if(\"number\"!=typeof o)return e.error('Input/output pairs for \"step\" expressions must be defined using literal numeric values (not computed expressions) for the input values.',l);if(n.length&&n[n.length-1][0]>=o)return e.error('Input/output pairs for \"step\" expressions must be arranged with input values in strictly ascending order.',l);var u=e.parse(s,c,i);if(!u)return null;i=i||u.type,n.push([o,u])}return new qe(i,r,n)},qe.prototype.evaluate=function(t){var e=this.labels,r=this.outputs;if(1===e.length)return r[0].evaluate(t);var n=this.input.evaluate(t);if(n<=e[0])return r[0].evaluate(t);var i=e.length;return n>=e[i-1]?r[i-1].evaluate(t):r[Ve(e,n)].evaluate(t)},qe.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1){t(r[e])}},qe.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))},qe.prototype.serialize=function(){for(var t=[\"step\",this.input.serialize()],e=0;e<this.labels.length;e++)e>0&&t.push(this.labels[e]),t.push(this.outputs[e].serialize());return t};var Ge=Object.freeze({__proto__:null,number:He,color:function(t,e,r){return new te(He(t.r,e.r,r),He(t.g,e.g,r),He(t.b,e.b,r),He(t.a,e.a,r))},array:function(t,e,r){return t.map((function(t,n){return He(t,e[n],r)}))}}),Ye=6/29,We=3*Ye*Ye,Xe=Math.PI/180,Ze=180/Math.PI;function Je(t){return t>.008856451679035631?Math.pow(t,1/3):t/We+4/29}function Ke(t){return t>Ye?t*t*t:We*(t-4/29)}function Qe(t){return 255*(t<=.0031308?12.92*t:1.055*Math.pow(t,1/2.4)-.055)}function $e(t){return(t/=255)<=.04045?t/12.92:Math.pow((t+.055)/1.055,2.4)}function tr(t){var e=$e(t.r),r=$e(t.g),n=$e(t.b),i=Je((.4124564*e+.3575761*r+.1804375*n)/.95047),a=Je((.2126729*e+.7151522*r+.072175*n)/1);return{l:116*a-16,a:500*(i-a),b:200*(a-Je((.0193339*e+.119192*r+.9503041*n)/1.08883)),alpha:t.a}}function er(t){var e=(t.l+16)/116,r=isNaN(t.a)?e:e+t.a/500,n=isNaN(t.b)?e:e-t.b/200;return e=1*Ke(e),r=.95047*Ke(r),n=1.08883*Ke(n),new te(Qe(3.2404542*r-1.5371385*e-.4985314*n),Qe(-.969266*r+1.8760108*e+.041556*n),Qe(.0556434*r-.2040259*e+1.0572252*n),t.alpha)}function rr(t,e,r){var n=e-t;return t+r*(n>180||n<-180?n-360*Math.round(n/360):n)}var nr={forward:tr,reverse:er,interpolate:function(t,e,r){return{l:He(t.l,e.l,r),a:He(t.a,e.a,r),b:He(t.b,e.b,r),alpha:He(t.alpha,e.alpha,r)}}},ir={forward:function(t){var e=tr(t),r=e.l,n=e.a,i=e.b,a=Math.atan2(i,n)*Ze;return{h:a<0?a+360:a,c:Math.sqrt(n*n+i*i),l:r,alpha:t.a}},reverse:function(t){var e=t.h*Xe,r=t.c;return er({l:t.l,a:Math.cos(e)*r,b:Math.sin(e)*r,alpha:t.alpha})},interpolate:function(t,e,r){return{h:rr(t.h,e.h,r),c:He(t.c,e.c,r),l:He(t.l,e.l,r),alpha:He(t.alpha,e.alpha,r)}}},ar=Object.freeze({__proto__:null,lab:nr,hcl:ir}),or=function(t,e,r,n,i){this.type=t,this.operator=e,this.interpolation=r,this.input=n,this.labels=[],this.outputs=[];for(var a=0,o=i;a<o.length;a+=1){var s=o[a],l=s[0],c=s[1];this.labels.push(l),this.outputs.push(c)}};function sr(t,e,r,n){var i=n-r,a=t-r;return 0===i?0:1===e?a/i:(Math.pow(e,a)-1)/(Math.pow(e,i)-1)}or.interpolationFactor=function(t,e,n,i){var a=0;if(\"exponential\"===t.name)a=sr(e,t.base,n,i);else if(\"linear\"===t.name)a=sr(e,1,n,i);else if(\"cubic-bezier\"===t.name){var o=t.controlPoints;a=new r(o[0],o[1],o[2],o[3]).solve(sr(e,1,n,i))}return a},or.parse=function(t,e){var r=t[0],n=t[1],i=t[2],a=t.slice(3);if(!Array.isArray(n)||0===n.length)return e.error(\"Expected an interpolation type expression.\",1);if(\"linear\"===n[0])n={name:\"linear\"};else if(\"exponential\"===n[0]){var o=n[1];if(\"number\"!=typeof o)return e.error(\"Exponential interpolation requires a numeric base.\",1,1);n={name:\"exponential\",base:o}}else{if(\"cubic-bezier\"!==n[0])return e.error(\"Unknown interpolation type \"+String(n[0]),1,0);var s=n.slice(1);if(4!==s.length||s.some((function(t){return\"number\"!=typeof t||t<0||t>1})))return e.error(\"Cubic bezier interpolation requires four numeric arguments with values between 0 and 1.\",1);n={name:\"cubic-bezier\",controlPoints:s}}if(t.length-1<4)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if((t.length-1)%2!=0)return e.error(\"Expected an even number of arguments.\");if(!(i=e.parse(i,2,Bt)))return null;var l=[],c=null;\"interpolate-hcl\"===r||\"interpolate-lab\"===r?c=Ut:e.expectedType&&\"value\"!==e.expectedType.kind&&(c=e.expectedType);for(var u=0;u<a.length;u+=2){var f=a[u],h=a[u+1],p=u+3,d=u+4;if(\"number\"!=typeof f)return e.error('Input/output pairs for 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a=Ve(e,n),o=e[a],s=e[a+1],l=or.interpolationFactor(this.interpolation,n,o,s),c=r[a].evaluate(t),u=r[a+1].evaluate(t);return\"interpolate\"===this.operator?Ge[this.type.kind.toLowerCase()](c,u,l):\"interpolate-hcl\"===this.operator?ir.reverse(ir.interpolate(ir.forward(c),ir.forward(u),l)):nr.reverse(nr.interpolate(nr.forward(c),nr.forward(u),l))},or.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1){t(r[e])}},or.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))},or.prototype.serialize=function(){var t;t=\"linear\"===this.interpolation.name?[\"linear\"]:\"exponential\"===this.interpolation.name?1===this.interpolation.base?[\"linear\"]:[\"exponential\",this.interpolation.base]:[\"cubic-bezier\"].concat(this.interpolation.controlPoints);for(var e=[this.operator,t,this.input.serialize()],r=0;r<this.labels.length;r++)e.push(this.labels[r],this.outputs[r].serialize());return e};var lr=function(t,e){this.type=t,this.args=e};lr.parse=function(t,e){if(t.length<2)return e.error(\"Expectected at least one argument.\");var r=null,n=e.expectedType;n&&\"value\"!==n.kind&&(r=n);for(var i=[],a=0,o=t.slice(1);a<o.length;a+=1){var s=o[a],l=e.parse(s,1+i.length,r,void 0,{typeAnnotation:\"omit\"});if(!l)return null;r=r||l.type,i.push(l)}var c=n&&i.some((function(t){return Jt(n,t.type)}));return new lr(c?qt:r,i)},lr.prototype.evaluate=function(t){for(var e,r=null,n=0,i=0,a=this.args;i<a.length;i+=1){if(n++,(r=a[i].evaluate(t))&&r instanceof ie&&!r.available&&(e||(e=r.name),r=null,n===this.args.length&&(r=e)),null!==r)break}return r},lr.prototype.eachChild=function(t){this.args.forEach(t)},lr.prototype.outputDefined=function(){return this.args.every((function(t){return t.outputDefined()}))},lr.prototype.serialize=function(){var t=[\"coalesce\"];return this.eachChild((function(e){t.push(e.serialize())})),t};var cr=function(t,e){this.type=e.type,this.bindings=[].concat(t),this.result=e};cr.prototype.evaluate=function(t){return this.result.evaluate(t)},cr.prototype.eachChild=function(t){for(var e=0,r=this.bindings;e<r.length;e+=1){t(r[e][1])}t(this.result)},cr.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found \"+(t.length-1)+\" instead.\");for(var r=[],n=1;n<t.length-1;n+=2){var i=t[n];if(\"string\"!=typeof i)return e.error(\"Expected string, but found \"+typeof i+\" instead.\",n);if(/[^a-zA-Z0-9_]/.test(i))return e.error(\"Variable names must contain only alphanumeric characters or '_'.\",n);var a=e.parse(t[n+1],n+1);if(!a)return null;r.push([i,a])}var o=e.parse(t[t.length-1],t.length-1,e.expectedType,r);return o?new cr(r,o):null},cr.prototype.outputDefined=function(){return this.result.outputDefined()},cr.prototype.serialize=function(){for(var t=[\"let\"],e=0,r=this.bindings;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];t.push(i,a.serialize())}return t.push(this.result.serialize()),t};var ur=function(t,e,r){this.type=t,this.index=e,this.input=r};ur.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Bt),n=e.parse(t[2],2,Wt(e.expectedType||qt));if(!r||!n)return null;var i=n.type;return new ur(i.itemType,r,n)},ur.prototype.evaluate=function(t){var e=this.index.evaluate(t),r=this.input.evaluate(t);if(e<0)throw new ue(\"Array index out of bounds: \"+e+\" < 0.\");if(e>=r.length)throw new ue(\"Array index out of bounds: \"+e+\" > \"+(r.length-1)+\".\");if(e!==Math.floor(e))throw new ue(\"Array index must be an integer, but found \"+e+\" instead.\");return r[e]},ur.prototype.eachChild=function(t){t(this.index),t(this.input)},ur.prototype.outputDefined=function(){return!1},ur.prototype.serialize=function(){return[\"at\",this.index.serialize(),this.input.serialize()]};var fr=function(t,e){this.type=jt,this.needle=t,this.haystack=e};fr.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,qt),n=e.parse(t[2],2,qt);return r&&n?Kt(r.type,[jt,Nt,Bt,Ft,qt])?new fr(r,n):e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(r.type)+\" instead\"):null},fr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!r)return!1;if(!Qt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new ue(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(se(e))+\" instead.\");if(!Qt(r,[\"string\",\"array\"]))throw new ue(\"Expected second argument to be of type array or string, but found \"+Xt(se(r))+\" instead.\");return r.indexOf(e)>=0},fr.prototype.eachChild=function(t){t(this.needle),t(this.haystack)},fr.prototype.outputDefined=function(){return!0},fr.prototype.serialize=function(){return[\"in\",this.needle.serialize(),this.haystack.serialize()]};var hr=function(t,e,r){this.type=Bt,this.needle=t,this.haystack=e,this.fromIndex=r};hr.parse=function(t,e){if(t.length<=2||t.length>=5)return e.error(\"Expected 3 or 4 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,qt),n=e.parse(t[2],2,qt);if(!r||!n)return null;if(!Kt(r.type,[jt,Nt,Bt,Ft,qt]))return e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(r.type)+\" instead\");if(4===t.length){var i=e.parse(t[3],3,Bt);return i?new hr(r,n,i):null}return new hr(r,n)},hr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!Qt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new ue(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(se(e))+\" instead.\");if(!Qt(r,[\"string\",\"array\"]))throw new ue(\"Expected second argument to be of type array or string, but found \"+Xt(se(r))+\" instead.\");if(this.fromIndex){var n=this.fromIndex.evaluate(t);return r.indexOf(e,n)}return r.indexOf(e)},hr.prototype.eachChild=function(t){t(this.needle),t(this.haystack),this.fromIndex&&t(this.fromIndex)},hr.prototype.outputDefined=function(){return!1},hr.prototype.serialize=function(){if(null!=this.fromIndex&&void 0!==this.fromIndex){var t=this.fromIndex.serialize();return[\"index-of\",this.needle.serialize(),this.haystack.serialize(),t]}return[\"index-of\",this.needle.serialize(),this.haystack.serialize()]};var pr=function(t,e,r,n,i,a){this.inputType=t,this.type=e,this.input=r,this.cases=n,this.outputs=i,this.otherwise=a};pr.parse=function(t,e){if(t.length<5)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=1)return e.error(\"Expected an even number of 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g?\"value\"!==d.type.kind&&e.concat(1).checkSubtype(r,d.type)?null:new pr(r,n,d,i,a,g):null},pr.prototype.evaluate=function(t){var e=this.input.evaluate(t);return(se(e)===this.inputType&&this.outputs[this.cases[e]]||this.otherwise).evaluate(t)},pr.prototype.eachChild=function(t){t(this.input),this.outputs.forEach(t),t(this.otherwise)},pr.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))&&this.otherwise.outputDefined()},pr.prototype.serialize=function(){for(var t=this,e=[\"match\",this.input.serialize()],r=[],n={},i=0,a=Object.keys(this.cases).sort();i<a.length;i+=1){var o=a[i];void 0===(f=n[this.cases[o]])?(n[this.cases[o]]=r.length,r.push([this.cases[o],[o]])):r[f][1].push(o)}for(var s=function(e){return\"number\"===t.inputType.kind?Number(e):e},l=0,c=r;l<c.length;l+=1){var u=c[l],f=u[0],h=u[1];1===h.length?e.push(s(h[0])):e.push(h.map(s)),e.push(this.outputs[outputIndex$1].serialize())}return e.push(this.otherwise.serialize()),e};var dr=function(t,e,r){this.type=t,this.branches=e,this.otherwise=r};dr.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=0)return e.error(\"Expected an odd number of arguments.\");var r;e.expectedType&&\"value\"!==e.expectedType.kind&&(r=e.expectedType);for(var n=[],i=1;i<t.length-1;i+=2){var a=e.parse(t[i],i,jt);if(!a)return null;var o=e.parse(t[i+1],i+1,r);if(!o)return null;n.push([a,o]),r=r||o.type}var s=e.parse(t[t.length-1],t.length-1,r);return s?new dr(r,n,s):null},dr.prototype.evaluate=function(t){for(var e=0,r=this.branches;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];if(i.evaluate(t))return a.evaluate(t)}return this.otherwise.evaluate(t)},dr.prototype.eachChild=function(t){for(var e=0,r=this.branches;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];t(i),t(a)}t(this.otherwise)},dr.prototype.outputDefined=function(){return this.branches.every((function(t){t[0];return 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or?a.interpolation:void 0;return Ir(new Zr(n?\"camera\":\"composite\",t.value,a.labels,o))}Zr.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)},Zr.prototype.evaluate=function(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)},Zr.prototype.interpolationFactor=function(t,e,r){return this.interpolationType?or.interpolationFactor(this.interpolationType,t,e,r):0};var Kr=function(t,e){this._parameters=t,this._specification=e,It(this,function t(e,r){var n,i,a,o=\"color\"===r.type,s=e.stops&&\"object\"==typeof e.stops[0][0],l=s||void 0!==e.property,c=s||!l,u=e.type||(Rr(r)?\"exponential\":\"interval\");if(o&&((e=It({},e)).stops&&(e.stops=e.stops.map((function(t){return[t[0],te.parse(t[1])]}))),e.default?e.default=te.parse(e.default):e.default=te.parse(r.default)),e.colorSpace&&\"rgb\"!==e.colorSpace&&!ar[e.colorSpace])throw new Error(\"Unknown color space: 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n&&r<n.minimum?[new Ct(e,r,r+\" is less than the minimum value \"+n.minimum)]:\"maximum\"in n&&r>n.maximum?[new Ct(e,r,r+\" is greater than the maximum value \"+n.maximum)]:[]}function en(t){var e,r,n,i=t.valueSpec,a=Ot(t.value.type),o={},s=\"categorical\"!==a&&void 0===t.value.property,l=!s,c=\"array\"===Fr(t.value.stops)&&\"array\"===Fr(t.value.stops[0])&&\"object\"===Fr(t.value.stops[0][0]),u=Qr({key:t.key,value:t.value,valueSpec:t.styleSpec.function,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{stops:function(t){if(\"identity\"===a)return[new Ct(t.key,t.value,'identity function may not have a \"stops\" property')];var e=[],r=t.value;e=e.concat($r({key:t.key,value:r,valueSpec:t.valueSpec,style:t.style,styleSpec:t.styleSpec,arrayElementValidator:f})),\"array\"===Fr(r)&&0===r.length&&e.push(new Ct(t.key,r,\"array must have at least one stop\"));return e},default:function(t){return kn({key:t.key,value:t.value,valueSpec:i,style:t.style,styleSpec:t.styleSpec})}}});return\"identity\"===a&&s&&u.push(new Ct(t.key,t.value,'missing required property \"property\"')),\"identity\"===a||t.value.stops||u.push(new Ct(t.key,t.value,'missing required property \"stops\"')),\"exponential\"===a&&t.valueSpec.expression&&!Rr(t.valueSpec)&&u.push(new Ct(t.key,t.value,\"exponential functions not supported\")),t.styleSpec.$version>=8&&(l&&!zr(t.valueSpec)?u.push(new Ct(t.key,t.value,\"property functions not supported\")):s&&!Dr(t.valueSpec)&&u.push(new Ct(t.key,t.value,\"zoom functions not supported\"))),\"categorical\"!==a&&!c||void 0!==t.value.property||u.push(new Ct(t.key,t.value,'\"property\" property is required')),u;function f(t){var e=[],a=t.value,s=t.key;if(\"array\"!==Fr(a))return[new Ct(s,a,\"array expected, \"+Fr(a)+\" found\")];if(2!==a.length)return[new Ct(s,a,\"array length 2 expected, length \"+a.length+\" found\")];if(c){if(\"object\"!==Fr(a[0]))return[new Ct(s,a,\"object expected, \"+Fr(a[0])+\" found\")];if(void 0===a[0].zoom)return[new Ct(s,a,\"object stop key must have zoom\")];if(void 0===a[0].value)return[new Ct(s,a,\"object stop key must have value\")];if(n&&n>Ot(a[0].zoom))return[new Ct(s,a[0].zoom,\"stop zoom values must appear in ascending order\")];Ot(a[0].zoom)!==n&&(n=Ot(a[0].zoom),r=void 0,o={}),e=e.concat(Qr({key:s+\"[0]\",value:a[0],valueSpec:{zoom:{}},style:t.style,styleSpec:t.styleSpec,objectElementValidators:{zoom:tn,value:h}}))}else e=e.concat(h({key:s+\"[0]\",value:a[0],valueSpec:{},style:t.style,styleSpec:t.styleSpec},a));return Yr(zt(a[1]))?e.concat([new Ct(s+\"[1]\",a[1],\"expressions are not allowed in function stops.\")]):e.concat(kn({key:s+\"[1]\",value:a[1],valueSpec:i,style:t.style,styleSpec:t.styleSpec}))}function h(t,n){var s=Fr(t.value),l=Ot(t.value),c=null!==t.value?t.value:n;if(e){if(s!==e)return[new Ct(t.key,c,s+\" stop domain type must match previous stop domain type \"+e)]}else e=s;if(\"number\"!==s&&\"string\"!==s&&\"boolean\"!==s)return[new Ct(t.key,c,\"stop domain value must be a number, string, or boolean\")];if(\"number\"!==s&&\"categorical\"!==a){var u=\"number expected, \"+s+\" found\";return zr(i)&&void 0===a&&(u+='\\nIf you intended to use a categorical function, specify `\"type\": \"categorical\"`.'),[new Ct(t.key,c,u)]}return\"categorical\"!==a||\"number\"!==s||isFinite(l)&&Math.floor(l)===l?\"categorical\"!==a&&\"number\"===s&&void 0!==r&&l<r?[new Ct(t.key,c,\"stop domain values must appear in ascending order\")]:(r=l,\"categorical\"===a&&l in o?[new Ct(t.key,c,\"stop domain values must be unique\")]:(o[l]=!0,[])):[new Ct(t.key,c,\"integer expected, found \"+l)]}}function rn(t){var e=(\"property\"===t.expressionContext?Jr:Wr)(zt(t.value),t.valueSpec);if(\"error\"===e.result)return e.value.map((function(e){return new Ct(\"\"+t.key+e.key,t.value,e.message)}));var r=e.value.expression||e.value._styleExpression.expression;if(\"property\"===t.expressionContext&&\"text-font\"===t.propertyKey&&!r.outputDefined())return[new Ct(t.key,t.value,'Invalid data expression for \"'+t.propertyKey+'\". Output values must be contained as literals within the expression.')];if(\"property\"===t.expressionContext&&\"layout\"===t.propertyType&&!Be(r))return[new Ct(t.key,t.value,'\"feature-state\" data expressions are not supported with layout properties.')];if(\"filter\"===t.expressionContext&&!Be(r))return[new Ct(t.key,t.value,'\"feature-state\" data expressions are not supported with filters.')];if(t.expressionContext&&0===t.expressionContext.indexOf(\"cluster\")){if(!Ne(r,[\"zoom\",\"feature-state\"]))return[new Ct(t.key,t.value,'\"zoom\" and \"feature-state\" expressions are not supported with cluster properties.')];if(\"cluster-initial\"===t.expressionContext&&!Fe(r))return[new Ct(t.key,t.value,\"Feature data expressions are not supported with initial expression part of cluster properties.\")]}return[]}function nn(t){var e=t.key,r=t.value,n=t.valueSpec,i=[];return Array.isArray(n.values)?-1===n.values.indexOf(Ot(r))&&i.push(new Ct(e,r,\"expected one of [\"+n.values.join(\", \")+\"], 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on={type:\"boolean\",default:!1,transition:!1,\"property-type\":\"data-driven\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]}};function sn(t){if(null==t)return{filter:function(){return!0},needGeometry:!1};an(t)||(t=cn(t));var e=Wr(t,on);if(\"error\"===e.result)throw new Error(e.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return{filter:function(t,r,n){return e.value.evaluate(t,r,{},n)},needGeometry:function t(e){if(!Array.isArray(e))return!1;if(\"within\"===e[0])return!0;for(var r=1;r<e.length;r++)if(t(e[r]))return!0;return!1}(t)}}function ln(t,e){return t<e?-1:t>e?1:0}function cn(t){if(!t)return!0;var e,r=t[0];return t.length<=1?\"any\"!==r:\"==\"===r?un(t[1],t[2],\"==\"):\"!=\"===r?pn(un(t[1],t[2],\"==\")):\"<\"===r||\">\"===r||\"<=\"===r||\">=\"===r?un(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(cn))):\"all\"===r?[\"all\"].concat(t.slice(1).map(cn)):\"none\"===r?[\"all\"].concat(t.slice(1).map(cn).map(pn)):\"in\"===r?fn(t[1],t.slice(2)):\"!in\"===r?pn(fn(t[1],t.slice(2))):\"has\"===r?hn(t[1]):\"!has\"===r?pn(hn(t[1])):\"within\"!==r||t}function un(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function fn(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some((function(t){return typeof t!=typeof e[0]}))?[\"filter-in-large\",t,[\"literal\",e.sort(ln)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function hn(t){switch(t){case\"$type\":return!0;case\"$id\":return[\"filter-has-id\"];default:return[\"filter-has\",t]}}function pn(t){return[\"!\",t]}function dn(t){return an(zt(t.value))?rn(It({},t,{expressionContext:\"filter\",valueSpec:{value:\"boolean\"}})):function t(e){var r=e.value,n=e.key;if(\"array\"!==Fr(r))return[new Ct(n,r,\"array expected, \"+Fr(r)+\" found\")];var i,a=e.styleSpec,o=[];if(r.length<1)return[new Ct(n,r,\"filter array must have at least 1 element\")];switch(o=o.concat(nn({key:n+\"[0]\",value:r[0],valueSpec:a.filter_operator,style:e.style,styleSpec:e.styleSpec})),Ot(r[0])){case\"<\":case\"<=\":case\">\":case\">=\":r.length>=2&&\"$type\"===Ot(r[1])&&o.push(new Ct(n,r,'\"$type\" cannot be use with operator \"'+r[0]+'\"'));case\"==\":case\"!=\":3!==r.length&&o.push(new Ct(n,r,'filter array for operator \"'+r[0]+'\" must have 3 elements'));case\"in\":case\"!in\":r.length>=2&&\"string\"!==(i=Fr(r[1]))&&o.push(new Ct(n+\"[1]\",r[1],\"string expected, \"+i+\" 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r=t.key,n=t.style,i=t.styleSpec,a=t.value,o=t.objectKey,s=i[e+\"_\"+t.layerType];if(!s)return[];var l=o.match(/^(.*)-transition$/);if(\"paint\"===e&&l&&s[l[1]]&&s[l[1]].transition)return kn({key:r,value:a,valueSpec:i.transition,style:n,styleSpec:i});var c,u=t.valueSpec||s[o];if(!u)return[new Ct(r,a,'unknown property \"'+o+'\"')];if(\"string\"===Fr(a)&&zr(u)&&!u.tokens&&(c=/^{([^}]+)}$/.exec(a)))return[new Ct(r,a,'\"'+o+'\" does not support interpolation syntax\\nUse an identity property function instead: `{ \"type\": \"identity\", \"property\": '+JSON.stringify(c[1])+\" }`.\")];var f=[];return\"symbol\"===t.layerType&&(\"text-field\"===o&&n&&!n.glyphs&&f.push(new Ct(r,a,'use of \"text-field\" requires a style \"glyphs\" property')),\"text-font\"===o&&Br(zt(a))&&\"identity\"===Ot(a.type)&&f.push(new Ct(r,a,'\"text-font\" does not support identity 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Kr(t,e);if(Yr(t)){var r=Jr(t,e);if(\"error\"===r.result)throw new Error(r.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return r.value}var n=t;return\"string\"==typeof t&&\"color\"===e.type&&(n=te.parse(t)),{kind:\"constant\",evaluate:function(){return n}}}(void 0===e?t.specification.default:e,t.specification)};di.prototype.isDataDriven=function(){return\"source\"===this.expression.kind||\"composite\"===this.expression.kind},di.prototype.possiblyEvaluate=function(t,e,r){return this.property.possiblyEvaluate(this,t,e,r)};var gi=function(t){this.property=t,this.value=new di(t,void 0)};gi.prototype.transitioned=function(t,e){return new vi(this.property,this.value,e,u({},t.transition,this.transition),t.now)},gi.prototype.untransitioned=function(){return new vi(this.property,this.value,null,{},0)};var mi=function(t){this._properties=t,this._values=Object.create(t.defaultTransitionablePropertyValues)};mi.prototype.getValue=function(t){return x(this._values[t].value.value)},mi.prototype.setValue=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new gi(this._values[t].property)),this._values[t].value=new di(this._values[t].property,null===e?void 0:x(e))},mi.prototype.getTransition=function(t){return x(this._values[t].transition)},mi.prototype.setTransition=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new gi(this._values[t].property)),this._values[t].transition=x(e)||void 0},mi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i);var a=this.getTransition(n);void 0!==a&&(t[n+\"-transition\"]=a)}return t},mi.prototype.transitioned=function(t,e){for(var r=new yi(this._properties),n=0,i=Object.keys(this._values);n<i.length;n+=1){var a=i[n];r._values[a]=this._values[a].transitioned(t,e._values[a])}return r},mi.prototype.untransitioned=function(){for(var t=new yi(this._properties),e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e];t._values[n]=this._values[n].untransitioned()}return t};var vi=function(t,e,r,n,i){this.property=t,this.value=e,this.begin=i+n.delay||0,this.end=this.begin+n.duration||0,t.specification.transition&&(n.delay||n.duration)&&(this.prior=r)};vi.prototype.possiblyEvaluate=function(t,e,r){var n=t.now||0,i=this.value.possiblyEvaluate(t,e,r),a=this.prior;if(a){if(n>this.end)return this.prior=null,i;if(this.value.isDataDriven())return this.prior=null,i;if(n<this.begin)return a.possiblyEvaluate(t,e,r);var o=(n-this.begin)/(this.end-this.begin);return this.property.interpolate(a.possiblyEvaluate(t,e,r),i,function(t){if(t<=0)return 0;if(t>=1)return 1;var e=t*t,r=e*t;return 4*(t<.5?r:3*(t-e)+r-.75)}(o))}return i};var yi=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};yi.prototype.possiblyEvaluate=function(t,e,r){for(var n=new _i(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n},yi.prototype.hasTransition=function(){for(var t=0,e=Object.keys(this._values);t<e.length;t+=1){var r=e[t];if(this._values[r].prior)return!0}return!1};var xi=function(t){this._properties=t,this._values=Object.create(t.defaultPropertyValues)};xi.prototype.getValue=function(t){return x(this._values[t].value)},xi.prototype.setValue=function(t,e){this._values[t]=new di(this._values[t].property,null===e?void 0:x(e))},xi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i)}return t},xi.prototype.possiblyEvaluate=function(t,e,r){for(var n=new _i(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n};var bi=function(t,e,r){this.property=t,this.value=e,this.parameters=r};bi.prototype.isConstant=function(){return\"constant\"===this.value.kind},bi.prototype.constantOr=function(t){return\"constant\"===this.value.kind?this.value.value:t},bi.prototype.evaluate=function(t,e,r,n){return this.property.evaluate(this.value,this.parameters,t,e,r,n)};var _i=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};_i.prototype.get=function(t){return this._values[t]};var wi=function(t){this.specification=t};wi.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},wi.prototype.interpolate=function(t,e,r){var n=Ge[this.specification.type];return n?n(t,e,r):t};var Ti=function(t,e){this.specification=t,this.overrides=e};Ti.prototype.possiblyEvaluate=function(t,e,r,n){return\"constant\"===t.expression.kind||\"camera\"===t.expression.kind?new bi(this,{kind:\"constant\",value:t.expression.evaluate(e,null,{},r,n)},e):new bi(this,t.expression,e)},Ti.prototype.interpolate=function(t,e,r){if(\"constant\"!==t.value.kind||\"constant\"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new bi(this,{kind:\"constant\",value:void 0},t.parameters);var n=Ge[this.specification.type];return n?new bi(this,{kind:\"constant\",value:n(t.value.value,e.value.value,r)},t.parameters):t},Ti.prototype.evaluate=function(t,e,r,n,i,a){return\"constant\"===t.kind?t.value:t.evaluate(e,r,n,i,a)};var ki=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0===t.value)return new bi(this,{kind:\"constant\",value:void 0},e);if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n),a=\"resolvedImage\"===t.property.specification.type&&\"string\"!=typeof i?i.name:i,o=this._calculate(a,a,a,e);return new bi(this,{kind:\"constant\",value:o},e)}if(\"camera\"===t.expression.kind){var s=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new bi(this,{kind:\"constant\",value:s},e)}return new bi(this,t.expression,e)},e.prototype.evaluate=function(t,e,r,n,i,a){if(\"source\"===t.kind){var o=t.evaluate(e,r,n,i,a);return this._calculate(o,o,o,e)}return\"composite\"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value},e.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(Ti),Ai=function(t){this.specification=t};Ai.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n);return this._calculate(i,i,i,e)}return this._calculate(t.expression.evaluate(new pi(Math.floor(e.zoom-1),e)),t.expression.evaluate(new pi(Math.floor(e.zoom),e)),t.expression.evaluate(new pi(Math.floor(e.zoom+1),e)),e)}},Ai.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},Ai.prototype.interpolate=function(t){return t};var Mi=function(t){this.specification=t};Mi.prototype.possiblyEvaluate=function(t,e,r,n){return!!t.expression.evaluate(e,null,{},r,n)},Mi.prototype.interpolate=function(){return!1};var Si=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[],t){var r=t[e];r.specification.overridable&&this.overridableProperties.push(e);var n=this.defaultPropertyValues[e]=new di(r,void 0),i=this.defaultTransitionablePropertyValues[e]=new gi(r);this.defaultTransitioningPropertyValues[e]=i.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};Nn(\"DataDrivenProperty\",Ti),Nn(\"DataConstantProperty\",wi),Nn(\"CrossFadedDataDrivenProperty\",ki),Nn(\"CrossFadedProperty\",Ai),Nn(\"ColorRampProperty\",Mi);var Ei=function(t){function e(e,r){if(t.call(this),this.id=e.id,this.type=e.type,this._featureFilter={filter:function(){return!0},needGeometry:!1},\"custom\"!==e.type&&(e=e,this.metadata=e.metadata,this.minzoom=e.minzoom,this.maxzoom=e.maxzoom,\"background\"!==e.type&&(this.source=e.source,this.sourceLayer=e[\"source-layer\"],this.filter=e.filter),r.layout&&(this._unevaluatedLayout=new xi(r.layout)),r.paint)){for(var n in this._transitionablePaint=new mi(r.paint),e.paint)this.setPaintProperty(n,e.paint[n],{validate:!1});for(var i in e.layout)this.setLayoutProperty(i,e.layout[i],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new _i(r.paint)}}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getCrossfadeParameters=function(){return this._crossfadeParameters},e.prototype.getLayoutProperty=function(t){return\"visibility\"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".layout.\"+t;if(this._validate(In,n,t,e,r))return}\"visibility\"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e},e.prototype.getPaintProperty=function(t){return m(t,\"-transition\")?this._transitionablePaint.getTransition(t.slice(0,-\"-transition\".length)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".paint.\"+t;if(this._validate(Pn,n,t,e,r))return!1}if(m(t,\"-transition\"))return this._transitionablePaint.setTransition(t.slice(0,-\"-transition\".length),e||void 0),!1;var i=this._transitionablePaint._values[t],a=\"cross-faded-data-driven\"===i.property.specification[\"property-type\"],o=i.value.isDataDriven(),s=i.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);var l=this._transitionablePaint._values[t].value;return l.isDataDriven()||o||a||this._handleOverridablePaintPropertyUpdate(t,s,l)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){},e.prototype._handleOverridablePaintPropertyUpdate=function(t,e,r){return!1},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||(!!(this.maxzoom&&t>=this.maxzoom)||\"none\"===this.visibility)},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t,e){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t,void 0,e)),this.paint=this._transitioningPaint.possiblyEvaluate(t,void 0,e)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,\"source-layer\":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),y(t,(function(t,e){return!(void 0===t||\"layout\"===e&&!Object.keys(t).length||\"paint\"===e&&!Object.keys(t).length)}))},e.prototype._validate=function(t,e,r,n,i){return void 0===i&&(i={}),(!i||!1!==i.validate)&&On(this,t.call(Ln,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:Lt,style:{glyphs:!0,sprite:!0}}))},e.prototype.is3D=function(){return!1},e.prototype.isTileClipped=function(){return!1},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e.prototype.isStateDependent=function(){for(var t in this.paint._values){var e=this.paint.get(t);if(e instanceof bi&&zr(e.property.specification)&&((\"source\"===e.value.kind||\"composite\"===e.value.kind)&&e.value.isStateDependent))return!0}return!1},e}(Et),Li={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},Ci=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},Pi=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function Ii(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map((function(t){var i,a=(i=t.type,Li[i].BYTES_PER_ELEMENT),o=r=Oi(r,Math.max(e,a)),s=t.components||1;return n=Math.max(n,a),r+=a*s,{name:t.name,type:t.type,components:s,offset:o}})),size:Oi(r,Math.max(n,e)),alignment:e}}function Oi(t,e){return Math.ceil(t/e)*e}Pi.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},Pi.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},Pi.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},Pi.prototype.clear=function(){this.length=0},Pi.prototype.resize=function(t){this.reserve(t),this.length=t},Pi.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);var e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}},Pi.prototype._refreshViews=function(){throw new Error(\"_refreshViews() must be implemented by each concrete StructArray layout\")};var zi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.int16[n+0]=e,this.int16[n+1]=r,t},e}(Pi);zi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout2i4\",zi);var Di=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.int16[a+0]=e,this.int16[a+1]=r,this.int16[a+2]=n,this.int16[a+3]=i,t},e}(Pi);Di.prototype.bytesPerElement=8,Nn(\"StructArrayLayout4i8\",Di);var Ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Pi);Ri.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2i4i12\",Ri);var Fi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=i,this.uint8[l+6]=a,this.uint8[l+7]=o,t},e}(Pi);Fi.prototype.bytesPerElement=8,Nn(\"StructArrayLayout2i4ub8\",Fi);var Bi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c){var u=this.length;return this.resize(u+1),this.emplace(u,t,e,r,n,i,a,o,s,l,c)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u){var f=9*t,h=18*t;return this.uint16[f+0]=e,this.uint16[f+1]=r,this.uint16[f+2]=n,this.uint16[f+3]=i,this.uint16[f+4]=a,this.uint16[f+5]=o,this.uint16[f+6]=s,this.uint16[f+7]=l,this.uint8[h+16]=c,this.uint8[h+17]=u,t},e}(Pi);Bi.prototype.bytesPerElement=18,Nn(\"StructArrayLayout8ui2ub18\",Bi);var Ni=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f){var h=this.length;return this.resize(h+1),this.emplace(h,t,e,r,n,i,a,o,s,l,c,u,f)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h){var p=12*t;return this.int16[p+0]=e,this.int16[p+1]=r,this.int16[p+2]=n,this.int16[p+3]=i,this.uint16[p+4]=a,this.uint16[p+5]=o,this.uint16[p+6]=s,this.uint16[p+7]=l,this.int16[p+8]=c,this.int16[p+9]=u,this.int16[p+10]=f,this.int16[p+11]=h,t},e}(Pi);Ni.prototype.bytesPerElement=24,Nn(\"StructArrayLayout4i4ui4i24\",Ni);var ji=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.float32[i+0]=e,this.float32[i+1]=r,this.float32[i+2]=n,t},e}(Pi);ji.prototype.bytesPerElement=12,Nn(\"StructArrayLayout3f12\",ji);var Ui=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint32[r+0]=e,t},e}(Pi);Ui.prototype.bytesPerElement=4,Nn(\"StructArrayLayout1ul4\",Ui);var Vi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l){var c=this.length;return this.resize(c+1),this.emplace(c,t,e,r,n,i,a,o,s,l)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c){var u=10*t,f=5*t;return this.int16[u+0]=e,this.int16[u+1]=r,this.int16[u+2]=n,this.int16[u+3]=i,this.int16[u+4]=a,this.int16[u+5]=o,this.uint32[f+3]=s,this.uint16[u+8]=l,this.uint16[u+9]=c,t},e}(Pi);Vi.prototype.bytesPerElement=20,Nn(\"StructArrayLayout6i1ul2ui20\",Vi);var qi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Pi);qi.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2i2i2i12\",qi);var Hi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n,i)},e.prototype.emplace=function(t,e,r,n,i,a){var o=4*t,s=8*t;return this.float32[o+0]=e,this.float32[o+1]=r,this.float32[o+2]=n,this.int16[s+6]=i,this.int16[s+7]=a,t},e}(Pi);Hi.prototype.bytesPerElement=16,Nn(\"StructArrayLayout2f1f2i16\",Hi);var Gi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=12*t,o=3*t;return this.uint8[a+0]=e,this.uint8[a+1]=r,this.float32[o+1]=n,this.float32[o+2]=i,t},e}(Pi);Gi.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2ub2f12\",Gi);var Yi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.uint16[i+0]=e,this.uint16[i+1]=r,this.uint16[i+2]=n,t},e}(Pi);Yi.prototype.bytesPerElement=6,Nn(\"StructArrayLayout3ui6\",Yi);var Wi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m){var v=this.length;return this.resize(v+1),this.emplace(v,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v){var y=24*t,x=12*t,b=48*t;return this.int16[y+0]=e,this.int16[y+1]=r,this.uint16[y+2]=n,this.uint16[y+3]=i,this.uint32[x+2]=a,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[y+10]=l,this.uint16[y+11]=c,this.uint16[y+12]=u,this.float32[x+7]=f,this.float32[x+8]=h,this.uint8[b+36]=p,this.uint8[b+37]=d,this.uint8[b+38]=g,this.uint32[x+10]=m,this.int16[y+22]=v,t},e}(Pi);Wi.prototype.bytesPerElement=48,Nn(\"StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48\",Wi);var Xi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,A,M,S){var E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,A,M,S)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,A,M,S,E){var L=34*t,C=17*t;return this.int16[L+0]=e,this.int16[L+1]=r,this.int16[L+2]=n,this.int16[L+3]=i,this.int16[L+4]=a,this.int16[L+5]=o,this.int16[L+6]=s,this.int16[L+7]=l,this.uint16[L+8]=c,this.uint16[L+9]=u,this.uint16[L+10]=f,this.uint16[L+11]=h,this.uint16[L+12]=p,this.uint16[L+13]=d,this.uint16[L+14]=g,this.uint16[L+15]=m,this.uint16[L+16]=v,this.uint16[L+17]=y,this.uint16[L+18]=x,this.uint16[L+19]=b,this.uint16[L+20]=_,this.uint16[L+21]=w,this.uint16[L+22]=T,this.uint32[C+12]=k,this.float32[C+13]=A,this.float32[C+14]=M,this.float32[C+15]=S,this.float32[C+16]=E,t},e}(Pi);Xi.prototype.bytesPerElement=68,Nn(\"StructArrayLayout8i15ui1ul4f68\",Xi);var Zi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.float32[r+0]=e,t},e}(Pi);Zi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout1f4\",Zi);var Ji=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,t},e}(Pi);Ji.prototype.bytesPerElement=6,Nn(\"StructArrayLayout3i6\",Ji);var Ki=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=2*t,a=4*t;return this.uint32[i+0]=e,this.uint16[a+2]=r,this.uint16[a+3]=n,t},e}(Pi);Ki.prototype.bytesPerElement=8,Nn(\"StructArrayLayout1ul2ui8\",Ki);var Qi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.uint16[n+0]=e,this.uint16[n+1]=r,t},e}(Pi);Qi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout2ui4\",Qi);var $i=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint16[r+0]=e,t},e}(Pi);$i.prototype.bytesPerElement=2,Nn(\"StructArrayLayout1ui2\",$i);var ta=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.float32[n+0]=e,this.float32[n+1]=r,t},e}(Pi);ta.prototype.bytesPerElement=8,Nn(\"StructArrayLayout2f8\",ta);var ea=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.float32[a+0]=e,this.float32[a+1]=r,this.float32[a+2]=n,this.float32[a+3]=i,t},e}(Pi);ea.prototype.bytesPerElement=16,Nn(\"StructArrayLayout4f16\",ea);var ra=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},anchorPoint:{configurable:!0}};return r.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},r.x1.get=function(){return this._structArray.int16[this._pos2+2]},r.y1.get=function(){return this._structArray.int16[this._pos2+3]},r.x2.get=function(){return this._structArray.int16[this._pos2+4]},r.y2.get=function(){return this._structArray.int16[this._pos2+5]},r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.anchorPoint.get=function(){return new i(this.anchorPointX,this.anchorPointY)},Object.defineProperties(e.prototype,r),e}(Ci);ra.prototype.size=20;var na=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new ra(this,t)},e}(Vi);Nn(\"CollisionBoxArray\",na);var ia=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},glyphStartIndex:{configurable:!0},numGlyphs:{configurable:!0},vertexStartIndex:{configurable:!0},lineStartIndex:{configurable:!0},lineLength:{configurable:!0},segment:{configurable:!0},lowerSize:{configurable:!0},upperSize:{configurable:!0},lineOffsetX:{configurable:!0},lineOffsetY:{configurable:!0},writingMode:{configurable:!0},placedOrientation:{configurable:!0},hidden:{configurable:!0},crossTileID:{configurable:!0},associatedIconIndex:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.glyphStartIndex.get=function(){return this._structArray.uint16[this._pos2+2]},r.numGlyphs.get=function(){return this._structArray.uint16[this._pos2+3]},r.vertexStartIndex.get=function(){return this._structArray.uint32[this._pos4+2]},r.lineStartIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.lineLength.get=function(){return this._structArray.uint32[this._pos4+4]},r.segment.get=function(){return this._structArray.uint16[this._pos2+10]},r.lowerSize.get=function(){return this._structArray.uint16[this._pos2+11]},r.upperSize.get=function(){return this._structArray.uint16[this._pos2+12]},r.lineOffsetX.get=function(){return this._structArray.float32[this._pos4+7]},r.lineOffsetY.get=function(){return this._structArray.float32[this._pos4+8]},r.writingMode.get=function(){return this._structArray.uint8[this._pos1+36]},r.placedOrientation.get=function(){return this._structArray.uint8[this._pos1+37]},r.placedOrientation.set=function(t){this._structArray.uint8[this._pos1+37]=t},r.hidden.get=function(){return this._structArray.uint8[this._pos1+38]},r.hidden.set=function(t){this._structArray.uint8[this._pos1+38]=t},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+10]=t},r.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(e.prototype,r),e}(Ci);ia.prototype.size=48;var aa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new ia(this,t)},e}(Wi);Nn(\"PlacedSymbolArray\",aa);var oa=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},rightJustifiedTextSymbolIndex:{configurable:!0},centerJustifiedTextSymbolIndex:{configurable:!0},leftJustifiedTextSymbolIndex:{configurable:!0},verticalPlacedTextSymbolIndex:{configurable:!0},placedIconSymbolIndex:{configurable:!0},verticalPlacedIconSymbolIndex:{configurable:!0},key:{configurable:!0},textBoxStartIndex:{configurable:!0},textBoxEndIndex:{configurable:!0},verticalTextBoxStartIndex:{configurable:!0},verticalTextBoxEndIndex:{configurable:!0},iconBoxStartIndex:{configurable:!0},iconBoxEndIndex:{configurable:!0},verticalIconBoxStartIndex:{configurable:!0},verticalIconBoxEndIndex:{configurable:!0},featureIndex:{configurable:!0},numHorizontalGlyphVertices:{configurable:!0},numVerticalGlyphVertices:{configurable:!0},numIconVertices:{configurable:!0},numVerticalIconVertices:{configurable:!0},useRuntimeCollisionCircles:{configurable:!0},crossTileID:{configurable:!0},textBoxScale:{configurable:!0},textOffset0:{configurable:!0},textOffset1:{configurable:!0},collisionCircleDiameter:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},r.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},r.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},r.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},r.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},r.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},r.key.get=function(){return this._structArray.uint16[this._pos2+8]},r.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},r.verticalTextBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+11]},r.verticalTextBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+12]},r.iconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+13]},r.iconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+14]},r.verticalIconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+15]},r.verticalIconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+16]},r.featureIndex.get=function(){return this._structArray.uint16[this._pos2+17]},r.numHorizontalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+18]},r.numVerticalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+19]},r.numIconVertices.get=function(){return this._structArray.uint16[this._pos2+20]},r.numVerticalIconVertices.get=function(){return this._structArray.uint16[this._pos2+21]},r.useRuntimeCollisionCircles.get=function(){return this._structArray.uint16[this._pos2+22]},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+12]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+12]=t},r.textBoxScale.get=function(){return this._structArray.float32[this._pos4+13]},r.textOffset0.get=function(){return this._structArray.float32[this._pos4+14]},r.textOffset1.get=function(){return this._structArray.float32[this._pos4+15]},r.collisionCircleDiameter.get=function(){return this._structArray.float32[this._pos4+16]},Object.defineProperties(e.prototype,r),e}(Ci);oa.prototype.size=68;var sa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new oa(this,t)},e}(Xi);Nn(\"SymbolInstanceArray\",sa);var la=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getoffsetX=function(t){return this.float32[1*t+0]},e}(Zi);Nn(\"GlyphOffsetArray\",la);var ca=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getx=function(t){return this.int16[3*t+0]},e.prototype.gety=function(t){return this.int16[3*t+1]},e.prototype.gettileUnitDistanceFromAnchor=function(t){return this.int16[3*t+2]},e}(Ji);Nn(\"SymbolLineVertexArray\",ca);var ua=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0}};return r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+0]},r.sourceLayerIndex.get=function(){return 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t.paint._values)if(r(a)){var o=t.paint.get(a);if(o instanceof bi&&zr(o.property.specification)){var s=Va(a,t.type),l=o.value,c=o.property.specification.type,u=o.property.useIntegerZoom,f=o.property.specification[\"property-type\"],h=\"cross-faded\"===f||\"cross-faded-data-driven\"===f;if(\"constant\"===l.kind)this.binders[a]=h?new Ra(l.value,s):new Da(l.value,s,c),i.push(\"/u_\"+a);else if(\"source\"===l.kind||h){var p=qa(a,c,\"source\");this.binders[a]=h?new Na(l,c,u,e,p,t.id):new Fa(l,s,c,p),i.push(\"/a_\"+a)}else{var d=qa(a,c,\"composite\");this.binders[a]=new Ba(l,s,c,u,e,d),i.push(\"/z_\"+a)}}}this.cacheKey=i.sort().join(\"\")};ja.prototype.getMaxValue=function(t){var e=this.binders[t];return e instanceof Fa||e instanceof Ba?e.maxValue:0},ja.prototype.populatePaintArrays=function(t,e,r,n,i){for(var a in this.binders){var o=this.binders[a];(o instanceof Fa||o instanceof Ba||o instanceof Na)&&o.populatePaintArray(t,e,r,n,i)}},ja.prototype.setConstantPatternPositions=function(t,e){for(var r in this.binders){var n=this.binders[r];n instanceof Ra&&n.setConstantPatternPositions(t,e)}},ja.prototype.updatePaintArrays=function(t,e,r,n,i){var a=!1;for(var o in t)for(var s=0,l=e.getPositions(o);s<l.length;s+=1){var c=l[s],u=r.feature(c.index);for(var f in this.binders){var h=this.binders[f];if((h instanceof Fa||h instanceof Ba||h instanceof Na)&&!0===h.expression.isStateDependent){var p=n.paint.get(f);h.expression=p.value,h.updatePaintArray(c.start,c.end,u,t[o],i),a=!0}}}return a},ja.prototype.defines=function(){var t=[];for(var e in this.binders){var r=this.binders[e];(r instanceof Da||r instanceof Ra)&&t.push.apply(t,r.uniformNames.map((function(t){return\"#define HAS_UNIFORM_\"+t})))}return t},ja.prototype.getPaintVertexBuffers=function(){return this._buffers},ja.prototype.getUniforms=function(t,e){var r=[];for(var n in this.binders){var i=this.binders[n];if(i instanceof Da||i instanceof Ra||i instanceof Ba)for(var a=0,o=i.uniformNames;a<o.length;a+=1){var s=o[a];if(e[s]){var l=i.getBinding(t,e[s],s);r.push({name:s,property:n,binding:l})}}}return r},ja.prototype.setUniforms=function(t,e,r,n){for(var i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.name,l=o.property,c=o.binding;this.binders[l].setUniform(c,n,r.get(l),s)}},ja.prototype.updatePaintBuffers=function(t){for(var e in this._buffers=[],this.binders){var r=this.binders[e];if(t&&r instanceof Na){var n=2===t.fromScale?r.zoomInPaintVertexBuffer:r.zoomOutPaintVertexBuffer;n&&this._buffers.push(n)}else(r instanceof Fa||r instanceof Ba)&&r.paintVertexBuffer&&this._buffers.push(r.paintVertexBuffer)}},ja.prototype.upload=function(t){for(var e in this.binders){var r=this.binders[e];(r instanceof Fa||r instanceof Ba||r instanceof Na)&&r.upload(t)}this.updatePaintBuffers()},ja.prototype.destroy=function(){for(var t in this.binders){var e=this.binders[t];(e instanceof Fa||e instanceof Ba||e instanceof Na)&&e.destroy()}};var Ua=function(t,e,r,n){void 0===n&&(n=function(){return!0}),this.programConfigurations={};for(var i=0,a=e;i<a.length;i+=1){var o=a[i];this.programConfigurations[o.id]=new ja(o,r,n,t)}this.needsUpload=!1,this._featureMap=new _a,this._bufferOffset=0};function Va(t,e){return{\"text-opacity\":[\"opacity\"],\"icon-opacity\":[\"opacity\"],\"text-color\":[\"fill_color\"],\"icon-color\":[\"fill_color\"],\"text-halo-color\":[\"halo_color\"],\"icon-halo-color\":[\"halo_color\"],\"text-halo-blur\":[\"halo_blur\"],\"icon-halo-blur\":[\"halo_blur\"],\"text-halo-width\":[\"halo_width\"],\"icon-halo-width\":[\"halo_width\"],\"line-gap-width\":[\"gapwidth\"],\"line-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"],\"fill-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"],\"fill-extrusion-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"]}[t]||[t.replace(e+\"-\",\"\").replace(/-/g,\"_\")]}function qa(t,e,r){var n={color:{source:ta,composite:ea},number:{source:Zi,composite:ta}},i=function(t){return{\"line-pattern\":{source:Bi,composite:Bi},\"fill-pattern\":{source:Bi,composite:Bi},\"fill-extrusion-pattern\":{source:Bi,composite:Bi}}[t]}(t);return 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c=t.readVarint();n=7&c,a=c>>3}if(a--,1===n||2===n)o+=t.readSVarint(),s+=t.readSVarint(),1===n&&(e&&l.push(e),e=[]),e.push(new i(o,s));else{if(7!==n)throw new Error(\"unknown command \"+n);e&&e.push(e[0].clone())}}return e&&l.push(e),l},ws.prototype.bbox=function(){var t=this._pbf;t.pos=this._geometry;for(var e=t.readVarint()+t.pos,r=1,n=0,i=0,a=0,o=1/0,s=-1/0,l=1/0,c=-1/0;t.pos<e;){if(n<=0){var u=t.readVarint();r=7&u,n=u>>3}if(n--,1===r||2===r)(i+=t.readSVarint())<o&&(o=i),i>s&&(s=i),(a+=t.readSVarint())<l&&(l=a),a>c&&(c=a);else if(7!==r)throw new Error(\"unknown command \"+r)}return[o,l,s,c]},ws.prototype.toGeoJSON=function(t,e,r){var n,i,a=this.extent*Math.pow(2,r),o=this.extent*t,s=this.extent*e,l=this.loadGeometry(),c=ws.types[this.type];function u(t){for(var e=0;e<t.length;e++){var r=t[e],n=180-360*(r.y+s)/a;t[e]=[360*(r.x+o)/a-180,360/Math.PI*Math.atan(Math.exp(n*Math.PI/180))-90]}}switch(this.type){case 1:var f=[];for(n=0;n<l.length;n++)f[n]=l[n][0];u(l=f);break;case 2:for(n=0;n<l.length;n++)u(l[n]);break;case 3:for(l=function(t){var e=t.length;if(e<=1)return[t];for(var r,n,i=[],a=0;a<e;a++){var o=ks(t[a]);0!==o&&(void 0===n&&(n=o<0),n===o<0?(r&&i.push(r),r=[t[a]]):r.push(t[a]))}r&&i.push(r);return i}(l),n=0;n<l.length;n++)for(i=0;i<l[n].length;i++)u(l[n][i])}1===l.length?l=l[0]:c=\"Multi\"+c;var h={type:\"Feature\",geometry:{type:c,coordinates:l},properties:this.properties};return\"id\"in this&&(h.id=this.id),h};var As=Ms;function Ms(t,e){this.version=1,this.name=null,this.extent=4096,this.length=0,this._pbf=t,this._keys=[],this._values=[],this._features=[],t.readFields(Ss,this,e),this.length=this._features.length}function Ss(t,e,r){15===t?e.version=r.readVarint():1===t?e.name=r.readString():5===t?e.extent=r.readVarint():2===t?e._features.push(r.pos):3===t?e._keys.push(r.readString()):4===t&&e._values.push(function(t){var e=null,r=t.readVarint()+t.pos;for(;t.pos<r;){var n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function Es(t,e,r){if(3===t){var n=new As(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}Ms.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error(\"feature index out of bounds\");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new _s(this._pbf,e,this.extent,this._keys,this._values)};var Ls={VectorTile:function(t,e){this.layers=t.readFields(Es,{},e)},VectorTileFeature:_s,VectorTileLayer:As},Cs=Ls.VectorTileFeature.types,Ps=Math.pow(2,13);function Is(t,e,r,n,i,a,o,s){t.emplaceBack(e,r,2*Math.floor(n*Ps)+o,i*Ps*2,a*Ps*2,Math.round(s))}var Os=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new Ri,this.indexArray=new Yi,this.programConfigurations=new Ua(bs,t.layers,t.zoom),this.segments=new pa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function zs(t,e){return t.x===e.x&&(t.x<0||t.x>8192)||t.y===e.y&&(t.y<0||t.y>8192)}function Ds(t){return t.every((function(t){return t.x<0}))||t.every((function(t){return t.x>8192}))||t.every((function(t){return t.y<0}))||t.every((function(t){return t.y>8192}))}Os.prototype.populate=function(t,e,r){this.features=[],this.hasPattern=ds(\"fill-extrusion\",this.layers,e);for(var n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.feature,s=a.id,l=a.index,c=a.sourceLayerIndex,u=this.layers[0]._featureFilter.needGeometry,f={type:o.type,id:s,properties:o.properties,geometry:u?Ya(o):[]};if(this.layers[0]._featureFilter.filter(new pi(this.zoom),f,r)){var h={id:s,sourceLayerIndex:c,index:l,geometry:u?f.geometry:Ya(o),properties:o.properties,type:o.type,patterns:{}};void 0!==o.id&&(h.id=o.id),this.hasPattern?this.features.push(gs(\"fill-extrusion\",this.layers,h,this.zoom,e)):this.addFeature(h,h.geometry,l,r,{}),e.featureIndex.insert(o,h.geometry,l,c,this.index,!0)}}},Os.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.features;n<i.length;n+=1){var a=i[n],o=a.geometry;this.addFeature(a,o,a.index,e,r)}},Os.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},Os.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},Os.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},Os.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,bs),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},Os.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},Os.prototype.addFeature=function(t,e,r,n,i){for(var a=0,o=hs(e,500);a<o.length;a+=1){for(var s=o[a],l=0,c=0,u=s;c<u.length;c+=1){l+=u[c].length}for(var f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray),h=0,p=s;h<p.length;h+=1){var d=p[h];if(0!==d.length&&!Ds(d))for(var g=0,m=0;m<d.length;m++){var v=d[m];if(m>=1){var y=d[m-1];if(!zs(v,y)){f.vertexLength+4>pa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var x=v.sub(y)._perp()._unit(),b=y.dist(v);g+b>32768&&(g=0),Is(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,0,g),Is(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,1,g),g+=b,Is(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,0,g),Is(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,1,g);var _=f.vertexLength;this.indexArray.emplaceBack(_,_+2,_+1),this.indexArray.emplaceBack(_+1,_+2,_+3),f.vertexLength+=4,f.primitiveLength+=2}}}}if(f.vertexLength+l>pa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(l,this.layoutVertexArray,this.indexArray)),\"Polygon\"===Cs[t.type]){for(var w=[],T=[],k=f.vertexLength,A=0,M=s;A<M.length;A+=1){var S=M[A];if(0!==S.length){S!==s[0]&&T.push(w.length/2);for(var E=0;E<S.length;E++){var L=S[E];Is(this.layoutVertexArray,L.x,L.y,0,0,1,1,0),w.push(L.x),w.push(L.y)}}}for(var C=Do(w,T),P=0;P<C.length;P+=3)this.indexArray.emplaceBack(k+C[P],k+C[P+2],k+C[P+1]);f.primitiveLength+=C.length/3,f.vertexLength+=l}}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},Nn(\"FillExtrusionBucket\",Os,{omit:[\"layers\",\"features\"]});var Rs={paint:new Si({\"fill-extrusion-opacity\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-opacity\"]),\"fill-extrusion-color\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-color\"]),\"fill-extrusion-translate\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-translate\"]),\"fill-extrusion-translate-anchor\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-translate-anchor\"]),\"fill-extrusion-pattern\":new ki(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-pattern\"]),\"fill-extrusion-height\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-height\"]),\"fill-extrusion-base\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-base\"]),\"fill-extrusion-vertical-gradient\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-vertical-gradient\"])})},Fs=function(t){function e(e){t.call(this,e,Rs)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.createBucket=function(t){return new Os(t)},e.prototype.queryRadius=function(){return so(this.paint.get(\"fill-extrusion-translate\"))},e.prototype.is3D=function(){return!0},e.prototype.queryIntersectsFeature=function(t,e,r,n,a,o,s,l){var c=lo(t,this.paint.get(\"fill-extrusion-translate\"),this.paint.get(\"fill-extrusion-translate-anchor\"),o.angle,s),u=this.paint.get(\"fill-extrusion-height\").evaluate(e,r),f=this.paint.get(\"fill-extrusion-base\").evaluate(e,r),h=function(t,e,r,n){for(var a=[],o=0,s=t;o<s.length;o+=1){var l=s[o],c=[l.x,l.y,n,1];xo(c,c,e),a.push(new i(c[0]/c[3],c[1]/c[3]))}return a}(c,l,0,0),p=function(t,e,r,n){for(var a=[],o=[],s=n[8]*e,l=n[9]*e,c=n[10]*e,u=n[11]*e,f=n[8]*r,h=n[9]*r,p=n[10]*r,d=n[11]*r,g=0,m=t;g<m.length;g+=1){for(var v=m[g],y=[],x=[],b=0,_=v;b<_.length;b+=1){var w=_[b],T=w.x,k=w.y,A=n[0]*T+n[4]*k+n[12],M=n[1]*T+n[5]*k+n[13],S=n[2]*T+n[6]*k+n[14],E=n[3]*T+n[7]*k+n[15],L=S+c,C=E+u,P=A+f,I=M+h,O=S+p,z=E+d,D=new i((A+s)/C,(M+l)/C);D.z=L/C,y.push(D);var R=new i(P/z,I/z);R.z=O/z,x.push(R)}a.push(y),o.push(x)}return[a,o]}(n,f,u,l);return function(t,e,r){var n=1/0;Ka(r,e)&&(n=Ns(r,e[0]));for(var i=0;i<e.length;i++)for(var a=e[i],o=t[i],s=0;s<a.length-1;s++){var l=a[s],c=a[s+1],u=o[s],f=o[s+1],h=[l,c,f,u,l];Za(r,h)&&(n=Math.min(n,Ns(r,h)))}return n!==1/0&&n}(p[0],p[1],h)},e}(Ei);function Bs(t,e){return t.x*e.x+t.y*e.y}function Ns(t,e){if(1===t.length){for(var r,n=0,i=e[n++];!r||i.equals(r);)if(!(r=e[n++]))return 1/0;for(;n<e.length;n++){var a=e[n],o=t[0],s=r.sub(i),l=a.sub(i),c=o.sub(i),u=Bs(s,s),f=Bs(s,l),h=Bs(l,l),p=Bs(c,s),d=Bs(c,l),g=u*h-f*f,m=(h*p-f*d)/g,v=(u*d-f*p)/g,y=1-m-v,x=i.z*y+r.z*m+a.z*v;if(isFinite(x))return x}return 1/0}for(var b=1/0,_=0,w=e;_<w.length;_+=1){var T=w[_];b=Math.min(b,T.z)}return b}var js=Ii([{name:\"a_pos_normal\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}],4).members,Us=Ls.VectorTileFeature.types,Vs=Math.cos(Math.PI/180*37.5),qs=Math.pow(2,14)/.5,Hs=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new Fi,this.indexArray=new Yi,this.programConfigurations=new Ua(js,t.layers,t.zoom),this.segments=new pa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};Hs.prototype.populate=function(t,e,r){this.hasPattern=ds(\"line\",this.layers,e);for(var n=this.layers[0].layout.get(\"line-sort-key\"),i=[],a=0,o=t;a<o.length;a+=1){var s=o[a],l=s.feature,c=s.id,u=s.index,f=s.sourceLayerIndex,h=this.layers[0]._featureFilter.needGeometry,p={type:l.type,id:c,properties:l.properties,geometry:h?Ya(l):[]};if(this.layers[0]._featureFilter.filter(new pi(this.zoom),p,r)){h||(p.geometry=Ya(l));var d=n?n.evaluate(p,{},r):void 0,g={id:c,properties:l.properties,type:l.type,sourceLayerIndex:f,index:u,geometry:p.geometry,patterns:{},sortKey:d};i.push(g)}}n&&i.sort((function(t,e){return t.sortKey-e.sortKey}));for(var m=0,v=i;m<v.length;m+=1){var y=v[m],x=y,b=x.geometry,_=x.index,w=x.sourceLayerIndex;if(this.hasPattern){var T=gs(\"line\",this.layers,y,this.zoom,e);this.patternFeatures.push(T)}else this.addFeature(y,b,_,r,{});var k=t[_].feature;e.featureIndex.insert(k,b,_,w,this.index)}},Hs.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},Hs.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.patternFeatures;n<i.length;n+=1){var a=i[n];this.addFeature(a,a.geometry,a.index,e,r)}},Hs.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},Hs.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},Hs.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,js),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},Hs.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},Hs.prototype.addFeature=function(t,e,r,n,i){for(var a=this.layers[0].layout,o=a.get(\"line-join\").evaluate(t,{}),s=a.get(\"line-cap\"),l=a.get(\"line-miter-limit\"),c=a.get(\"line-round-limit\"),u=0,f=e;u<f.length;u+=1){var h=f[u];this.addLine(h,t,o,s,l,c)}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},Hs.prototype.addLine=function(t,e,r,n,i,a){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,e.properties&&e.properties.hasOwnProperty(\"mapbox_clip_start\")&&e.properties.hasOwnProperty(\"mapbox_clip_end\")){this.clipStart=+e.properties.mapbox_clip_start,this.clipEnd=+e.properties.mapbox_clip_end;for(var o=0;o<t.length-1;o++)this.totalDistance+=t[o].dist(t[o+1]);this.updateScaledDistance()}for(var s=\"Polygon\"===Us[e.type],l=t.length;l>=2&&t[l-1].equals(t[l-2]);)l--;for(var c=0;c<l-1&&t[c].equals(t[c+1]);)c++;if(!(l<(s?3:2))){\"bevel\"===r&&(i=1.05);var u,f=this.overscaling<=16?122880/(512*this.overscaling):0,h=this.segments.prepareSegment(10*l,this.layoutVertexArray,this.indexArray),p=void 0,d=void 0,g=void 0,m=void 0;this.e1=this.e2=-1,s&&(u=t[l-2],m=t[c].sub(u)._unit()._perp());for(var v=c;v<l;v++)if(!(d=v===l-1?s?t[c+1]:void 0:t[v+1])||!t[v].equals(d)){m&&(g=m),u&&(p=u),u=t[v],m=d?d.sub(u)._unit()._perp():g;var y=(g=g||m).add(m);0===y.x&&0===y.y||y._unit();var x=g.x*m.x+g.y*m.y,b=y.x*m.x+y.y*m.y,_=0!==b?1/b:1/0,w=2*Math.sqrt(2-2*b),T=b<Vs&&p&&d,k=g.x*m.y-g.y*m.x>0;if(T&&v>c){var A=u.dist(p);if(A>2*f){var M=u.sub(u.sub(p)._mult(f/A)._round());this.updateDistance(p,M),this.addCurrentVertex(M,g,0,0,h),p=M}}var S=p&&d,E=S?r:s?\"butt\":n;if(S&&\"round\"===E&&(_<a?E=\"miter\":_<=2&&(E=\"fakeround\")),\"miter\"===E&&_>i&&(E=\"bevel\"),\"bevel\"===E&&(_>2&&(E=\"flipbevel\"),_<i&&(E=\"miter\")),p&&this.updateDistance(p,u),\"miter\"===E)y._mult(_),this.addCurrentVertex(u,y,0,0,h);else if(\"flipbevel\"===E){if(_>100)y=m.mult(-1);else{var L=_*g.add(m).mag()/g.sub(m).mag();y._perp()._mult(L*(k?-1:1))}this.addCurrentVertex(u,y,0,0,h),this.addCurrentVertex(u,y.mult(-1),0,0,h)}else if(\"bevel\"===E||\"fakeround\"===E){var C=-Math.sqrt(_*_-1),P=k?C:0,I=k?0:C;if(p&&this.addCurrentVertex(u,g,P,I,h),\"fakeround\"===E)for(var O=Math.round(180*w/Math.PI/20),z=1;z<O;z++){var D=z/O;if(.5!==D){var R=D-.5;D+=D*R*(D-1)*((1.0904+x*(x*(3.55645-1.43519*x)-3.2452))*R*R+(.848013+x*(.215638*x-1.06021)))}var F=m.sub(g)._mult(D)._add(g)._unit()._mult(k?-1:1);this.addHalfVertex(u,F.x,F.y,!1,k,0,h)}d&&this.addCurrentVertex(u,m,-P,-I,h)}else if(\"butt\"===E)this.addCurrentVertex(u,y,0,0,h);else if(\"square\"===E){var B=p?1:-1;this.addCurrentVertex(u,y,B,B,h)}else\"round\"===E&&(p&&(this.addCurrentVertex(u,g,0,0,h),this.addCurrentVertex(u,g,1,1,h,!0)),d&&(this.addCurrentVertex(u,m,-1,-1,h,!0),this.addCurrentVertex(u,m,0,0,h)));if(T&&v<l-1){var N=u.dist(d);if(N>2*f){var j=u.add(d.sub(u)._mult(f/N)._round());this.updateDistance(u,j),this.addCurrentVertex(j,m,0,0,h),u=j}}}}},Hs.prototype.addCurrentVertex=function(t,e,r,n,i,a){void 0===a&&(a=!1);var o=e.x+e.y*r,s=e.y-e.x*r,l=-e.x+e.y*n,c=-e.y-e.x*n;this.addHalfVertex(t,o,s,a,!1,r,i),this.addHalfVertex(t,l,c,a,!0,-n,i),this.distance>qs/2&&0===this.totalDistance&&(this.distance=0,this.addCurrentVertex(t,e,r,n,i,a))},Hs.prototype.addHalfVertex=function(t,e,r,n,i,a,o){var s=t.x,l=t.y,c=.5*this.scaledDistance;this.layoutVertexArray.emplaceBack((s<<1)+(n?1:0),(l<<1)+(i?1:0),Math.round(63*e)+128,Math.round(63*r)+128,1+(0===a?0:a<0?-1:1)|(63&c)<<2,c>>6);var u=o.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,u),o.primitiveLength++),i?this.e2=u:this.e1=u},Hs.prototype.updateScaledDistance=function(){this.scaledDistance=this.totalDistance>0?(this.clipStart+(this.clipEnd-this.clipStart)*this.distance/this.totalDistance)*(qs-1):this.distance},Hs.prototype.updateDistance=function(t,e){this.distance+=t.dist(e),this.updateScaledDistance()},Nn(\"LineBucket\",Hs,{omit:[\"layers\",\"patternFeatures\"]});var Gs=new Si({\"line-cap\":new wi(Lt.layout_line[\"line-cap\"]),\"line-join\":new Ti(Lt.layout_line[\"line-join\"]),\"line-miter-limit\":new wi(Lt.layout_line[\"line-miter-limit\"]),\"line-round-limit\":new wi(Lt.layout_line[\"line-round-limit\"]),\"line-sort-key\":new Ti(Lt.layout_line[\"line-sort-key\"])}),Ys={paint:new Si({\"line-opacity\":new Ti(Lt.paint_line[\"line-opacity\"]),\"line-color\":new Ti(Lt.paint_line[\"line-color\"]),\"line-translate\":new wi(Lt.paint_line[\"line-translate\"]),\"line-translate-anchor\":new wi(Lt.paint_line[\"line-translate-anchor\"]),\"line-width\":new Ti(Lt.paint_line[\"line-width\"]),\"line-gap-width\":new Ti(Lt.paint_line[\"line-gap-width\"]),\"line-offset\":new Ti(Lt.paint_line[\"line-offset\"]),\"line-blur\":new Ti(Lt.paint_line[\"line-blur\"]),\"line-dasharray\":new Ai(Lt.paint_line[\"line-dasharray\"]),\"line-pattern\":new ki(Lt.paint_line[\"line-pattern\"]),\"line-gradient\":new Mi(Lt.paint_line[\"line-gradient\"])}),layout:Gs},Ws=new(function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(e,r){return r=new pi(Math.floor(r.zoom),{now:r.now,fadeDuration:r.fadeDuration,zoomHistory:r.zoomHistory,transition:r.transition}),t.prototype.possiblyEvaluate.call(this,e,r)},e.prototype.evaluate=function(e,r,n,i){return r=u({},r,{zoom:Math.floor(r.zoom)}),t.prototype.evaluate.call(this,e,r,n,i)},e}(Ti))(Ys.paint.properties[\"line-width\"].specification);Ws.useIntegerZoom=!0;var Xs=function(t){function e(e){t.call(this,e,Ys)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._handleSpecialPaintPropertyUpdate=function(t){\"line-gradient\"===t&&this._updateGradient()},e.prototype._updateGradient=function(){var t=this._transitionablePaint._values[\"line-gradient\"].value.expression;this.gradient=Co(t,\"lineProgress\"),this.gradientTexture=null},e.prototype.recalculate=function(e,r){t.prototype.recalculate.call(this,e,r),this.paint._values[\"line-floorwidth\"]=Ws.possiblyEvaluate(this._transitioningPaint._values[\"line-width\"].value,e)},e.prototype.createBucket=function(t){return new Hs(t)},e.prototype.queryRadius=function(t){var e=t,r=Zs(oo(\"line-width\",this,e),oo(\"line-gap-width\",this,e)),n=oo(\"line-offset\",this,e);return r/2+Math.abs(n)+so(this.paint.get(\"line-translate\"))},e.prototype.queryIntersectsFeature=function(t,e,r,n,a,o,s){var l=lo(t,this.paint.get(\"line-translate\"),this.paint.get(\"line-translate-anchor\"),o.angle,s),c=s/2*Zs(this.paint.get(\"line-width\").evaluate(e,r),this.paint.get(\"line-gap-width\").evaluate(e,r)),u=this.paint.get(\"line-offset\").evaluate(e,r);return u&&(n=function(t,e){for(var r=[],n=new i(0,0),a=0;a<t.length;a++){for(var o=t[a],s=[],l=0;l<o.length;l++){var c=o[l-1],u=o[l],f=o[l+1],h=0===l?n:u.sub(c)._unit()._perp(),p=l===o.length-1?n:f.sub(u)._unit()._perp(),d=h._add(p)._unit(),g=d.x*p.x+d.y*p.y;d._mult(1/g),s.push(d._mult(e)._add(u))}r.push(s)}return r}(n,u*s)),function(t,e,r){for(var n=0;n<e.length;n++){var i=e[n];if(t.length>=3)for(var a=0;a<i.length;a++)if(io(t,i[a]))return!0;if(Qa(t,i,r))return!0}return!1}(l,n,c)},e.prototype.isTileClipped=function(){return!0},e}(Ei);function Zs(t,e){return e>0?e+2*t:t}var 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el(t,e,r){return t.sections.forEach((function(t){t.text=function(t,e,r){var n=e.layout.get(\"text-transform\").evaluate(r,{});return\"uppercase\"===n?t=t.toLocaleUpperCase():\"lowercase\"===n&&(t=t.toLocaleLowerCase()),hi.applyArabicShaping&&(t=hi.applyArabicShaping(t)),t}(t.text,e,r)})),t}var 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nl=function(t,e,r,n,i){var a,o,s=8*i-n-1,l=(1<<s)-1,c=l>>1,u=-7,f=r?i-1:0,h=r?-1:1,p=t[e+f];for(f+=h,a=p&(1<<-u)-1,p>>=-u,u+=s;u>0;a=256*a+t[e+f],f+=h,u-=8);for(o=a&(1<<-u)-1,a>>=-u,u+=n;u>0;o=256*o+t[e+f],f+=h,u-=8);if(0===a)a=1-c;else{if(a===l)return o?NaN:1/0*(p?-1:1);o+=Math.pow(2,n),a-=c}return(p?-1:1)*o*Math.pow(2,a-n)},il=function(t,e,r,n,i,a){var o,s,l,c=8*a-i-1,u=(1<<c)-1,f=u>>1,h=23===i?Math.pow(2,-24)-Math.pow(2,-77):0,p=n?0:a-1,d=n?1:-1,g=e<0||0===e&&1/e<0?1:0;for(e=Math.abs(e),isNaN(e)||e===1/0?(s=isNaN(e)?1:0,o=u):(o=Math.floor(Math.log(e)/Math.LN2),e*(l=Math.pow(2,-o))<1&&(o--,l*=2),(e+=o+f>=1?h/l:h*Math.pow(2,1-f))*l>=2&&(o++,l/=2),o+f>=u?(s=0,o=u):o+f>=1?(s=(e*l-1)*Math.pow(2,i),o+=f):(s=e*Math.pow(2,f-1)*Math.pow(2,i),o=0));i>=8;t[r+p]=255&s,p+=d,s/=256,i-=8);for(o=o<<i|s,c+=i;c>0;t[r+p]=255&o,p+=d,o/=256,c-=8);t[r+p-d]|=128*g},al=ol;function ol(t){this.buf=ArrayBuffer.isView&&ArrayBuffer.isView(t)?t:new 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e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed32());return t},readPackedFixed64:function(t){if(this.type!==ol.Bytes)return t.push(this.readFixed64());var e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readFixed64());return t},readPackedSFixed64:function(t){if(this.type!==ol.Bytes)return t.push(this.readSFixed64());var e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed64());return t},skip:function(t){var e=7&t;if(e===ol.Varint)for(;this.buf[this.pos++]>127;);else if(e===ol.Bytes)this.pos=this.readVarint()+this.pos;else if(e===ol.Fixed32)this.pos+=4;else{if(e!==ol.Fixed64)throw new Error(\"Unimplemented type: \"+e);this.pos+=8}},writeTag:function(t,e){this.writeVarint(t<<3|e)},realloc:function(t){for(var e=this.length||16;e<this.pos+t;)e*=2;if(e!==this.length){var r=new Uint8Array(e);r.set(this.buf),this.buf=r,this.length=e}},finish:function(){return this.length=this.pos,this.pos=0,this.buf.subarray(0,this.length)},writeFixed32:function(t){this.realloc(4),_l(this.buf,t,this.pos),this.pos+=4},writeSFixed32:function(t){this.realloc(4),_l(this.buf,t,this.pos),this.pos+=4},writeFixed64:function(t){this.realloc(8),_l(this.buf,-1&t,this.pos),_l(this.buf,Math.floor(t*(1/4294967296)),this.pos+4),this.pos+=8},writeSFixed64:function(t){this.realloc(8),_l(this.buf,-1&t,this.pos),_l(this.buf,Math.floor(t*(1/4294967296)),this.pos+4),this.pos+=8},writeVarint:function(t){(t=+t||0)>268435455||t<0?function(t,e){var r,n;t>=0?(r=t%4294967296|0,n=t/4294967296|0):(n=~(-t/4294967296),4294967295^(r=~(-t%4294967296))?r=r+1|0:(r=0,n=n+1|0));if(t>=0x10000000000000000||t<-0x10000000000000000)throw new Error(\"Given varint doesn't fit into 10 bytes\");e.realloc(10),function(t,e,r){r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos]=127&t}(r,0,e),function(t,e){var r=(7&t)<<4;if(e.buf[e.pos++]|=r|((t>>>=3)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;e.buf[e.pos++]=127&t}(n,e)}(t,this):(this.realloc(4),this.buf[this.pos++]=127&t|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=t>>>7&127))))},writeSVarint:function(t){this.writeVarint(t<0?2*-t-1:2*t)},writeBoolean:function(t){this.writeVarint(Boolean(t))},writeString:function(t){t=String(t),this.realloc(4*t.length),this.pos++;var e=this.pos;this.pos=function(t,e,r){for(var n,i,a=0;a<e.length;a++){if((n=e.charCodeAt(a))>55295&&n<57344){if(!i){n>56319||a+1===e.length?(t[r++]=239,t[r++]=191,t[r++]=189):i=n;continue}if(n<56320){t[r++]=239,t[r++]=191,t[r++]=189,i=n;continue}n=i-55296<<10|n-56320|65536,i=null}else i&&(t[r++]=239,t[r++]=191,t[r++]=189,i=null);n<128?t[r++]=n:(n<2048?t[r++]=n>>6|192:(n<65536?t[r++]=n>>12|224:(t[r++]=n>>18|240,t[r++]=n>>12&63|128),t[r++]=n>>6&63|128),t[r++]=63&n|128)}return r}(this.buf,t,this.pos);var r=this.pos-e;r>=128&&ul(e,r,this),this.pos=e-1,this.writeVarint(r),this.pos+=r},writeFloat:function(t){this.realloc(4),il(this.buf,t,this.pos,!0,23,4),this.pos+=4},writeDouble:function(t){this.realloc(8),il(this.buf,t,this.pos,!0,52,8),this.pos+=8},writeBytes:function(t){var e=t.length;this.writeVarint(e),this.realloc(e);for(var r=0;r<e;r++)this.buf[this.pos++]=t[r]},writeRawMessage:function(t,e){this.pos++;var r=this.pos;t(e,this);var n=this.pos-r;n>=128&&ul(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,ol.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,fl,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,hl,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,gl,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,pl,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,dl,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,ml,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,vl,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,yl,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,xl,e)},writeBytesField:function(t,e){this.writeTag(t,ol.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,ol.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,ol.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,ol.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,ol.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,ol.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,ol.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,ol.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,ol.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,ol.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,Boolean(e))}};function Tl(t,e,r){1===t&&r.readMessage(kl,e)}function kl(t,e,r){if(3===t){var n=r.readMessage(Al,{}),i=n.id,a=n.bitmap,o=n.width,s=n.height,l=n.left,c=n.top,u=n.advance;e.push({id:i,bitmap:new So({width:o+6,height:s+6},a),metrics:{width:o,height:s,left:l,top:c,advance:u}})}}function Al(t,e,r){1===t?e.id=r.readVarint():2===t?e.bitmap=r.readBytes():3===t?e.width=r.readVarint():4===t?e.height=r.readVarint():5===t?e.left=r.readSVarint():6===t?e.top=r.readSVarint():7===t&&(e.advance=r.readVarint())}function Ml(t){for(var e=0,r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];e+=a.w*a.h,r=Math.max(r,a.w)}t.sort((function(t,e){return e.h-t.h}));for(var o=[{x:0,y:0,w:Math.max(Math.ceil(Math.sqrt(e/.95)),r),h:1/0}],s=0,l=0,c=0,u=t;c<u.length;c+=1)for(var f=u[c],h=o.length-1;h>=0;h--){var p=o[h];if(!(f.w>p.w||f.h>p.h)){if(f.x=p.x,f.y=p.y,l=Math.max(l,f.y+f.h),s=Math.max(s,f.x+f.w),f.w===p.w&&f.h===p.h){var d=o.pop();h<o.length&&(o[h]=d)}else 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Eo({width:o||1,height:s||1});for(var c in t){var u=t[c],f=r[c].paddedRect;Eo.copy(u.data,l,{x:0,y:0},{x:f.x+1,y:f.y+1},u.data)}for(var h in e){var p=e[h],d=n[h].paddedRect,g=d.x+1,m=d.y+1,v=p.data.width,y=p.data.height;Eo.copy(p.data,l,{x:0,y:0},{x:g,y:m},p.data),Eo.copy(p.data,l,{x:0,y:y-1},{x:g,y:m-1},{width:v,height:1}),Eo.copy(p.data,l,{x:0,y:0},{x:g,y:m+y},{width:v,height:1}),Eo.copy(p.data,l,{x:v-1,y:0},{x:g-1,y:m},{width:1,height:y}),Eo.copy(p.data,l,{x:0,y:0},{x:g+v,y:m},{width:1,height:y})}this.image=l,this.iconPositions=r,this.patternPositions=n};Ll.prototype.addImages=function(t,e,r){for(var n in t){var i=t[n],a={x:0,y:0,w:i.data.width+2,h:i.data.height+2};r.push(a),e[n]=new Sl(a,i),i.hasRenderCallback&&this.haveRenderCallbacks.push(n)}},Ll.prototype.patchUpdatedImages=function(t,e){for(var r in t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},Ll.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var n=t.tl,i=n[0],a=n[1];r.update(e.data,void 0,{x:i,y:a})}},Nn(\"ImagePosition\",Sl),Nn(\"ImageAtlas\",Ll);var Cl={horizontal:1,vertical:2,horizontalOnly:3};var Pl=function(){this.scale=1,this.fontStack=\"\",this.imageName=null};Pl.forText=function(t,e){var r=new Pl;return r.scale=t||1,r.fontStack=e,r},Pl.forImage=function(t){var e=new Pl;return e.imageName=t,e};var Il=function(){this.text=\"\",this.sectionIndex=[],this.sections=[],this.imageSectionID=null};function Ol(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g){var m,v=Il.fromFeature(t,i);f===Cl.vertical&&v.verticalizePunctuation();var y=hi.processBidirectionalText,x=hi.processStyledBidirectionalText;if(y&&1===v.sections.length){m=[];for(var b=0,_=y(v.toString(),jl(v,c,a,e,n,p,d));b<_.length;b+=1){var w=_[b],T=new Il;T.text=w,T.sections=v.sections;for(var k=0;k<w.length;k++)T.sectionIndex.push(0);m.push(T)}}else if(x){m=[];for(var A=0,M=x(v.text,v.sectionIndex,jl(v,c,a,e,n,p,d));A<M.length;A+=1){var S=M[A],E=new Il;E.text=S[0],E.sectionIndex=S[1],E.sections=v.sections,m.push(E)}}else m=function(t,e){for(var r=[],n=t.text,i=0,a=0,o=e;a<o.length;a+=1){var s=o[a];r.push(t.substring(i,s)),i=s}return i<n.length&&r.push(t.substring(i,n.length)),r}(v,jl(v,c,a,e,n,p,d));var L=[],C={positionedLines:L,text:v.toString(),top:u[1],bottom:u[1],left:u[0],right:u[0],writingMode:f,iconsInText:!1,verticalizable:!1};return function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=0,p=-17,d=0,g=0,m=\"right\"===s?1:\"left\"===s?0:.5,v=0,y=0,x=i;y<x.length;y+=1){var b=x[y];b.trim();var _=b.getMaxScale(),w=24*(_-1),T={positionedGlyphs:[],lineOffset:0};t.positionedLines[v]=T;var k=T.positionedGlyphs,A=0;if(b.length()){for(var M=0;M<b.length();M++){var S=b.getSection(M),E=b.getSectionIndex(M),L=b.getCharCode(M),C=0,P=null,I=null,O=null,z=24,D=!(l===Cl.horizontal||!u&&!Zn(L)||u&&(zl[L]||(Y=L,Yn.Arabic(Y)||Yn[\"Arabic Supplement\"](Y)||Yn[\"Arabic Extended-A\"](Y)||Yn[\"Arabic Presentation Forms-A\"](Y)||Yn[\"Arabic Presentation Forms-B\"](Y))));if(S.imageName){var R=n[S.imageName];if(!R)continue;O=S.imageName,t.iconsInText=t.iconsInText||!0,I=R.paddedRect;var F=R.displaySize;S.scale=24*S.scale/f,P={width:F[0],height:F[1],left:1,top:-3,advance:D?F[1]:F[0]};var B=24-F[1]*S.scale;C=w+B,z=P.advance;var N=D?F[0]*S.scale-24*_:F[1]*S.scale-24*_;N>0&&N>A&&(A=N)}else{var j=r[S.fontStack],U=j&&j[L];if(U&&U.rect)I=U.rect,P=U.metrics;else{var V=e[S.fontStack],q=V&&V[L];if(!q)continue;P=q.metrics}C=24*(_-S.scale)}D?(t.verticalizable=!0,k.push({glyph:L,imageName:O,x:h,y:p+C,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:I}),h+=z*S.scale+c):(k.push({glyph:L,imageName:O,x:h,y:p+C,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:I}),h+=P.advance*S.scale+c)}if(0!==k.length){var H=h-c;d=Math.max(H,d),Vl(k,0,k.length-1,m,A)}h=0;var G=a*_+A;T.lineOffset=Math.max(A,w),p+=G,g=Math.max(G,g),++v}else p+=a,++v}var Y;var W=p- -17,X=Ul(o),Z=X.horizontalAlign,J=X.verticalAlign;(function(t,e,r,n,i,a,o,s,l){var c=(e-r)*i,u=0;u=a!==o?-s*n- -17:(-n*l+.5)*o;for(var f=0,h=t;f<h.length;f+=1)for(var p=h[f],d=0,g=p.positionedGlyphs;d<g.length;d+=1){var m=g[d];m.x+=c,m.y+=u}})(t.positionedLines,m,Z,J,d,g,a,W,i.length),t.top+=-J*W,t.bottom=t.top+W,t.left+=-Z*d,t.right=t.left+d}(C,e,r,n,m,o,s,l,f,c,h,g),!function(t){for(var e=0,r=t;e<r.length;e+=1){if(0!==r[e].positionedGlyphs.length)return!1}return!0}(L)&&C}Il.fromFeature=function(t,e){for(var r=new Il,n=0;n<t.sections.length;n++){var i=t.sections[n];i.image?r.addImageSection(i):r.addTextSection(i,e)}return r},Il.prototype.length=function(){return this.text.length},Il.prototype.getSection=function(t){return this.sections[this.sectionIndex[t]]},Il.prototype.getSectionIndex=function(t){return this.sectionIndex[t]},Il.prototype.getCharCode=function(t){return this.text.charCodeAt(t)},Il.prototype.verticalizePunctuation=function(){this.text=function(t){for(var e=\"\",r=0;r<t.length;r++){var n=t.charCodeAt(r+1)||null,i=t.charCodeAt(r-1)||null;(!n||!Jn(n)||rl[t[r+1]])&&(!i||!Jn(i)||rl[t[r-1]])&&rl[t[r]]?e+=rl[t[r]]:e+=t[r]}return e}(this.text)},Il.prototype.trim=function(){for(var t=0,e=0;e<this.text.length&&zl[this.text.charCodeAt(e)];e++)t++;for(var 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e=this.data,r=this.compare,n=this.length>>1,i=e[t];t<n;){var a=1+(t<<1),o=e[a],s=a+1;if(s<this.length&&r(e[s],o)<0&&(a=s,o=e[s]),r(o,i)>=0)break;e[t]=o,t=a}e[t]=i};var pc=Number.POSITIVE_INFINITY;function dc(t,e){return e[1]!==pc?function(t,e,r){var n=0,i=0;switch(e=Math.abs(e),r=Math.abs(r),t){case\"top-right\":case\"top-left\":case\"top\":i=r-7;break;case\"bottom-right\":case\"bottom-left\":case\"bottom\":i=7-r}switch(t){case\"top-right\":case\"bottom-right\":case\"right\":n=-e;break;case\"top-left\":case\"bottom-left\":case\"left\":n=e}return[n,i]}(t,e[0],e[1]):function(t,e){var r=0,n=0;e<0&&(e=0);var i=e/Math.sqrt(2);switch(t){case\"top-right\":case\"top-left\":n=i-7;break;case\"bottom-right\":case\"bottom-left\":n=7-i;break;case\"bottom\":n=7-e;break;case\"top\":n=e-7}switch(t){case\"top-right\":case\"bottom-right\":r=-i;break;case\"top-left\":case\"bottom-left\":r=i;break;case\"left\":r=e;break;case\"right\":r=-e}return[r,n]}(t,e[0])}function gc(t){switch(t){case\"right\":case\"top-right\":case\"bottom-right\":return\"right\";case\"left\":case\"top-left\":case\"bottom-left\":return\"left\"}return\"center\"}function mc(t,e,r,n,a,o,s,l,c,u,f,h,p,d,g){var m=function(t,e,r,n,a,o,s,l){for(var c=n.layout.get(\"text-rotate\").evaluate(o,{})*Math.PI/180,u=[],f=0,h=e.positionedLines;f<h.length;f+=1)for(var p=h[f],d=0,g=p.positionedGlyphs;d<g.length;d+=1){var m=g[d];if(m.rect){var v=m.rect||{},y=4,x=!0,b=1,_=0,w=(a||l)&&m.vertical,T=m.metrics.advance*m.scale/2;if(l&&e.verticalizable){var k=24*(m.scale-1),A=(24-m.metrics.width*m.scale)/2;_=p.lineOffset/2-(m.imageName?-A:k)}if(m.imageName){var M=s[m.imageName];x=M.sdf,y=1/(b=M.pixelRatio)}var S=a?[m.x+T,m.y]:[0,0],E=a?[0,0]:[m.x+T+r[0],m.y+r[1]-_],L=[0,0];w&&(L=E,E=[0,0]);var C=(m.metrics.left-y)*m.scale-T+E[0],P=(-m.metrics.top-y)*m.scale+E[1],I=C+v.w*m.scale/b,O=P+v.h*m.scale/b,z=new i(C,P),D=new i(I,P),R=new i(C,O),F=new i(I,O);if(w){var B=new i(-T,T- -17),N=-Math.PI/2,j=12-T,U=m.imageName?j:0,V=new i(22-j,-U),q=new(Function.prototype.bind.apply(i,[null].concat(L)));z._rotateAround(N,B)._add(V)._add(q),D._rotateAround(N,B)._add(V)._add(q),R._rotateAround(N,B)._add(V)._add(q),F._rotateAround(N,B)._add(V)._add(q)}if(c){var H=Math.sin(c),G=Math.cos(c),Y=[G,-H,H,G];z._matMult(Y),D._matMult(Y),R._matMult(Y),F._matMult(Y)}var W=new i(0,0),X=new i(0,0);u.push({tl:z,tr:D,bl:R,br:F,tex:v,writingMode:e.writingMode,glyphOffset:S,sectionIndex:m.sectionIndex,isSDF:x,pixelOffsetTL:W,pixelOffsetBR:X,minFontScaleX:0,minFontScaleY:0})}}return u}(0,r,l,a,o,s,n,t.allowVerticalPlacement),v=t.textSizeData,y=null;\"source\"===v.kind?(y=[128*a.layout.get(\"text-size\").evaluate(s,{})])[0]>32640&&_(t.layerIds[0]+': Value for \"text-size\" is >= 255. Reduce your \"text-size\".'):\"composite\"===v.kind&&((y=[128*d.compositeTextSizes[0].evaluate(s,{},g),128*d.compositeTextSizes[1].evaluate(s,{},g)])[0]>32640||y[1]>32640)&&_(t.layerIds[0]+': Value for \"text-size\" is >= 255. Reduce your \"text-size\".'),t.addSymbols(t.text,m,y,l,o,s,u,e,c.lineStartIndex,c.lineLength,p,g);for(var x=0,b=f;x<b.length;x+=1){h[b[x]]=t.text.placedSymbolArray.length-1}return 4*m.length}function vc(t){for(var e in t)return t[e];return null}function yc(t,e,r,n){var i=t.compareText;if(e in i){for(var a=i[e],o=a.length-1;o>=0;o--)if(n.dist(a[o])<r)return!0}else i[e]=[];return i[e].push(n),!1}var xc=Ls.VectorTileFeature.types,bc=[{name:\"a_fade_opacity\",components:1,type:\"Uint8\",offset:0}];function _c(t,e,r,n,i,a,o,s,l,c,u,f,h){var p=s?Math.min(32640,Math.round(s[0])):0,d=s?Math.min(32640,Math.round(s[1])):0;t.emplaceBack(e,r,Math.round(32*n),Math.round(32*i),a,o,(p<<1)+(l?1:0),d,16*c,16*u,256*f,256*h)}function wc(t,e,r){t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r)}function Tc(t){for(var e=0,r=t.sections;e<r.length;e+=1){if($n(r[e].text))return!0}return!1}var kc=function(t){this.layoutVertexArray=new Ni,this.indexArray=new Yi,this.programConfigurations=t,this.segments=new pa,this.dynamicLayoutVertexArray=new ji,this.opacityVertexArray=new Ui,this.placedSymbolArray=new aa};kc.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length&&0===this.indexArray.length&&0===this.dynamicLayoutVertexArray.length&&0===this.opacityVertexArray.length},kc.prototype.upload=function(t,e,r,n){this.isEmpty()||(r&&(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Js.members),this.indexBuffer=t.createIndexBuffer(this.indexArray,e),this.dynamicLayoutVertexBuffer=t.createVertexBuffer(this.dynamicLayoutVertexArray,Ks.members,!0),this.opacityVertexBuffer=t.createVertexBuffer(this.opacityVertexArray,bc,!0),this.opacityVertexBuffer.itemSize=1),(r||n)&&this.programConfigurations.upload(t))},kc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.dynamicLayoutVertexBuffer.destroy(),this.opacityVertexBuffer.destroy())},Nn(\"SymbolBuffers\",kc);var Ac=function(t,e,r){this.layoutVertexArray=new t,this.layoutAttributes=e,this.indexArray=new r,this.segments=new pa,this.collisionVertexArray=new Gi};Ac.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=t.createVertexBuffer(this.collisionVertexArray,Qs.members,!0)},Ac.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},Nn(\"CollisionBuffers\",Ac);var Mc=function(t){this.collisionBoxArray=t.collisionBoxArray,this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.pixelRatio=t.pixelRatio,this.sourceLayerIndex=t.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=ho([]),this.placementViewportMatrix=ho([]);var e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=Gl(this.zoom,e[\"text-size\"]),this.iconSizeData=Gl(this.zoom,e[\"icon-size\"]);var r=this.layers[0].layout,n=r.get(\"symbol-sort-key\"),i=r.get(\"symbol-z-order\");this.sortFeaturesByKey=\"viewport-y\"!==i&&void 0!==n.constantOr(1);var a=\"viewport-y\"===i||\"auto\"===i&&!this.sortFeaturesByKey;this.sortFeaturesByY=a&&(r.get(\"text-allow-overlap\")||r.get(\"icon-allow-overlap\")||r.get(\"text-ignore-placement\")||r.get(\"icon-ignore-placement\")),\"point\"===r.get(\"symbol-placement\")&&(this.writingModes=r.get(\"text-writing-mode\").map((function(t){return Cl[t]}))),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id})),this.sourceID=t.sourceID};Mc.prototype.createArrays=function(){this.text=new kc(new Ua(Js.members,this.layers,this.zoom,(function(t){return/^text/.test(t)}))),this.icon=new kc(new Ua(Js.members,this.layers,this.zoom,(function(t){return/^icon/.test(t)}))),this.glyphOffsetArray=new la,this.lineVertexArray=new ca,this.symbolInstances=new sa},Mc.prototype.calculateGlyphDependencies=function(t,e,r,n,i){for(var a=0;a<t.length;a++)if(e[t.charCodeAt(a)]=!0,(r||n)&&i){var o=rl[t.charAt(a)];o&&(e[o.charCodeAt(0)]=!0)}},Mc.prototype.populate=function(t,e,r){var n=this.layers[0],i=n.layout,a=i.get(\"text-font\"),o=i.get(\"text-field\"),s=i.get(\"icon-image\"),l=(\"constant\"!==o.value.kind||o.value.value instanceof ne&&!o.value.value.isEmpty()||o.value.value.toString().length>0)&&(\"constant\"!==a.value.kind||a.value.value.length>0),c=\"constant\"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,u=i.get(\"symbol-sort-key\");if(this.features=[],l||c){for(var f=e.iconDependencies,h=e.glyphDependencies,p=e.availableImages,d=new pi(this.zoom),g=0,m=t;g<m.length;g+=1){var v=m[g],y=v.feature,x=v.id,b=v.index,_=v.sourceLayerIndex,w=n._featureFilter.needGeometry,T={type:y.type,id:x,properties:y.properties,geometry:w?Ya(y):[]};if(n._featureFilter.filter(d,T,r)){w||(T.geometry=Ya(y));var k=void 0;if(l){var A=n.getValueAndResolveTokens(\"text-field\",T,r,p),M=ne.factory(A);Tc(M)&&(this.hasRTLText=!0),(!this.hasRTLText||\"unavailable\"===ui()||this.hasRTLText&&hi.isParsed())&&(k=el(M,n,T))}var S=void 0;if(c){var E=n.getValueAndResolveTokens(\"icon-image\",T,r,p);S=E instanceof ie?E:ie.fromString(E)}if(k||S){var L=this.sortFeaturesByKey?u.evaluate(T,{},r):void 0,C={id:x,text:k,icon:S,index:b,sourceLayerIndex:_,geometry:Ya(y),properties:y.properties,type:xc[y.type],sortKey:L};if(this.features.push(C),S&&(f[S.name]=!0),k){var P=a.evaluate(T,{},r).join(\",\"),I=\"map\"===i.get(\"text-rotation-alignment\")&&\"point\"!==i.get(\"symbol-placement\");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(Cl.vertical)>=0;for(var O=0,z=k.sections;O<z.length;O+=1){var D=z[O];if(D.image)f[D.image.name]=!0;else{var R=Wn(k.toString()),F=D.fontStack||P,B=h[F]=h[F]||{};this.calculateGlyphDependencies(D.text,B,I,this.allowVerticalPlacement,R)}}}}}}\"line\"===i.get(\"symbol-placement\")&&(this.features=function(t){var e={},r={},n=[],i=0;function a(e){n.push(t[e]),i++}function o(t,e,i){var a=r[t];return delete r[t],r[e]=a,n[a].geometry[0].pop(),n[a].geometry[0]=n[a].geometry[0].concat(i[0]),a}function s(t,r,i){var a=e[r];return delete e[r],e[t]=a,n[a].geometry[0].shift(),n[a].geometry[0]=i[0].concat(n[a].geometry[0]),a}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}for(var c=0;c<t.length;c++){var u=t[c],f=u.geometry,h=u.text?u.text.toString():null;if(h){var p=l(h,f),d=l(h,f,!0);if(p in r&&d in e&&r[p]!==e[d]){var g=s(p,d,f),m=o(p,d,n[g].geometry);delete e[p],delete r[d],r[l(h,n[m].geometry,!0)]=m,n[g].geometry=null}else p in r?o(p,d,f):d in e?s(p,d,f):(a(c),e[p]=i-1,r[d]=i-1)}else a(c)}return n.filter((function(t){return t.geometry}))}(this.features)),this.sortFeaturesByKey&&this.features.sort((function(t,e){return t.sortKey-e.sortKey}))}},Mc.prototype.update=function(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))},Mc.prototype.isEmpty=function(){return 0===this.symbolInstances.length&&!this.hasRTLText},Mc.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},Mc.prototype.upload=function(t){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(t),this.iconCollisionBox.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},Mc.prototype.destroyDebugData=function(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()},Mc.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()},Mc.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),i=t.dist(e[t.segment]),a={},o=t.segment+1;o<e.length;o++)a[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var c=a[l];this.lineVertexArray.emplaceBack(c.x,c.y,c.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},Mc.prototype.addSymbols=function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=t.indexArray,p=t.layoutVertexArray,d=t.segments.prepareSegment(4*e.length,p,h,a.sortKey),g=this.glyphOffsetArray.length,m=d.vertexLength,v=this.allowVerticalPlacement&&o===Cl.vertical?Math.PI/2:0,y=a.text&&a.text.sections,x=0;x<e.length;x++){var b=e[x],_=b.tl,w=b.tr,T=b.bl,k=b.br,A=b.tex,M=b.pixelOffsetTL,S=b.pixelOffsetBR,E=b.minFontScaleX,L=b.minFontScaleY,C=b.glyphOffset,P=b.isSDF,I=b.sectionIndex,O=d.vertexLength,z=C[1];_c(p,s.x,s.y,_.x,z+_.y,A.x,A.y,r,P,M.x,M.y,E,L),_c(p,s.x,s.y,w.x,z+w.y,A.x+A.w,A.y,r,P,S.x,M.y,E,L),_c(p,s.x,s.y,T.x,z+T.y,A.x,A.y+A.h,r,P,M.x,S.y,E,L),_c(p,s.x,s.y,k.x,z+k.y,A.x+A.w,A.y+A.h,r,P,S.x,S.y,E,L),wc(t.dynamicLayoutVertexArray,s,v),h.emplaceBack(O,O+1,O+2),h.emplaceBack(O+1,O+2,O+3),d.vertexLength+=4,d.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(C[0]),x!==e.length-1&&I===e[x+1].sectionIndex||t.programConfigurations.populatePaintArrays(p.length,a,a.index,{},f,y&&y[I])}t.placedSymbolArray.emplaceBack(s.x,s.y,g,this.glyphOffsetArray.length-g,m,l,c,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,0,!1,0,u)},Mc.prototype._addCollisionDebugVertex=function(t,e,r,n,i,a){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n,i,Math.round(a.x),Math.round(a.y))},Mc.prototype.addCollisionDebugVertices=function(t,e,r,n,a,o,s){var l=a.segments.prepareSegment(4,a.layoutVertexArray,a.indexArray),c=l.vertexLength,u=a.layoutVertexArray,f=a.collisionVertexArray,h=s.anchorX,p=s.anchorY;this._addCollisionDebugVertex(u,f,o,h,p,new i(t,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,n)),this._addCollisionDebugVertex(u,f,o,h,p,new i(t,n)),l.vertexLength+=4;var d=a.indexArray;d.emplaceBack(c,c+1),d.emplaceBack(c+1,c+2),d.emplaceBack(c+2,c+3),d.emplaceBack(c+3,c),l.primitiveLength+=4},Mc.prototype.addDebugCollisionBoxes=function(t,e,r,n){for(var i=t;i<e;i++){var a=this.collisionBoxArray.get(i),o=a.x1,s=a.y1,l=a.x2,c=a.y2;this.addCollisionDebugVertices(o,s,l,c,n?this.textCollisionBox:this.iconCollisionBox,a.anchorPoint,r)}},Mc.prototype.generateCollisionDebugBuffers=function(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new Ac(qi,$s.members,Qi),this.iconCollisionBox=new Ac(qi,$s.members,Qi);for(var t=0;t<this.symbolInstances.length;t++){var e=this.symbolInstances.get(t);this.addDebugCollisionBoxes(e.textBoxStartIndex,e.textBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.verticalTextBoxStartIndex,e.verticalTextBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.iconBoxStartIndex,e.iconBoxEndIndex,e,!1),this.addDebugCollisionBoxes(e.verticalIconBoxStartIndex,e.verticalIconBoxEndIndex,e,!1)}},Mc.prototype._deserializeCollisionBoxesForSymbol=function(t,e,r,n,i,a,o,s,l){for(var c={},u=e;u<r;u++){var f=t.get(u);c.textBox={x1:f.x1,y1:f.y1,x2:f.x2,y2:f.y2,anchorPointX:f.anchorPointX,anchorPointY:f.anchorPointY},c.textFeatureIndex=f.featureIndex;break}for(var h=n;h<i;h++){var p=t.get(h);c.verticalTextBox={x1:p.x1,y1:p.y1,x2:p.x2,y2:p.y2,anchorPointX:p.anchorPointX,anchorPointY:p.anchorPointY},c.verticalTextFeatureIndex=p.featureIndex;break}for(var d=a;d<o;d++){var g=t.get(d);c.iconBox={x1:g.x1,y1:g.y1,x2:g.x2,y2:g.y2,anchorPointX:g.anchorPointX,anchorPointY:g.anchorPointY},c.iconFeatureIndex=g.featureIndex;break}for(var m=s;m<l;m++){var v=t.get(m);c.verticalIconBox={x1:v.x1,y1:v.y1,x2:v.x2,y2:v.y2,anchorPointX:v.anchorPointX,anchorPointY:v.anchorPointY},c.verticalIconFeatureIndex=v.featureIndex;break}return c},Mc.prototype.deserializeCollisionBoxes=function(t){this.collisionArrays=[];for(var e=0;e<this.symbolInstances.length;e++){var r=this.symbolInstances.get(e);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(t,r.textBoxStartIndex,r.textBoxEndIndex,r.verticalTextBoxStartIndex,r.verticalTextBoxEndIndex,r.iconBoxStartIndex,r.iconBoxEndIndex,r.verticalIconBoxStartIndex,r.verticalIconBoxEndIndex))}},Mc.prototype.hasTextData=function(){return this.text.segments.get().length>0},Mc.prototype.hasIconData=function(){return this.icon.segments.get().length>0},Mc.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},Mc.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},Mc.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},Mc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i<n;i+=4)t.indexArray.emplaceBack(i,i+1,i+2),t.indexArray.emplaceBack(i+1,i+2,i+3)},Mc.prototype.getSortedSymbolIndexes=function(t){if(this.sortedAngle===t&&void 0!==this.symbolInstanceIndexes)return this.symbolInstanceIndexes;for(var e=Math.sin(t),r=Math.cos(t),n=[],i=[],a=[],o=0;o<this.symbolInstances.length;++o){a.push(o);var s=this.symbolInstances.get(o);n.push(0|Math.round(e*s.anchorX+r*s.anchorY)),i.push(s.featureIndex)}return a.sort((function(t,e){return n[t]-n[e]||i[e]-i[t]})),a},Mc.prototype.addToSortKeyRanges=function(t,e){var r=this.sortKeyRanges[this.sortKeyRanges.length-1];r&&r.sortKey===e?r.symbolInstanceEnd=t+1:this.sortKeyRanges.push({sortKey:e,symbolInstanceStart:t,symbolInstanceEnd:t+1})},Mc.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r<n.length;r+=1){var i=n[r],a=this.symbolInstances.get(i);this.featureSortOrder.push(a.featureIndex),[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t,r,n){t>=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},Nn(\"SymbolBucket\",Mc,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),Mc.MAX_GLYPHS=65535,Mc.addDynamicAttributes=wc;var Sc=new Si({\"symbol-placement\":new wi(Lt.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new wi(Lt.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new wi(Lt.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new Ti(Lt.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new wi(Lt.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new wi(Lt.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new wi(Lt.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new wi(Lt.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new wi(Lt.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new Ti(Lt.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new wi(Lt.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new wi(Lt.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new Ti(Lt.layout_symbol[\"icon-image\"]),\"icon-rotate\":new Ti(Lt.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new wi(Lt.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new wi(Lt.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new Ti(Lt.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new Ti(Lt.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new wi(Lt.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new wi(Lt.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new wi(Lt.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new Ti(Lt.layout_symbol[\"text-field\"]),\"text-font\":new Ti(Lt.layout_symbol[\"text-font\"]),\"text-size\":new Ti(Lt.layout_symbol[\"text-size\"]),\"text-max-width\":new Ti(Lt.layout_symbol[\"text-max-width\"]),\"text-line-height\":new wi(Lt.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new Ti(Lt.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new Ti(Lt.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new Ti(Lt.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new wi(Lt.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new Ti(Lt.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new wi(Lt.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new wi(Lt.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new Ti(Lt.layout_symbol[\"text-rotate\"]),\"text-padding\":new wi(Lt.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new wi(Lt.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new Ti(Lt.layout_symbol[\"text-transform\"]),\"text-offset\":new Ti(Lt.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new wi(Lt.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new wi(Lt.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new wi(Lt.layout_symbol[\"text-optional\"])}),Ec={paint:new Si({\"icon-opacity\":new Ti(Lt.paint_symbol[\"icon-opacity\"]),\"icon-color\":new Ti(Lt.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new Ti(Lt.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new Ti(Lt.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new Ti(Lt.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new wi(Lt.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new wi(Lt.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new Ti(Lt.paint_symbol[\"text-opacity\"]),\"text-color\":new Ti(Lt.paint_symbol[\"text-color\"],{runtimeType:Ut,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new Ti(Lt.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new Ti(Lt.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new Ti(Lt.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new wi(Lt.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new wi(Lt.paint_symbol[\"text-translate-anchor\"])}),layout:Sc},Lc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Ft,this.defaultValue=t};Lc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},Lc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},Lc.prototype.outputDefined=function(){return!1},Lc.prototype.serialize=function(){return null},Nn(\"FormatSectionOverride\",Lc,{omit:[\"defaultValue\"]});var Cc=function(t){function e(e){t.call(this,e,Ec)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var n=this.layout.get(\"text-writing-mode\");if(n){for(var i=[],a=0,o=n;a<o.length;a+=1){var s=o[a];i.indexOf(s)<0&&i.push(s)}this.layout._values[\"text-writing-mode\"]=i}else this.layout._values[\"text-writing-mode\"]=[\"horizontal\"]}this._setPaintOverrides()},e.prototype.getValueAndResolveTokens=function(t,e,r,n){var i=this.layout.get(t).evaluate(e,{},r,n),a=this._unevaluatedLayout._values[t];return a.isDataDriven()||Yr(a.value)||!i?i:function(t,e){return e.replace(/{([^{}]+)}/g,(function(e,r){return r in t?String(t[r]):\"\"}))}(e.properties,i)},e.prototype.createBucket=function(t){return new Mc(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype._setPaintOverrides=function(){for(var t=0,r=Ec.paint.overridableProperties;t<r.length;t+=1){var n=r[t];if(e.hasPaintOverride(this.layout,n)){var i=this.paint.get(n),a=new Lc(i),o=new Gr(a,i.property.specification),s=null;s=\"constant\"===i.value.kind||\"source\"===i.value.kind?new Xr(\"source\",o):new Zr(\"composite\",o,i.value.zoomStops,i.value._interpolationType),this.paint._values[n]=new bi(i.property,s,i.parameters)}}},e.prototype._handleOverridablePaintPropertyUpdate=function(t,r,n){return!(!this.layout||r.isDataDriven()||n.isDataDriven())&&e.hasPaintOverride(this.layout,t)},e.hasPaintOverride=function(t,e){var r=t.get(\"text-field\"),n=Ec.paint.properties[e],i=!1,a=function(t){for(var e=0,r=t;e<r.length;e+=1){var a=r[e];if(n.overrides&&n.overrides.hasOverride(a))return void(i=!0)}};if(\"constant\"===r.value.kind&&r.value.value instanceof ne)a(r.value.value.sections);else if(\"source\"===r.value.kind){var o=function(t){if(!i)if(t instanceof ce&&se(t.value)===Gt){var e=t.value;a(e.sections)}else t instanceof pe?a(t.sections):t.eachChild(o)},s=r.value;s._styleExpression&&o(s._styleExpression.expression)}return i},e}(Ei),Pc={paint:new Si({\"background-color\":new wi(Lt.paint_background[\"background-color\"]),\"background-pattern\":new Ai(Lt.paint_background[\"background-pattern\"]),\"background-opacity\":new wi(Lt.paint_background[\"background-opacity\"])})},Ic=function(t){function e(e){t.call(this,e,Pc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ei),Oc={paint:new Si({\"raster-opacity\":new wi(Lt.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new wi(Lt.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new wi(Lt.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new wi(Lt.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new wi(Lt.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new wi(Lt.paint_raster[\"raster-contrast\"]),\"raster-resampling\":new wi(Lt.paint_raster[\"raster-resampling\"]),\"raster-fade-duration\":new wi(Lt.paint_raster[\"raster-fade-duration\"])})},zc=function(t){function e(e){t.call(this,e,Oc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ei);var Dc=function(t){function e(e){t.call(this,e,{}),this.implementation=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.is3D=function(){return\"3d\"===this.implementation.renderingMode},e.prototype.hasOffscreenPass=function(){return void 0!==this.implementation.prerender},e.prototype.recalculate=function(){},e.prototype.updateTransitions=function(){},e.prototype.hasTransition=function(){},e.prototype.serialize=function(){},e.prototype.onAdd=function(t){this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},e.prototype.onRemove=function(t){this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},e}(Ei),Rc={circle:_o,heatmap:Po,hillshade:Oo,fill:xs,\"fill-extrusion\":Fs,line:Xs,symbol:Cc,background:Ic,raster:zc};var Fc=self.HTMLImageElement,Bc=self.HTMLCanvasElement,Nc=self.HTMLVideoElement,jc=self.ImageData,Uc=self.ImageBitmap,Vc=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};Vc.prototype.update=function(t,e,r){var n=t.width,i=t.height,a=!(this.size&&this.size[0]===n&&this.size[1]===i||r),o=this.context,s=o.gl;if(this.useMipmap=Boolean(e&&e.useMipmap),s.bindTexture(s.TEXTURE_2D,this.texture),o.pixelStoreUnpackFlipY.set(!1),o.pixelStoreUnpack.set(1),o.pixelStoreUnpackPremultiplyAlpha.set(this.format===s.RGBA&&(!e||!1!==e.premultiply)),a)this.size=[n,i],t instanceof Fc||t instanceof Bc||t instanceof Nc||t instanceof jc||Uc&&t instanceof Uc?s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,s.UNSIGNED_BYTE,t):s.texImage2D(s.TEXTURE_2D,0,this.format,n,i,0,this.format,s.UNSIGNED_BYTE,t.data);else{var l=r||{x:0,y:0},c=l.x,u=l.y;t instanceof Fc||t instanceof Bc||t instanceof Nc||t instanceof jc||Uc&&t instanceof Uc?s.texSubImage2D(s.TEXTURE_2D,0,c,u,s.RGBA,s.UNSIGNED_BYTE,t):s.texSubImage2D(s.TEXTURE_2D,0,c,u,n,i,s.RGBA,s.UNSIGNED_BYTE,t.data)}this.useMipmap&&this.isSizePowerOfTwo()&&s.generateMipmap(s.TEXTURE_2D)},Vc.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},Vc.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},Vc.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var qc=function(t){var e=this;this._callback=t,this._triggered=!1,\"undefined\"!=typeof MessageChannel&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){e._triggered=!1,e._callback()})};qc.prototype.trigger=function(){var t=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout((function(){t._triggered=!1,t._callback()}),0))},qc.prototype.remove=function(){delete this._channel,this._callback=function(){}};var Hc=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},g([\"receive\",\"process\"],this),this.invoker=new qc(this.process),this.target.addEventListener(\"message\",this.receive,!1),this.globalScope=k()?t:self};function Gc(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}Hc.prototype.send=function(t,e,r,n,i){var a=this;void 0===i&&(i=!1);var o=Math.round(1e18*Math.random()).toString(36).substring(0,10);r&&(this.callbacks[o]=r);var s=S(this.globalScope)?void 0:[];return this.target.postMessage({id:o,type:t,hasCallback:!!r,targetMapId:n,mustQueue:i,sourceMapId:this.mapId,data:qn(e,s)},s),{cancel:function(){r&&delete a.callbacks[o],a.target.postMessage({id:o,type:\"<cancel>\",targetMapId:n,sourceMapId:a.mapId})}}},Hc.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"<cancel>\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else k()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Hc.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Hc.prototype.processTask=function(t,e){var r=this;if(\"<response>\"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(Hn(e.error)):n(null,Hn(e.data)))}else{var i=!1,a=S(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:\"<response>\",sourceMapId:r.mapId,error:e?qn(e):null,data:qn(n,a)},a)}:function(t){i=!0},s=null,l=Hn(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var c=e.type.split(\".\");s=this.parent.getWorkerSource(e.sourceMapId,c[0],l.source)[c[1]](l,o)}else o(new Error(\"Could not find function \"+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Hc.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};var Yc=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Yc.prototype.setNorthEast=function(t){return this._ne=t instanceof Wc?new Wc(t.lng,t.lat):Wc.convert(t),this},Yc.prototype.setSouthWest=function(t){return this._sw=t instanceof Wc?new Wc(t.lng,t.lat):Wc.convert(t),this},Yc.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof Wc)e=t,r=t;else{if(!(t instanceof Yc)){if(Array.isArray(t)){if(4===t.length||t.every(Array.isArray)){var a=t;return this.extend(Yc.convert(a))}var o=t;return this.extend(Wc.convert(o))}return this}if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new Wc(e.lng,e.lat),this._ne=new Wc(r.lng,r.lat)),this},Yc.prototype.getCenter=function(){return new Wc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Yc.prototype.getSouthWest=function(){return this._sw},Yc.prototype.getNorthEast=function(){return this._ne},Yc.prototype.getNorthWest=function(){return new Wc(this.getWest(),this.getNorth())},Yc.prototype.getSouthEast=function(){return new Wc(this.getEast(),this.getSouth())},Yc.prototype.getWest=function(){return this._sw.lng},Yc.prototype.getSouth=function(){return this._sw.lat},Yc.prototype.getEast=function(){return this._ne.lng},Yc.prototype.getNorth=function(){return this._ne.lat},Yc.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Yc.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Yc.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Yc.prototype.contains=function(t){var e=Wc.convert(t),r=e.lng,n=e.lat,i=this._sw.lat<=n&&n<=this._ne.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),i&&a},Yc.convert=function(t){return!t||t instanceof Yc?t:new Yc(t)};var Wc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};Wc.prototype.wrap=function(){return new Wc(c(this.lng,-180,180),this.lat)},Wc.prototype.toArray=function(){return[this.lng,this.lat]},Wc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},Wc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return 6371008.8*Math.acos(Math.min(i,1))},Wc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Yc(new Wc(this.lng-r,this.lat-e),new Wc(this.lng+r,this.lat+e))},Wc.convert=function(t){if(t instanceof Wc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Wc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new Wc(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")};var Xc=2*Math.PI*6371008.8;function Zc(t){return Xc*Math.cos(t*Math.PI/180)}function Jc(t){return(180+t)/360}function Kc(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Qc(t,e){return t/Zc(e)}function $c(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var tu=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};tu.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Wc.convert(t);return new tu(Jc(r.lng),Kc(r.lat),Qc(e,r.lat))},tu.prototype.toLngLat=function(){return new Wc(360*this.x-180,$c(this.y))},tu.prototype.toAltitude=function(){return t=this.z,e=this.y,t*Zc($c(e));var t,e},tu.prototype.meterInMercatorCoordinateUnits=function(){return 1/Xc*(t=$c(this.y),1/Math.cos(t*Math.PI/180));var t};var eu=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=iu(0,t,t,e,r)};eu.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},eu.prototype.url=function(t,e){var r,n,i,a,o,s=(r=this.x,n=this.y,i=this.z,a=Gc(256*r,256*(n=Math.pow(2,i)-n-1),i),o=Gc(256*(r+1),256*(n+1),i),a[0]+\",\"+a[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<<a-1)?1:0)+(r&n?2:0);return i}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",String(this.z)).replace(\"{x}\",String(this.x)).replace(\"{y}\",String(\"tms\"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace(\"{quadkey}\",l).replace(\"{bbox-epsg-3857}\",s)},eu.prototype.getTilePoint=function(t){var e=Math.pow(2,this.z);return new i(8192*(t.x*e-this.x),8192*(t.y*e-this.y))},eu.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y};var ru=function(t,e){this.wrap=t,this.canonical=e,this.key=iu(t,e.z,e.z,e.x,e.y)},nu=function(t,e,r,n,i){this.overscaledZ=t,this.wrap=e,this.canonical=new eu(r,+n,+i),this.key=iu(e,t,r,n,i)};function iu(t,e,r,n,i){(t*=2)<0&&(t=-1*t-1);var a=1<<r;return(a*a*t+a*i+n).toString(36)+r.toString(36)+e.toString(36)}nu.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},nu.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new nu(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new nu(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},nu.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?iu(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):iu(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},nu.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},nu.prototype.children=function(t){if(this.overscaledZ>=t)return[new nu(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new nu(e,this.wrap,e,r,n),new nu(e,this.wrap,e,r+1,n),new nu(e,this.wrap,e,r,n+1),new nu(e,this.wrap,e,r+1,n+1)]},nu.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},nu.prototype.wrapped=function(){return new nu(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},nu.prototype.unwrapTo=function(t){return new nu(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},nu.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},nu.prototype.toUnwrapped=function(){return new ru(this.wrap,this.canonical)},nu.prototype.toString=function(){return this.overscaledZ+\"/\"+this.canonical.x+\"/\"+this.canonical.y},nu.prototype.getTilePoint=function(t){return this.canonical.getTilePoint(new tu(t.x-this.wrap,t.y))},Nn(\"CanonicalTileID\",eu),Nn(\"OverscaledTileID\",nu,{omit:[\"posMatrix\"]});var au=function(t,e,r){if(this.uid=t,e.height!==e.width)throw new RangeError(\"DEM tiles must be square\");if(r&&\"mapbox\"!==r&&\"terrarium\"!==r)return _('\"'+r+'\" is not a valid encoding type. Valid types include \"mapbox\" and \"terrarium\".');this.stride=e.height;var n=this.dim=e.height-2;this.data=new Uint32Array(e.data.buffer),this.encoding=r||\"mapbox\";for(var i=0;i<n;i++)this.data[this._idx(-1,i)]=this.data[this._idx(0,i)],this.data[this._idx(n,i)]=this.data[this._idx(n-1,i)],this.data[this._idx(i,-1)]=this.data[this._idx(i,0)],this.data[this._idx(i,n)]=this.data[this._idx(i,n-1)];this.data[this._idx(-1,-1)]=this.data[this._idx(0,0)],this.data[this._idx(n,-1)]=this.data[this._idx(n-1,0)],this.data[this._idx(-1,n)]=this.data[this._idx(0,n-1)],this.data[this._idx(n,n)]=this.data[this._idx(n-1,n-1)]};au.prototype.get=function(t,e){var r=new Uint8Array(this.data.buffer),n=4*this._idx(t,e);return(\"terrarium\"===this.encoding?this._unpackTerrarium:this._unpackMapbox)(r[n],r[n+1],r[n+2])},au.prototype.getUnpackVector=function(){return\"terrarium\"===this.encoding?[256,1,1/256,32768]:[6553.6,25.6,.1,1e4]},au.prototype._idx=function(t,e){if(t<-1||t>=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},au.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},au.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},au.prototype.getPixels=function(){return new Eo({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},au.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,c=a;c<o;c++)for(var u=n;u<i;u++)this.data[this._idx(u,c)]=t.data[this._idx(u+s,c+l)]},Nn(\"DEMData\",au);var ou=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};ou.prototype.encode=function(t){return this._stringToNumber[t]},ou.prototype.decode=function(t){return this._numberToString[t]};var su=function(t,e,r,n,i){this.type=\"Feature\",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,this.id=i},lu={geometry:{configurable:!0}};lu.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},lu.geometry.set=function(t){this._geometry=t},su.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)\"_geometry\"!==e&&\"_vectorTileFeature\"!==e&&(t[e]=this[e]);return t},Object.defineProperties(su.prototype,lu);var cu=function(){this.state={},this.stateChanges={},this.deletedStates={}};cu.prototype.updateState=function(t,e,r){var n=String(e);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][n]=this.stateChanges[t][n]||{},u(this.stateChanges[t][n],r),null===this.deletedStates[t])for(var i in this.deletedStates[t]={},this.state[t])i!==n&&(this.deletedStates[t][i]=null);else if(this.deletedStates[t]&&null===this.deletedStates[t][n])for(var a in this.deletedStates[t][n]={},this.state[t][n])r[a]||(this.deletedStates[t][n][a]=null);else for(var o in r){this.deletedStates[t]&&this.deletedStates[t][n]&&null===this.deletedStates[t][n][o]&&delete this.deletedStates[t][n][o]}},cu.prototype.removeFeatureState=function(t,e,r){if(!(null===this.deletedStates[t])){var n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e){if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null}else this.deletedStates[t]=null}},cu.prototype.getState=function(t,e){var r=String(e),n=this.state[t]||{},i=this.stateChanges[t]||{},a=u({},n[r],i[r]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){var o=this.deletedStates[t][e];if(null===o)return{};for(var s in o)delete a[s]}return a},cu.prototype.initializeTileState=function(t,e){t.setFeatureState(this.state,e)},cu.prototype.coalesceChanges=function(t,e){var r={};for(var n in this.stateChanges){this.state[n]=this.state[n]||{};var i={};for(var a in this.stateChanges[n])this.state[n][a]||(this.state[n][a]={}),u(this.state[n][a],this.stateChanges[n][a]),i[a]=this.state[n][a];r[n]=i}for(var o in this.deletedStates){this.state[o]=this.state[o]||{};var s={};if(null===this.deletedStates[o])for(var l in this.state[o])s[l]={},this.state[o][l]={};else for(var c in this.deletedStates[o]){if(null===this.deletedStates[o][c])this.state[o][c]={};else for(var f=0,h=Object.keys(this.deletedStates[o][c]);f<h.length;f+=1){var p=h[f];delete this.state[o][c][p]}s[c]=this.state[o][c]}r[o]=r[o]||{},u(r[o],s)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(r).length)for(var d in t){t[d].setFeatureState(r,e)}};var uu=function(t,e){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=new zn(8192,16,0),this.grid3D=new zn(8192,16,0),this.featureIndexArray=new fa,this.promoteId=e};function fu(t,e,r,n,i){return v(t,(function(t,a){var o=e instanceof _i?e.get(a):null;return o&&o.evaluate?o.evaluate(r,n,i):o}))}function hu(t){for(var e=1/0,r=1/0,n=-1/0,i=-1/0,a=0,o=t;a<o.length;a+=1){var s=o[a];e=Math.min(e,s.x),r=Math.min(r,s.y),n=Math.max(n,s.x),i=Math.max(i,s.y)}return{minX:e,minY:r,maxX:n,maxY:i}}function pu(t,e){return e-t}uu.prototype.insert=function(t,e,r,n,i,a){var o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,i);for(var s=a?this.grid3D:this.grid,l=0;l<e.length;l++){for(var c=e[l],u=[1/0,1/0,-1/0,-1/0],f=0;f<c.length;f++){var h=c[f];u[0]=Math.min(u[0],h.x),u[1]=Math.min(u[1],h.y),u[2]=Math.max(u[2],h.x),u[3]=Math.max(u[3],h.y)}u[0]<8192&&u[1]<8192&&u[2]>=0&&u[3]>=0&&s.insert(o,u[0],u[1],u[2],u[3])}},uu.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new Ls.VectorTile(new al(this.rawTileData)).layers,this.sourceLayerCoder=new ou(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},uu.prototype.query=function(t,e,r,n){var a=this;this.loadVTLayers();for(var o=t.params||{},s=8192/t.tileSize/t.scale,l=sn(o.filter),c=t.queryGeometry,u=t.queryPadding*s,f=hu(c),h=this.grid.query(f.minX-u,f.minY-u,f.maxX+u,f.maxY+u),p=hu(t.cameraQueryGeometry),d=this.grid3D.query(p.minX-u,p.minY-u,p.maxX+u,p.maxY+u,(function(e,r,n,a){return function(t,e,r,n,a){for(var o=0,s=t;o<s.length;o+=1){var l=s[o];if(e<=l.x&&r<=l.y&&n>=l.x&&a>=l.y)return!0}var c=[new i(e,r),new i(e,a),new i(n,a),new i(n,r)];if(t.length>2)for(var u=0,f=c;u<f.length;u+=1){if(io(t,f[u]))return!0}for(var h=0;h<t.length-1;h++){if(ao(t[h],t[h+1],c))return!0}return!1}(t.cameraQueryGeometry,e-u,r-u,n+u,a+u)})),g=0,m=d;g<m.length;g+=1){var v=m[g];h.push(v)}h.sort(pu);for(var y,x={},b=function(i){var u=h[i];if(u!==y){y=u;var f=a.featureIndexArray.get(u),p=null;a.loadMatchingFeature(x,f.bucketIndex,f.sourceLayerIndex,f.featureIndex,l,o.layers,o.availableImages,e,r,n,(function(e,r,n){return p||(p=Ya(e)),r.queryIntersectsFeature(c,e,n,p,a.z,t.transform,s,t.pixelPosMatrix)}))}},_=0;_<h.length;_++)b(_);return x},uu.prototype.loadMatchingFeature=function(t,e,r,n,i,a,o,s,l,c,u){var f=this.bucketLayerIDs[e];if(!a||function(t,e){for(var r=0;r<t.length;r++)if(e.indexOf(t[r])>=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),p=this.vtLayers[h].feature(n);if(i.filter(new pi(this.tileID.overscaledZ),p))for(var d=this.getId(p,h),g=0;g<f.length;g++){var m=f[g];if(!(a&&a.indexOf(m)<0)){var v=s[m];if(v){var y={};void 0!==d&&c&&(y=c.getState(v.sourceLayer||\"_geojsonTileLayer\",d));var x=l[m];x.paint=fu(x.paint,v.paint,p,y,o),x.layout=fu(x.layout,v.layout,p,y,o);var b=!u||u(p,v,y);if(b){var _=new su(p,this.z,this.x,this.y,d);_.layer=x;var w=t[m];void 0===w&&(w=t[m]=[]),w.push({featureIndex:n,feature:_,intersectionZ:b})}}}}}},uu.prototype.lookupSymbolFeatures=function(t,e,r,n,i,a,o,s){var l={};this.loadVTLayers();for(var c=sn(i),u=0,f=t;u<f.length;u+=1){var h=f[u];this.loadMatchingFeature(l,r,n,h,c,a,o,s,e)}return l},uu.prototype.hasLayer=function(t){for(var e=0,r=this.bucketLayerIDs;e<r.length;e+=1)for(var n=0,i=r[e];n<i.length;n+=1){if(t===i[n])return!0}return!1},uu.prototype.getId=function(t,e){var r=t.id;if(this.promoteId){var n=\"string\"==typeof this.promoteId?this.promoteId:this.promoteId[e];\"boolean\"==typeof(r=t.properties[n])&&(r=Number(r))}return r},Nn(\"FeatureIndex\",uu,{omit:[\"rawTileData\",\"sourceLayerCoder\"]});var du=function(t,e){this.tileID=t,this.uid=h(),this.uses=0,this.tileSize=e,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.expiredRequestCount=0,this.state=\"loading\"};du.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<R.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},du.prototype.wasRequested=function(){return\"errored\"===this.state||\"loaded\"===this.state||\"reloading\"===this.state},du.prototype.loadVectorData=function(t,e,r){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",t){for(var n in t.featureIndex&&(this.latestFeatureIndex=t.featureIndex,t.rawTileData?(this.latestRawTileData=t.rawTileData,this.latestFeatureIndex.rawTileData=t.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=t.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=function(){var t=a[i],n=t.layerIds.map((function(t){return e.getLayer(t)})).filter(Boolean);if(0!==n.length){t.layers=n,t.stateDependentLayerIds&&(t.stateDependentLayers=t.stateDependentLayerIds.map((function(t){return n.filter((function(e){return e.id===t}))[0]})));for(var o=0,s=n;o<s.length;o+=1){var l=s[o];r[l.id]=t}}},i=0,a=t;i<a.length;i+=1)n();return r}(t.buckets,e.style),this.hasSymbolBuckets=!1,this.buckets){var i=this.buckets[n];if(i instanceof Mc){if(this.hasSymbolBuckets=!0,!r)break;i.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(var a in this.buckets){var o=this.buckets[a];if(o instanceof Mc&&o.hasRTLText){this.hasRTLText=!0,hi.isLoading()||hi.isLoaded()||\"deferred\"!==ui()||fi();break}}for(var s in this.queryPadding=0,this.buckets){var l=this.buckets[s];this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(s).queryRadius(l))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new na},du.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"},du.prototype.getBucket=function(t){return this.buckets[t.id]},du.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploadPending()&&r.upload(t)}var n=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new Vc(t,this.imageAtlas.image,n.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new Vc(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},du.prototype.prepare=function(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)},du.prototype.queryRenderedFeatures=function(t,e,r,n,i,a,o,s,l,c){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:n,cameraQueryGeometry:i,scale:a,tileSize:this.tileSize,pixelPosMatrix:c,transform:s,params:o,queryPadding:this.queryPadding*l},t,e,r):{}},du.prototype.querySourceFeatures=function(t,e){var r=this.latestFeatureIndex;if(r&&r.rawTileData){var n=r.loadVTLayers(),i=e?e.sourceLayer:\"\",a=n._geojsonTileLayer||n[i];if(a)for(var o=sn(e&&e.filter),s=this.tileID.canonical,l=s.z,c=s.x,u=s.y,f={z:l,x:c,y:u},h=0;h<a.length;h++){var p=a.feature(h);if(o.filter(new pi(this.tileID.overscaledZ),p)){var d=r.getId(p,i),g=new su(p,l,c,u,d);g.tile=f,t.push(g)}}}},du.prototype.hasData=function(){return\"loaded\"===this.state||\"reloading\"===this.state||\"expired\"===this.state},du.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},du.prototype.setExpiryData=function(t){var e=this.expirationTime;if(t.cacheControl){var r=A(t.cacheControl);r[\"max-age\"]&&(this.expirationTime=Date.now()+1e3*r[\"max-age\"])}else t.expires&&(this.expirationTime=new Date(t.expires).getTime());if(this.expirationTime){var n=Date.now(),i=!1;if(this.expirationTime>n)i=!1;else if(e)if(this.expirationTime<e)i=!0;else{var a=this.expirationTime-e;a?this.expirationTime=n+Math.max(a,3e4):i=!0}else i=!0;i?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}},du.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)},du.prototype.setFeatureState=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData&&0!==Object.keys(t).length){var r=this.latestFeatureIndex.loadVTLayers();for(var n in this.buckets)if(e.style.hasLayer(n)){var i=this.buckets[n],a=i.layers[0].sourceLayer||\"_geojsonTileLayer\",o=r[a],s=t[a];if(o&&s&&0!==Object.keys(s).length){i.update(s,o,this.imageAtlas&&this.imageAtlas.patternPositions||{});var l=e&&e.style&&e.style.getLayer(n);l&&(this.queryPadding=Math.max(this.queryPadding,l.queryRadius(i)))}}}},du.prototype.holdingForFade=function(){return void 0!==this.symbolFadeHoldUntil},du.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<R.now()},du.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},du.prototype.setHoldDuration=function(t){this.symbolFadeHoldUntil=R.now()+t},du.prototype.setDependencies=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){r[i[n]]=!0}this.dependencies[t]=r},du.prototype.hasDependency=function(t,e){for(var r=0,n=t;r<n.length;r+=1){var i=n[r],a=this.dependencies[i];if(a)for(var o=0,s=e;o<s.length;o+=1){if(a[s[o]])return!0}}return!1};var 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r},t.makeRequest=yt,t.mapObject=v,t.mercatorXfromLng=Jc,t.mercatorYfromLat=Kc,t.mercatorZfromAltitude=Qc,t.mul=go,t.multiply=po,t.mvt=Ls,t.normalize=function(t,e){var r=e[0],n=e[1],i=e[2],a=r*r+n*n+i*i;return a>0&&(a=1/Math.sqrt(a)),t[0]=e[0]*a,t[1]=e[1]*a,t[2]=e[2]*a,t},t.number=He,t.offscreenCanvasSupported=pt,t.ortho=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),c=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*c,t[15]=1,t},t.parseGlyphPBF=function(t){return new al(t).readFields(Tl,[])},t.pbf=al,t.performSymbolLayout=function(t,e,r,n,i,a,o){t.createArrays();var s=512*t.overscaling;t.tilePixelRatio=8192/s,t.compareText={},t.iconsNeedLinear=!1;var l=t.layers[0].layout,c=t.layers[0]._unevaluatedLayout._values,u={};if(\"composite\"===t.textSizeData.kind){var f=t.textSizeData,h=f.minZoom,p=f.maxZoom;u.compositeTextSizes=[c[\"text-size\"].possiblyEvaluate(new 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m=(c+1)%2;(0===c?r-i<=d:n-i<=g)&&(o.push(f),o.push(p-1),o.push(m)),(0===c?r+i>=d:n+i>=g)&&(o.push(p+1),o.push(u),o.push(m))}}return s}(this.ids,this.coords,t,e,r,this.nodeSize)};var j={minZoom:0,maxZoom:16,radius:40,extent:512,nodeSize:64,log:!1,generateId:!1,reduce:null,map:function(t){return t}},U=function(t){this.options=X(Object.create(j),t),this.trees=new Array(this.options.maxZoom+1)};function V(t,e,r,n,i){return{x:t,y:e,zoom:1/0,id:r,parentId:-1,numPoints:n,properties:i}}function q(t,e){var r=t.geometry.coordinates,n=r[0],i=r[1];return{x:Y(n),y:W(i),zoom:1/0,index:e,parentId:-1}}function H(t){return{type:\"Feature\",id:t.id,properties:G(t),geometry:{type:\"Point\",coordinates:[(n=t.x,360*(n-.5)),(e=t.y,r=(180-360*e)*Math.PI/180,360*Math.atan(Math.exp(r))/Math.PI-90)]}};var e,r,n}function G(t){var e=t.numPoints,r=e>=1e4?Math.round(e/1e3)+\"k\":e>=1e3?Math.round(e/100)/10+\"k\":e;return 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r=0;r<e.length;r+=3)t.minX=Math.min(t.minX,e[r]),t.minY=Math.min(t.minY,e[r+1]),t.maxX=Math.max(t.maxX,e[r]),t.maxY=Math.max(t.maxY,e[r+1])}function tt(t,e,r,n){if(e.geometry){var i=e.geometry.coordinates,a=e.geometry.type,o=Math.pow(r.tolerance/((1<<r.maxZoom)*r.extent),2),s=[],l=e.id;if(r.promoteId?l=e.properties[r.promoteId]:r.generateId&&(l=n||0),\"Point\"===a)et(i,s);else if(\"MultiPoint\"===a)for(var c=0;c<i.length;c++)et(i[c],s);else if(\"LineString\"===a)rt(i,s,o,!1);else if(\"MultiLineString\"===a){if(r.lineMetrics){for(c=0;c<i.length;c++)s=[],rt(i[c],s,o,!1),t.push(Q(l,\"LineString\",s,e.properties));return}nt(i,s,o,!1)}else if(\"Polygon\"===a)nt(i,s,o,!0);else{if(\"MultiPolygon\"!==a){if(\"GeometryCollection\"===a){for(c=0;c<e.geometry.geometries.length;c++)tt(t,{id:l,geometry:e.geometry.geometries[c],properties:e.properties},r,n);return}throw new Error(\"Input data is not a valid GeoJSON object.\")}for(c=0;c<i.length;c++){var 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r=[],n=0;n<t.length;n++){var i,a=t[n],o=a.type;if(\"Point\"===o||\"MultiPoint\"===o||\"LineString\"===o)i=gt(a.geometry,e);else if(\"MultiLineString\"===o||\"Polygon\"===o){i=[];for(var s=0;s<a.geometry.length;s++)i.push(gt(a.geometry[s],e))}else if(\"MultiPolygon\"===o)for(i=[],s=0;s<a.geometry.length;s++){for(var l=[],c=0;c<a.geometry[s].length;c++)l.push(gt(a.geometry[s][c],e));i.push(l)}r.push(Q(a.id,o,i,a.tags))}return r}function gt(t,e){var r=[];r.size=t.size,void 0!==t.start&&(r.start=t.start,r.end=t.end);for(var n=0;n<t.length;n+=3)r.push(t[n]+e,t[n+1],t[n+2]);return r}function mt(t,e){if(t.transformed)return t;var r,n,i,a=1<<t.z,o=t.x,s=t.y;for(r=0;r<t.features.length;r++){var l=t.features[r],c=l.geometry,u=l.type;if(l.geometry=[],1===u)for(n=0;n<c.length;n+=2)l.geometry.push(vt(c[n],c[n+1],e,a,o,s));else for(n=0;n<c.length;n++){var f=[];for(i=0;i<c[n].length;i+=2)f.push(vt(c[n][i],c[n][i+1],e,a,o,s));l.geometry.push(f)}}return t.transformed=!0,t}function 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u={},e.tags)u[f]=e.tags[f];u.mapbox_clip_start=i.start/i.size,u.mapbox_clip_end=i.end/i.size}var h={geometry:o,type:\"Polygon\"===a||\"MultiPolygon\"===a?3:\"LineString\"===a||\"MultiLineString\"===a?2:1,tags:u};null!==e.id&&(h.id=e.id),t.features.push(h)}}function bt(t,e,r,n,i,a){var o=n*n;if(n>0&&e.size<(i?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;l<e.length;l+=3)(0===n||e[l+2]>o)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;i&&function(t,e){for(var r=0,n=0,i=t.length,a=i-2;n<i;a=n,n+=2)r+=(t[n]-t[a])*(t[n+1]+t[a+1]);if(r>0===e)for(n=0,i=t.length;n<i/2;n+=2){var o=t[n],s=t[n+1];t[n]=t[i-2-n],t[n+1]=t[i-1-n],t[i-2-n]=o,t[i-1-n]=s}}(s,a),t.push(s)}}function _t(t,e){var r=(e=this.options=function(t,e){for(var r in e)t[r]=e[r];return t}(Object.create(this.options),e)).debug;if(r&&console.time(\"preprocess data\"),e.maxZoom<0||e.maxZoom>24)throw new Error(\"maxZoom should be in the 0-24 range\");if(e.promoteId&&e.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n<t.features.length;n++)tt(r,t.features[n],e,n);else\"Feature\"===t.type?tt(r,t,e):tt(r,{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",e.indexMaxZoom,e.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,i=ot(t,1,-1-r,r,0,-1,2,e),a=ot(t,1,1-r,2+r,0,-1,2,e);return(i||a)&&(n=ot(t,1,-r,1+r,0,-1,2,e)||[],i&&(n=dt(i,1).concat(n)),a&&(n=n.concat(dt(a,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}function wt(t,e,r){return 32*((1<<t)*r+e)+t}function Tt(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var i=new m(n.features),a=_(i);0===a.byteOffset&&a.byteLength===a.buffer.byteLength||(a=new Uint8Array(a)),e(null,{vectorTile:i,rawData:a.buffer})}U.prototype.load=function(t){var e=this.options,r=e.log,n=e.minZoom,i=e.maxZoom,a=e.nodeSize;r&&console.time(\"total time\");var o=\"prepare \"+t.length+\" points\";r&&console.time(o),this.points=t;for(var s=[],l=0;l<t.length;l++)t[l].geometry&&s.push(q(t[l],l));this.trees[i+1]=new N(s,Z,J,a,Float32Array),r&&console.timeEnd(o);for(var c=i;c>=n;c--){var u=+Date.now();s=this._cluster(s,c),this.trees[c]=new N(s,Z,J,a,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",c,s.length,+Date.now()-u)}return r&&console.timeEnd(\"total time\"),this},U.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],c=[],u=0,f=l.range(Y(r),W(a),Y(i),W(n));u<f.length;u+=1){var h=f[u],p=l.points[h];c.push(p.numPoints?H(p):this.points[p.index])}return c},U.prototype.getChildren=function(t){var e=this._getOriginId(t),r=this._getOriginZoom(t),n=\"No cluster with the specified id.\",i=this.trees[r];if(!i)throw new Error(n);var a=i.points[e];if(!a)throw new Error(n);for(var o=this.options.radius/(this.options.extent*Math.pow(2,r-1)),s=[],l=0,c=i.within(a.x,a.y,o);l<c.length;l+=1){var u=c[l],f=i.points[u];f.parentId===t&&s.push(f.numPoints?H(f):this.points[f.index])}if(0===s.length)throw new Error(n);return s},U.prototype.getLeaves=function(t,e,r){e=e||10,r=r||0;var n=[];return this._appendLeaves(n,t,e,r,0),n},U.prototype.getTile=function(t,e,r){var n=this.trees[this._limitZoom(t)],i=Math.pow(2,t),a=this.options,o=a.extent,s=a.radius/o,l=(r-s)/i,c=(r+1+s)/i,u={features:[]};return this._addTileFeatures(n.range((e-s)/i,l,(e+1+s)/i,c),n.points,e,r,i,u),0===e&&this._addTileFeatures(n.range(1-s/i,l,1,c),n.points,i,r,i,u),e===i-1&&this._addTileFeatures(n.range(0,l,s/i,c),n.points,-1,r,i,u),u.features.length?u:null},U.prototype.getClusterExpansionZoom=function(t){for(var e=this._getOriginZoom(t)-1;e<=this.options.maxZoom;){var r=this.getChildren(t);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},U.prototype._appendLeaves=function(t,e,r,n,i){for(var a=0,o=this.getChildren(e);a<o.length;a+=1){var s=o[a],l=s.properties;if(l&&l.cluster?i+l.point_count<=n?i+=l.point_count:i=this._appendLeaves(t,l.cluster_id,r,n,i):i<n?i++:t.push(s),t.length===r)break}return i},U.prototype._addTileFeatures=function(t,e,r,n,i,a){for(var o=0,s=t;o<s.length;o+=1){var l=e[s[o]],c=l.numPoints,u={type:1,geometry:[[Math.round(this.options.extent*(l.x*i-r)),Math.round(this.options.extent*(l.y*i-n))]],tags:c?G(l):this.points[l.index].properties},f=void 0;c?f=l.id:this.options.generateId?f=l.index:this.points[l.index].id&&(f=this.points[l.index].id),void 0!==f&&(u.id=f),a.features.push(u)}},U.prototype._limitZoom=function(t){return Math.max(this.options.minZoom,Math.min(t,this.options.maxZoom+1))},U.prototype._cluster=function(t,e){for(var r=[],n=this.options,i=n.radius,a=n.extent,o=n.reduce,s=i/(a*Math.pow(2,e)),l=0;l<t.length;l++){var c=t[l];if(!(c.zoom<=e)){c.zoom=e;for(var u=this.trees[e+1],f=u.within(c.x,c.y,s),h=c.numPoints||1,p=c.x*h,d=c.y*h,g=o&&h>1?this._map(c,!0):null,m=(l<<5)+(e+1)+this.points.length,v=0,y=f;v<y.length;v+=1){var x=y[v],b=u.points[x];if(!(b.zoom<=e)){b.zoom=e;var _=b.numPoints||1;p+=b.x*_,d+=b.y*_,h+=_,b.parentId=m,o&&(g||(g=this._map(c,!0)),o(g,this._map(b)))}}1===h?r.push(c):(c.parentId=m,r.push(V(p/h,d/h,m,h,g)))}}return r},U.prototype._getOriginId=function(t){return t-this.points.length>>5},U.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},U.prototype._map=function(t,e){if(t.numPoints)return e?X({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?X({},n):n},_t.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},_t.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,c=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var u=1<<e,f=wt(e,r,n),h=this.tiles[f];if(!h&&(c>1&&console.time(\"creation\"),h=this.tiles[f]=yt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),c)){c>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<<i-e;if(r!==Math.floor(a/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||h.numPoints<=l.indexMaxPoints)continue;if(h.source=null,0!==t.length){c>1&&console.time(\"clipping\");var g,m,v,y,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;g=m=v=y=null,x=ot(t,u,r-_,r+T,0,h.minX,h.maxX,l),b=ot(t,u,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(g=ot(x,u,n-_,n+T,1,h.minY,h.maxY,l),m=ot(x,u,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(v=ot(b,u,n-_,n+T,1,h.minY,h.maxY,l),y=ot(b,u,n+w,n+k,1,h.minY,h.maxY,l),b=null),c>1&&console.timeEnd(\"clipping\"),s.push(g||[],e+1,2*r,2*n),s.push(m||[],e+1,2*r,2*n+1),s.push(v||[],e+1,2*r+1,2*n),s.push(y||[],e+1,2*r+1,2*n+1)}}},_t.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<<t,s=wt(t,e=(e%o+o)%o,r);if(this.tiles[s])return mt(this.tiles[s],i);a>1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,c=t,u=e,f=r;!l&&c>0;)c--,u=Math.floor(u/2),f=Math.floor(f/2),l=this.tiles[wt(c,u,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",c,u,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,c,u,f,t,e,r),a>1&&console.timeEnd(\"drilling down\"),this.tiles[s]?mt(this.tiles[s],i):null):null};var kt=function(e){function r(t,r,n,i){e.call(this,t,r,n,Tt),i&&(this.loadGeoJSON=i)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&\"Idle\"!==this._state?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var i=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(a,o){if(a||!o)return r(a);if(\"object\"!=typeof o)return r(new Error(\"Input data given to '\"+n.source+\"' is not a valid GeoJSON object.\"));f(o,!0);try{e._geoJSONIndex=n.cluster?new U(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var i={},a={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),c=0,u=l;c<u.length;c+=1){var f=u[c],h=n[f],p=h[0],d=h[1],g=t.createExpression(d),m=t.createExpression(\"string\"==typeof p?[p,[\"accumulated\"],[\"get\",f]]:p);i[f]=g.value,a[f]=m.value}return r.map=function(t){s.properties=t;for(var e={},r=0,n=l;r<n.length;r+=1){var a=n[r];e[a]=i[a].evaluate(o,s)}return e},r.reduce=function(t,e){s.properties=e;for(var r=0,n=l;r<n.length;r+=1){var i=n[r];o.accumulated=t[i],t[i]=a[i].evaluate(o,s)}},r}(n)).load(o.features):function(t,e){return new _t(t,e)}(o,n.geojsonVtOptions)}catch(a){return r(a)}e.loaded={};var s={};if(i){var l=i.finish();l&&(s.resourceTiming={},s.resourceTiming[n.source]=JSON.parse(JSON.stringify(l)))}r(null,s)}))}},r.prototype.coalesce=function(){\"Coalescing\"===this._state?this._state=\"Idle\":\"NeedsLoadData\"===this._state&&(this._state=\"Coalescing\",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded,i=t.uid;return n&&n[i]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if(\"string\"!=typeof e.data)return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON 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t.Point(r.clientX-n.left-e.clientLeft,r.clientY-n.top-e.clientTop)},r.touchPos=function(e,r){for(var n=e.getBoundingClientRect(),i=[],a=0;a<r.length;a++)i.push(new t.Point(r[a].clientX-n.left-e.clientLeft,r[a].clientY-n.top-e.clientTop));return i},r.mouseButton=function(e){return void 0!==t.window.InstallTrigger&&2===e.button&&e.ctrlKey&&t.window.navigator.platform.toUpperCase().indexOf(\"MAC\")>=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var h=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e<r.length;e+=1){var n=r[e],i=n.ids,a=n.callback;this._notify(i,a)}this.requestors=[]}},r.prototype.getImage=function(t){return this.images[t]},r.prototype.addImage=function(t,e){this._validate(t,e)&&(this.images[t]=e)},r.prototype._validate=function(e,r){var n=!0;return this._validateStretch(r.stretchX,r.data&&r.data.width)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchX\" value'))),n=!1),this._validateStretch(r.stretchY,r.data&&r.data.height)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchY\" value'))),n=!1),this._validateContent(r.content,r)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"content\" value'))),n=!1),n},r.prototype._validateStretch=function(t,e){if(!t)return!0;for(var r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];if(a[0]<r||a[1]<a[0]||e<a[1])return!1;r=a[1]}return!0},r.prototype._validateContent=function(t,e){return!t||4===t.length&&(!(t[0]<0||e.data.width<t[0])&&(!(t[1]<0||e.data.height<t[1])&&(!(t[2]<0||e.data.width<t[2])&&(!(t[3]<0||e.data.height<t[3])&&(!(t[2]<t[0])&&!(t[3]<t[1]))))))},r.prototype.updateImage=function(t,e){var r=this.images[t];e.version=r.version+1,this.images[t]=e,this.updatedImages[t]=!0},r.prototype.removeImage=function(t){var e=this.images[t];delete this.images[t],delete this.patterns[t],e.userImage&&e.userImage.onRemove&&e.userImage.onRemove()},r.prototype.listImages=function(){return Object.keys(this.images)},r.prototype.getImages=function(t,e){var r=!0;if(!this.isLoaded())for(var n=0,i=t;n<i.length;n+=1){var a=i[n];this.images[a]||(r=!1)}this.isLoaded()||r?this._notify(t,e):this.requestors.push({ids:t,callback:e})},r.prototype._notify=function(e,r){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i];this.images[o]||this.fire(new t.Event(\"styleimagemissing\",{id:o}));var s=this.images[o];s?n[o]={data:s.data.clone(),pixelRatio:s.pixelRatio,sdf:s.sdf,version:s.version,stretchX:s.stretchX,stretchY:s.stretchY,content:s.content,hasRenderCallback:Boolean(s.userImage&&s.userImage.render)}:t.warnOnce('Image \"'+o+'\" could not be loaded. Please make sure you have added the image with map.addImage() or a \"sprite\" property in your style. You can provide missing images by listening for the \"styleimagemissing\" map event.')}r(null,n)},r.prototype.getPixelSize=function(){var t=this.atlasImage;return{width:t.width,height:t.height}},r.prototype.getPattern=function(e){var r=this.patterns[e],n=this.getImage(e);if(!n)return null;if(r&&r.position.version===n.version)return r.position;if(r)r.position.version=n.version;else{var i={w:n.data.width+2,h:n.data.height+2,x:0,y:0},a=new t.ImagePosition(i,n);this.patterns[e]={bin:i,position:a}}return this._updatePatternAtlas(),this.patterns[e].position},r.prototype.bind=function(e){var r=e.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new t.Texture(e,this.atlasImage,r.RGBA),this.atlasTexture.bind(r.LINEAR,r.CLAMP_TO_EDGE)},r.prototype._updatePatternAtlas=function(){var e=[];for(var r in this.patterns)e.push(this.patterns[r].bin);var n=t.potpack(e),i=n.w,a=n.h,o=this.atlasImage;for(var s in o.resize({width:i||1,height:a||1}),this.patterns){var l=this.patterns[s].bin,c=l.x+1,u=l.y+1,f=this.images[s].data,h=f.width,p=f.height;t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u},{width:h,height:p}),t.RGBAImage.copy(f,o,{x:0,y:p-1},{x:c,y:u-1},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u+p},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:h-1,y:0},{x:c-1,y:u},{width:1,height:p}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c+h,y:u},{width:1,height:p})}this.dirty=!0},r.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},r.prototype.dispatchRenderCallbacks=function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!this.callbackDispatchedThisFrame[n]){this.callbackDispatchedThisFrame[n]=!0;var i=this.images[n];f(i)&&this.updateImage(n,i)}}},r}(t.Evented);var p=m,d=m,g=1e20;function m(t,e,r,n,i,a){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=i||\"sans-serif\",this.fontWeight=a||\"normal\",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement(\"canvas\"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext(\"2d\"),this.ctx.font=this.fontWeight+\" \"+this.fontSize+\"px \"+this.fontFamily,this.ctx.textBaseline=\"middle\",this.ctx.fillStyle=\"black\",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf(\"Gecko/\")>=0?1.2:1))}function v(t,e,r,n,i,a,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(y(n,i,a,o,r),l=0;l<r;l++)t[l*e+s]=i[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(y(n,i,a,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(i[s])}}function y(t,e,r,n,i){r[0]=0,n[0]=-g,n[1]=+g;for(var a=1,o=0;a<i;a++){for(var s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);s<=n[o];)o--,s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);r[++o]=a,n[o]=s,n[o+1]=+g}for(a=0,o=0;a<i;a++){for(;n[o+1]<a;)o++;e[a]=(a-r[o])*(a-r[o])+t[r[o]]}}m.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var i=e.data[4*n+3]/255;this.gridOuter[n]=1===i?0:0===i?g:Math.pow(Math.max(0,.5-i),2),this.gridInner[n]=1===i?g:0===i?0:Math.pow(Math.max(0,i-.5),2)}for(v(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),v(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++){var a=this.gridOuter[n]-this.gridInner[n];r[n]=Math.max(0,Math.min(255,Math.round(255-255*(a/this.radius+this.cutoff))))}return r},p.default=d;var x=function(t,e){this.requestManager=t,this.localIdeographFontFamily=e,this.entries={}};x.prototype.setURL=function(t){this.url=t},x.prototype.getGlyphs=function(e,r){var n=this,i=[];for(var a in e)for(var o=0,s=e[a];o<s.length;o+=1){var l=s[o];i.push({stack:a,id:l})}t.asyncAll(i,(function(t,e){var r=t.stack,i=t.id,a=n.entries[r];a||(a=n.entries[r]={glyphs:{},requests:{},ranges:{}});var o=a.glyphs[i];if(void 0===o){if(o=n._tinySDF(a,r,i))return a.glyphs[i]=o,void e(null,{stack:r,id:i,glyph:o});var s=Math.floor(i/256);if(256*s>65535)e(new Error(\"glyphs > 65535 not supported\"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i<o.length;i+=1){(0,o[i])(t,e)}delete a.requests[s]}))),l.push((function(t,n){t?e(t):n&&e(null,{stack:r,id:i,glyph:n[i]||null})}))}}else e(null,{stack:r,id:i,glyph:o})}),(function(t,e){if(t)r(t);else if(e){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.stack,l=o.id,c=o.glyph;(n[s]||(n[s]={}))[l]=c&&{id:c.id,bitmap:c.bitmap.clone(),metrics:c.metrics}}r(null,n)}}))},x.prototype._doesCharSupportLocalGlyph=function(e){return!!this.localIdeographFontFamily&&(t.isChar[\"CJK Unified Ideographs\"](e)||t.isChar[\"Hangul Syllables\"](e)||t.isChar.Hiragana(e)||t.isChar.Katakana(e))},x.prototype._tinySDF=function(e,r,n){var i=this.localIdeographFontFamily;if(i&&this._doesCharSupportLocalGlyph(n)){var a=e.tinySDF;if(!a){var o=\"400\";/bold/i.test(r)?o=\"900\":/medium/i.test(r)?o=\"500\":/light/i.test(r)&&(o=\"200\"),a=e.tinySDF=new x.TinySDF(24,3,8,.25,i,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},a.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},x.loadGlyphRange=function(e,r,n,i,a){var o=256*r,s=o+255,l=i.transformRequest(i.normalizeGlyphsURL(n).replace(\"{fontstack}\",e).replace(\"{range}\",o+\"-\"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,(function(e,r){if(e)a(e);else if(r){for(var n={},i=0,o=t.parseGlyphPBF(r);i<o.length;i+=1){var s=o[i];n[s.id]=s}a(null,n)}}))},x.TinySDF=p;var b=function(){this.specification=t.styleSpec.light.position};b.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},b.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var _=new t.Properties({anchor:new t.DataConstantProperty(t.styleSpec.light.anchor),position:new b,color:new t.DataConstantProperty(t.styleSpec.light.color),intensity:new t.DataConstantProperty(t.styleSpec.light.intensity)}),w=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(_),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e,r){if(void 0===r&&(r={}),!this._validate(t.validateLight,e,r))for(var n in e){var i=e[n];t.endsWith(n,\"-transition\")?this._transitionable.setTransition(n.slice(0,-\"-transition\".length),i):this._transitionable.setValue(n,i)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r,n){return(!n||!1!==n.validate)&&t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.styleSpec})))},r}(t.Evented),T=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}};T.prototype.getDash=function(t,e){var r=t.join(\",\")+String(e);return this.dashEntry[r]||(this.dashEntry[r]=this.addDash(t,e)),this.dashEntry[r]},T.prototype.getDashRanges=function(t,e,r){var n=[],i=t.length%2==1?-t[t.length-1]*r:0,a=t[0]*r,o=!0;n.push({left:i,right:a,isDash:o,zeroLength:0===t[0]});for(var s=t[0],l=1;l<t.length;l++){o=!o;var c=t[l];i=s*r,a=(s+=c)*r,n.push({left:i,right:a,isDash:o,zeroLength:0===c})}return n},T.prototype.addRoundDash=function(t,e,r){for(var n=e/2,i=-r;i<=r;i++)for(var a=this.nextRow+r+i,o=this.width*a,s=0,l=t[s],c=0;c<this.width;c++){c/l.right>1&&(l=t[++s]);var u=Math.abs(c-l.left),f=Math.abs(c-l.right),h=Math.min(u,f),p=void 0,d=i/r*(n+1);if(l.isDash){var g=n-Math.abs(d);p=Math.sqrt(h*h+g*g)}else p=n-Math.sqrt(h*h+d*d);this.data[o+c]=Math.max(0,Math.min(255,p+128))}},T.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],c=0;c<this.width;c++){c/l.right>1&&(l=t[++s]);var u=Math.abs(c-l.left),f=Math.abs(c-l.right),h=Math.min(u,f),p=l.isDash?h:-h;this.data[o+c]=Math.max(0,Math.min(255,p+128))}},T.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o<e.length;o++)a+=e[o];if(0!==a){var s=this.width/a,l=this.getDashRanges(e,this.width,s);r?this.addRoundDash(l,s,n):this.addRegularDash(l)}var c={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:a};return this.nextRow+=i,this.dirty=!0,c},T.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.ALPHA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.ALPHA,this.width,this.height,0,e.ALPHA,e.UNSIGNED_BYTE,this.data))};var k=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var i=this.workerPool.acquire(this.id),a=0;a<i.length;a++){var o=i[a],s=new e.Actor(o,n,this.id);s.name=\"Worker \"+a,this.actors.push(s)}};function A(e,r,n){var i=function(i,a){if(i)return n(i);if(a){var o=t.pick(t.extend(a,e),[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"mapbox_logo\",\"bounds\",\"scheme\",\"tileSize\",\"encoding\"]);a.vector_layers&&(o.vectorLayers=a.vector_layers,o.vectorLayerIds=o.vectorLayers.map((function(t){return t.id}))),o.tiles=r.canonicalizeTileset(o,e.url),n(null,o)}};return e.url?t.getJSON(r.transformRequest(r.normalizeSourceURL(e.url),t.ResourceType.Source),i):t.browser.frame((function(){return i(null,e)}))}k.prototype.broadcast=function(e,r,n){n=n||function(){},t.asyncAll(this.actors,(function(t,n){t.send(e,r,n)}),n)},k.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},k.prototype.remove=function(){this.actors.forEach((function(t){t.remove()})),this.actors=[],this.workerPool.release(this.id)},k.Actor=t.Actor;var M=function(e,r,n){this.bounds=t.LngLatBounds.convert(this.validateBounds(e)),this.minzoom=r||0,this.maxzoom=n||24};M.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},M.prototype.contains=function(e){var r=Math.pow(2,e.z),n=Math.floor(t.mercatorXfromLng(this.bounds.getWest())*r),i=Math.floor(t.mercatorYfromLat(this.bounds.getNorth())*r),a=Math.ceil(t.mercatorXfromLng(this.bounds.getEast())*r),o=Math.ceil(t.mercatorYfromLat(this.bounds.getSouth())*r);return e.x>=n&&e.x<a&&e.y>=i&&e.y<o};var S=function(e){function r(r,n,i,a){if(e.call(this),this.id=r,this.dispatcher=i,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\",\"promoteId\"])),this._options=t.extend({type:\"vector\"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(a)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=A(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new M(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles,e.map._requestManager._customAccessToken),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken,e.map._requestManager._customAccessToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme)),i={request:this.map._requestManager.transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};function a(n,i){return delete e.request,e.aborted?r(null):n&&404!==n.status?r(n):(i&&i.resourceTiming&&(e.resourceTiming=i.resourceTiming),this.map._refreshExpiredTiles&&i&&e.setExpiryData(i),e.loadVectorData(i,this.map.painter),t.cacheEntryPossiblyAdded(this.dispatcher),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}i.request.collectResourceTiming=this._collectResourceTiming,e.actor&&\"expired\"!==e.state?\"loading\"===e.state?e.reloadCallback=r:e.request=e.actor.send(\"reloadTile\",i,a.bind(this)):(e.actor=this.dispatcher.getActor(),e.request=e.actor.send(\"loadTile\",i,a.bind(this)))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.actor&&t.actor.send(\"abortTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.unloadTile=function(t){t.unloadVectorData(),t.actor&&t.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),E=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.dispatcher=i,this.setEventedParent(a),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=t.extend({type:\"raster\"},n),t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"]))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=A(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new M(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,i=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(i,t.ResourceType.Tile),(function(i,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(i)e.state=\"errored\",r(i);else if(a){n.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=n.map.painter.context,s=o.gl;e.texture=n.map.painter.getTileTexture(a.width),e.texture?e.texture.update(a,{useMipmap:!0}):(e.texture=new t.Texture(o,a,s.RGBA,{useMipmap:!0}),e.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.extTextureFilterAnisotropic&&s.texParameterf(s.TEXTURE_2D,o.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,o.extTextureFilterAnisotropicMax)),e.state=\"loaded\",t.cacheEntryPossiblyAdded(n.dispatcher),r(null)}}))},r.prototype.abortTile=function(t,e){t.request&&(t.request.cancel(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),L=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),this.type=\"raster-dem\",this.maxzoom=22,this._options=t.extend({type:\"raster-dem\"},n),this.encoding=n.encoding||\"mapbox\"}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.serialize=function(){return{type:\"raster-dem\",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);function i(t,n){t&&(e.state=\"errored\",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state=\"loaded\",r(null))}e.request=t.getImage(this.map._requestManager.transformRequest(n,t.ResourceType.Tile),function(n,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(n)e.state=\"errored\",r(n);else if(a){this.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=t.window.ImageBitmap&&a instanceof t.window.ImageBitmap&&t.offscreenCanvasSupported()?a:t.browser.getImageData(a,1),s={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:o,encoding:this.encoding};e.actor&&\"expired\"!==e.state||(e.actor=this.dispatcher.getActor(),e.actor.send(\"loadDEMTile\",s,i.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),i=(r.x-1+n)%n,a=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state=\"unloaded\",t.actor&&t.actor.send(\"removeDEMTile\",{uid:t.uid,source:this.id})},r}(E),C=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=i.getActor(),this.setEventedParent(a),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type),n.attribution&&(this.attribution=n.attribution),this.promoteId=n.promoteId;var o=t.EXTENT/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.EXTENT,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1,generateId:n.generateId||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,extent:t.EXTENT,radius:(n.clusterRadius||50)*o,log:!1,generateId:n.generateId||!1},clusterProperties:n.clusterProperties},n.workerOptions)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:\"source\",sourceDataType:\"metadata\"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;\"string\"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+\".loadData\",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor;var a={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};e.request=this.actor.send(i,a,(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,\"reloadTile\"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),P=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),I=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;o<s.length;o+=1){var l=s[o];r=Math.min(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.x),a=Math.max(a,l.y)}var c=i-r,u=a-n,f=Math.max(c,u),h=Math.max(0,Math.floor(-Math.log(f)/Math.LN2)),p=Math.pow(2,h);return new t.CanonicalTileID(h,Math.floor((r+i)/2*p),Math.floor((n+a)/2*p))}(n),this.minzoom=this.maxzoom=this.tileID.z;var i=n.map((function(t){return r.tileID.getTilePoint(t)._round()}));return this._boundsArray=new t.StructArrayLayout4i8,this._boundsArray.emplaceBack(i[0].x,i[0].y,0,0),this._boundsArray.emplaceBack(i[1].x,i[1].y,t.EXTENT,0),this._boundsArray.emplaceBack(i[3].x,i[3].y,0,t.EXTENT),this._boundsArray.emplaceBack(i[2].x,i[2].y,t.EXTENT,t.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new t.Texture(e,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state=\"errored\",e(null))},r.prototype.serialize=function(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented);var O=function(e){function r(t,r,n,i){e.call(this,t,r,n,i),this.roundZoom=!0,this.type=\"video\",this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1;var r=this.options;this.urls=[];for(var n=0,i=r.urls;n<i.length;n+=1){var a=i[n];this.urls.push(this.map._requestManager.transformRequest(a,t.ResourceType.Source).url)}t.getVideo(this.urls,(function(r,n){e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener(\"playing\",(function(){e.map.triggerRepaint()})),e.map&&e.video.play(),e._finishLoading())}))},r.prototype.pause=function(){this.video&&this.video.pause()},r.prototype.play=function(){this.video&&this.video.play()},r.prototype.seek=function(e){if(this.video){var r=this.video.seekable;e<r.start(0)||e>r.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(I),z=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return\"number\"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var 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e=this.gl;e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0),this.current=t,this.dirty=!1}},e}(_t),Tt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){if(t!==this.current||this.dirty){this.context.bindFramebuffer.set(this.parent);var e=this.gl;e.framebufferRenderbuffer(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(_t),kt=function(t,e,r,n){this.context=t,this.width=e,this.height=r;var i=t.gl,a=this.framebuffer=i.createFramebuffer();this.colorAttachment=new wt(t,a),n&&(this.depthAttachment=new Tt(t,a))};kt.prototype.destroy=function(){var t=this.context.gl,e=this.colorAttachment.get();if(e&&t.deleteTexture(e),this.depthAttachment){var r=this.depthAttachment.get();r&&t.deleteRenderbuffer(r)}t.deleteFramebuffer(this.framebuffer)};var At=function(t,e,r){this.func=t,this.mask=e,this.range=r};At.ReadOnly=!1,At.ReadWrite=!0,At.disabled=new At(519,At.ReadOnly,[0,1]);var Mt=function(t,e,r,n,i,a){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=i,this.pass=a};Mt.disabled=new Mt({func:519,mask:0},0,0,7680,7680,7680);var St=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};St.disabled=new St(St.Replace=[1,0],t.Color.transparent,[!1,!1,!1,!1]),St.unblended=new St(St.Replace,t.Color.transparent,[!0,!0,!0,!0]),St.alphaBlended=new St([1,771],t.Color.transparent,[!0,!0,!0,!0]);var Et=function(t,e,r){this.enable=t,this.mode=e,this.frontFace=r};Et.disabled=new Et(!1,1029,2305),Et.backCCW=new Et(!0,1029,2305);var Lt=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension(\"OES_vertex_array_object\"),this.clearColor=new H(this),this.clearDepth=new G(this),this.clearStencil=new Y(this),this.colorMask=new W(this),this.depthMask=new X(this),this.stencilMask=new Z(this),this.stencilFunc=new J(this),this.stencilOp=new K(this),this.stencilTest=new Q(this),this.depthRange=new $(this),this.depthTest=new tt(this),this.depthFunc=new et(this),this.blend=new rt(this),this.blendFunc=new nt(this),this.blendColor=new it(this),this.blendEquation=new at(this),this.cullFace=new ot(this),this.cullFaceSide=new st(this),this.frontFace=new lt(this),this.program=new ct(this),this.activeTexture=new ut(this),this.viewport=new ft(this),this.bindFramebuffer=new ht(this),this.bindRenderbuffer=new pt(this),this.bindTexture=new dt(this),this.bindVertexBuffer=new gt(this),this.bindElementBuffer=new mt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new vt(this),this.pixelStoreUnpack=new yt(this),this.pixelStoreUnpackPremultiplyAlpha=new xt(this),this.pixelStoreUnpackFlipY=new bt(this),this.extTextureFilterAnisotropic=t.getExtension(\"EXT_texture_filter_anisotropic\")||t.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||t.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension(\"OES_texture_half_float\"),this.extTextureHalfFloat&&(t.getExtension(\"OES_texture_half_float_linear\"),this.extRenderToTextureHalfFloat=t.getExtension(\"EXT_color_buffer_half_float\")),this.extTimerQuery=t.getExtension(\"EXT_disjoint_timer_query\")};Lt.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Lt.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Lt.prototype.createIndexBuffer=function(t,e){return new j(this,t,e)},Lt.prototype.createVertexBuffer=function(t,e,r){return new V(this,t,e,r)},Lt.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,i=n.createRenderbuffer();return this.bindRenderbuffer.set(i),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),i},Lt.prototype.createFramebuffer=function(t,e,r){return new kt(this,t,e,r)},Lt.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,i=0;e&&(i|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(i|=n.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(i)},Lt.prototype.setCullFace=function(t){!1===t.enable?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(t.mode),this.frontFace.set(t.frontFace))},Lt.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Lt.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Lt.prototype.setColorMode=function(e){t.deepEqual(e.blendFunction,St.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)},Lt.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var Ct=function(e){function r(r,n,i){var a=this;e.call(this),this.id=r,this.dispatcher=i,this.on(\"data\",(function(t){\"source\"===t.dataType&&\"metadata\"===t.sourceDataType&&(a._sourceLoaded=!0),a._sourceLoaded&&!a._paused&&\"source\"===t.dataType&&\"content\"===t.sourceDataType&&(a.reload(),a.transform&&a.update(a.transform))})),this.on(\"error\",(function(){a._sourceErrored=!0})),this._source=function(e,r,n,i){var a=new D[r.type](e,r,n,i);if(a.id!==e)throw new Error(\"Expected Source id to be \"+e+\" instead of \"+a.id);return t.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],a),a}(r,n,i,this),this._tiles={},this._cache=new N(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new t.SourceFeatureState}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;if(!this._source.loaded())return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,(function(){}))},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,(function(){}))},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null),this._tiles){var r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}},r.prototype.getIds=function(){return t.values(this._tiles).map((function(t){return t.tileID})).sort(Pt).map((function(t){return t.key}))},r.prototype.getRenderableIds=function(e){var r=this,n=[];for(var i in this._tiles)this._isIdRenderable(i,e)&&n.push(this._tiles[i]);return e?n.sort((function(e,n){var i=e.tileID,a=n.tileID,o=new t.Point(i.canonical.x,i.canonical.y)._rotate(r.transform.angle),s=new t.Point(a.canonical.x,a.canonical.y)._rotate(r.transform.angle);return i.overscaledZ-a.overscaledZ||s.y-o.y||s.x-o.x})).map((function(t){return t.tileID.key})):n.map((function(t){return t.tileID})).sort(Pt).map((function(t){return t.key}))},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)\"errored\"!==this._tiles[t].state&&this._reloadTile(t,\"reloading\")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&(\"loading\"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,i){if(i)return e.state=\"errored\",void(404!==i.status?this._source.fire(new t.ErrorEvent(i,{tile:e})):this.update(this.transform));e.timeAdded=t.browser.now(),\"expired\"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),\"raster-dem\"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._state.initializeTileState(e,this.map?this.map.painter:null),this._source.fire(new t.Event(\"data\",{dataType:\"source\",tile:e,coord:e.tileID}))},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var i=this.getTileByID(n);a(t,i),a(i,t)}}function a(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,i=Math.pow(2,t.tileID.canonical.z),a=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(It(this._source.type)){for(var c={},u={},f=0,h=Object.keys(l);f<h.length;f+=1){var p=h[f],d=l[p],g=this._tiles[p];if(g&&!(g.fadeEndTime&&g.fadeEndTime<=t.browser.now())){var m=this.findLoadedParent(d,o);m&&(this._addTile(m.tileID),c[m.tileID.key]=m.tileID),u[p]=d}}for(var v in this._retainLoadedChildren(u,a,s,l),c)l[v]||(this._coveredTiles[v]=!0,l[v]=c[v])}for(var y in l)this._tiles[y].clearFadeHold();for(var x=0,b=t.keysDifference(this._tiles,l);x<b.length;x+=1){var _=b[x],w=this._tiles[_];w.hasSymbolBuckets&&!w.holdingForFade()?w.setHoldDuration(this.map._fadeDuration):w.hasSymbolBuckets&&!w.symbolFadeFinished()||this._removeTile(_)}this._updateLoadedParentTileCache()}},r.prototype.releaseSymbolFadeTiles=function(){for(var t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)},r.prototype._updateRetainedTiles=function(t,e){for(var n={},i={},a=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s={},l=0,c=t;l<c.length;l+=1){var u=c[l],f=this._addTile(u);n[u.key]=u,f.hasData()||e<this._source.maxzoom&&(s[u.key]=u)}this._retainLoadedChildren(s,e,o,n);for(var h=0,p=t;h<p.length;h+=1){var d=p[h],g=this._tiles[d.key];if(!g.hasData()){if(e+1>this._source.maxzoom){var m=d.children(this._source.maxzoom)[0],v=this.getTile(m);if(v&&v.hasData()){n[m.key]=m;continue}}else{var y=d.children(this._source.maxzoom);if(n[y[0].key]&&n[y[1].key]&&n[y[2].key]&&n[y[3].key])continue}for(var x=g.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(g=this.getTile(_))&&x&&(g=this._addTile(_)),g&&(n[_.key]=_,x=g.wasRequested(),g.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a<o.length;a+=1){var s=o[a];this._loadedParentTiles[s]=r}}},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[e.key]&&(clearTimeout(this._cacheTimers[e.key]),delete this._cacheTimers[e.key],this._setTileReloadTimer(e.key,r)));var n=Boolean(r);return n||(r=new t.Tile(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event(\"dataloading\",{tile:r,coord:r.tileID,dataType:\"source\"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout((function(){r._reloadTile(t,\"expired\"),delete r._timers[t]}),n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),c=s.map((function(t){return o.pointCoordinate(t)})),u=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,g=0,m=c;g<m.length;g+=1){var v=m[g];f=Math.min(f,v.x),h=Math.min(h,v.y),p=Math.max(p,v.x),d=Math.max(d,v.y)}for(var y=function(e){var n=i._tiles[u[e]];if(!n.holdingForFade()){var s=n.tileID,g=Math.pow(2,o.zoom-n.tileID.overscaledZ),m=r*n.queryPadding*t.EXTENT/n.tileSize/g,v=[s.getTilePoint(new t.MercatorCoordinate(f,h)),s.getTilePoint(new t.MercatorCoordinate(p,d))];if(v[0].x-m<t.EXTENT&&v[0].y-m<t.EXTENT&&v[1].x+m>=0&&v[1].y+m>=0){var y=l.map((function(t){return s.getTilePoint(t)})),x=c.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:y,cameraQueryGeometry:x,scale:g})}}},x=0;x<u.length;x++)y(x);return a},r.prototype.getVisibleCoordinates=function(t){for(var e=this,r=this.getRenderableIds(t).map((function(t){return e._tiles[t].tileID})),n=0,i=r;n<i.length;n+=1){var a=i[n];a.posMatrix=this.transform.calculatePosMatrix(a.toUnwrapped())}return r},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(It(this._source.type))for(var e in this._tiles){var r=this._tiles[e];if(void 0!==r.fadeEndTime&&r.fadeEndTime>=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||\"_geojsonTileLayer\",this._state.getState(t,e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles){this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,\"reloading\")}this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function Pt(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function It(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function Ot(){return new t.window.Worker(Zi.workerUrl)}Ct.maxOverzooming=10,Ct.maxUnderzooming=3;var zt=\"mapboxgl_preloaded_worker_pool\",Dt=function(){this.active={}};Dt.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length<Dt.workerCount;)this.workers.push(new Ot);return this.active[t]=!0,this.workers.slice()},Dt.prototype.release=function(t){delete this.active[t],0===this.numActive()&&(this.workers.forEach((function(t){t.terminate()})),this.workers=null)},Dt.prototype.isPreloaded=function(){return!!this.active[zt]},Dt.prototype.numActive=function(){return Object.keys(this.active).length};var Rt,Ft=Math.floor(t.browser.hardwareConcurrency/2);function Bt(){return Rt||(Rt=new Dt),Rt}function Nt(e,r){var n={};for(var i in e)\"ref\"!==i&&(n[i]=e[i]);return t.refProperties.forEach((function(t){t in r&&(n[t]=r[t])})),n}function jt(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)\"ref\"in t[n]&&(t[n]=Nt(t[n],e[t[n].ref]));return t}Dt.workerCount=Math.max(Math.min(Ft,6),1);var Ut={setStyle:\"setStyle\",addLayer:\"addLayer\",removeLayer:\"removeLayer\",setPaintProperty:\"setPaintProperty\",setLayoutProperty:\"setLayoutProperty\",setFilter:\"setFilter\",addSource:\"addSource\",removeSource:\"removeSource\",setGeoJSONSourceData:\"setGeoJSONSourceData\",setLayerZoomRange:\"setLayerZoomRange\",setLayerProperty:\"setLayerProperty\",setCenter:\"setCenter\",setZoom:\"setZoom\",setBearing:\"setBearing\",setPitch:\"setPitch\",setSprite:\"setSprite\",setGlyphs:\"setGlyphs\",setTransition:\"setTransition\",setLight:\"setLight\"};function Vt(t,e,r){r.push({command:Ut.addSource,args:[t,e[t]]})}function qt(t,e,r){e.push({command:Ut.removeSource,args:[t]}),r[t]=!0}function Ht(t,e,r,n){qt(t,r,n),Vt(t,e,r)}function Gt(e,r,n){var i;for(i in e[n])if(e[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;for(i in r[n])if(r[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;return!0}function Yt(e,r,n,i,a,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}))}function Wt(t){return t.id}function Xt(t,e){return t[e.id]=e,t}function Zt(e,r){if(!e)return[{command:Ut.setStyle,args:[r]}];var n=[];try{if(!t.deepEqual(e.version,r.version))return[{command:Ut.setStyle,args:[r]}];t.deepEqual(e.center,r.center)||n.push({command:Ut.setCenter,args:[r.center]}),t.deepEqual(e.zoom,r.zoom)||n.push({command:Ut.setZoom,args:[r.zoom]}),t.deepEqual(e.bearing,r.bearing)||n.push({command:Ut.setBearing,args:[r.bearing]}),t.deepEqual(e.pitch,r.pitch)||n.push({command:Ut.setPitch,args:[r.pitch]}),t.deepEqual(e.sprite,r.sprite)||n.push({command:Ut.setSprite,args:[r.sprite]}),t.deepEqual(e.glyphs,r.glyphs)||n.push({command:Ut.setGlyphs,args:[r.glyphs]}),t.deepEqual(e.transition,r.transition)||n.push({command:Ut.setTransition,args:[r.transition]}),t.deepEqual(e.light,r.light)||n.push({command:Ut.setLight,args:[r.light]});var i={},a=[];!function(e,r,n,i){var a;for(a in r=r||{},e=e||{})e.hasOwnProperty(a)&&(r.hasOwnProperty(a)||qt(a,n,i));for(a in r)r.hasOwnProperty(a)&&(e.hasOwnProperty(a)?t.deepEqual(e[a],r[a])||(\"geojson\"===e[a].type&&\"geojson\"===r[a].type&&Gt(e,r,a)?n.push({command:Ut.setGeoJSONSourceData,args:[a,r[a].data]}):Ht(a,r,n,i)):Vt(a,r,n))}(e.sources,r.sources,a,i);var o=[];e.layers&&e.layers.forEach((function(t){i[t.source]?n.push({command:Ut.removeLayer,args:[t.id]}):o.push(t)})),n=n.concat(a),function(e,r,n){r=r||[];var i,a,o,s,l,c,u,f=(e=e||[]).map(Wt),h=r.map(Wt),p=e.reduce(Xt,{}),d=r.reduce(Xt,{}),g=f.slice(),m=Object.create(null);for(i=0,a=0;i<f.length;i++)o=f[i],d.hasOwnProperty(o)?a++:(n.push({command:Ut.removeLayer,args:[o]}),g.splice(g.indexOf(o,a),1));for(i=0,a=0;i<h.length;i++)o=h[h.length-1-i],g[g.length-1-i]!==o&&(p.hasOwnProperty(o)?(n.push({command:Ut.removeLayer,args:[o]}),g.splice(g.lastIndexOf(o,g.length-a),1)):a++,c=g[g.length-i],n.push({command:Ut.addLayer,args:[d[o],c]}),g.splice(g.length-i,0,o),m[o]=!0);for(i=0;i<h.length;i++)if(s=p[o=h[i]],l=d[o],!m[o]&&!t.deepEqual(s,l))if(t.deepEqual(s.source,l.source)&&t.deepEqual(s[\"source-layer\"],l[\"source-layer\"])&&t.deepEqual(s.type,l.type)){for(u in Yt(s.layout,l.layout,n,o,null,Ut.setLayoutProperty),Yt(s.paint,l.paint,n,o,null,Ut.setPaintProperty),t.deepEqual(s.filter,l.filter)||n.push({command:Ut.setFilter,args:[o,l.filter]}),t.deepEqual(s.minzoom,l.minzoom)&&t.deepEqual(s.maxzoom,l.maxzoom)||n.push({command:Ut.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}));for(u in l)l.hasOwnProperty(u)&&!s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}))}else n.push({command:Ut.removeLayer,args:[o]}),c=g[g.lastIndexOf(o)+1],n.push({command:Ut.addLayer,args:[l,c]})}(o,r.layers,n)}catch(t){console.warn(\"Unable to compute style diff:\",t),n=[{command:Ut.setStyle,args:[r]}]}return n}var Jt=function(t,e){this.reset(t,e)};Jt.prototype.reset=function(t,e){this.points=t||[],this._distances=[0];for(var r=1;r<this.points.length;r++)this._distances[r]=this._distances[r-1]+this.points[r].dist(this.points[r-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(e||0,.5*this.length),this.paddedLength=this.length-2*this.padding},Jt.prototype.lerp=function(e){if(1===this.points.length)return this.points[0];e=t.clamp(e,0,1);for(var r=1,n=this._distances[r],i=e*this.paddedLength+this.padding;n<i&&r<this._distances.length;)n=this._distances[++r];var a=r-1,o=this._distances[a],s=n-o,l=s>0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Kt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a<this.xCellCount*this.yCellCount;a++)n.push([]),i.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};function Qt(e,r,n,i,a){var o=t.create();return r?(t.scale(o,o,[1/a,1/a,1]),n||t.rotateZ(o,o,i.angle)):t.multiply(o,i.labelPlaneMatrix,e),o}function $t(e,r,n,i,a){if(r){var o=t.clone(e);return t.scale(o,o,[a,a,1]),n||t.rotateZ(o,o,-i.angle),o}return i.glCoordMatrix}function te(e,r){var n=[e.x,e.y,0,1];fe(n,n,r);var i=n[3];return{point:new t.Point(n[0]/i,n[1]/i),signedDistanceFromCamera:i}}function ee(t,e){return.5+t/e*.5}function re(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ne(e,r,n,i,a,o,s,l){var c=i?e.textSizeData:e.iconSizeData,u=t.evaluateSizeForZoom(c,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,g=n.transform.width/n.transform.height,m=!1,v=0;v<d.length;v++){var y=d.get(v);if(y.hidden||y.writingMode===t.WritingMode.vertical&&!m)ue(y.numGlyphs,h);else{m=!1;var x=[y.anchorX,y.anchorY,0,1];if(t.transformMat4(x,x,r),re(x,f)){var b=x[3],_=ee(n.transform.cameraToCenterDistance,b),w=t.evaluateSizeForFeature(c,u,y),T=s?w/_:w*_,k=new t.Point(y.anchorX,y.anchorY),A=te(k,a).point,M={},S=oe(y,T,!1,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,g);m=S.useVertical,(S.notEnoughRoom||m||S.needsFlipping&&oe(y,T,!0,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,g).notEnoughRoom)&&ue(y.numGlyphs,h)}else ue(y.numGlyphs,h)}}i?e.text.dynamicLayoutVertexBuffer.updateData(h):e.icon.dynamicLayoutVertexBuffer.updateData(h)}function ie(t,e,r,n,i,a,o,s,l,c,u){var f=s.glyphStartIndex+s.numGlyphs,h=s.lineStartIndex,p=s.lineStartIndex+s.lineLength,d=e.getoffsetX(s.glyphStartIndex),g=e.getoffsetX(f-1),m=le(t*d,r,n,i,a,o,s.segment,h,p,l,c,u);if(!m)return null;var v=le(t*g,r,n,i,a,o,s.segment,h,p,l,c,u);return v?{first:m,last:v}:null}function ae(e,r,n,i){if(e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*i)return{useVertical:!0};return(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function oe(e,r,n,i,a,o,s,l,c,u,f,h,p,d){var g,m=r/24,v=e.lineOffsetX*m,y=e.lineOffsetY*m;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=ie(m,l,v,y,n,f,h,e,c,o,p);if(!w)return{notEnoughRoom:!0};var T=te(w.first.point,s).point,k=te(w.last.point,s).point;if(i&&!n){var A=ae(e.writingMode,T,k,d);if(A)return A}g=[w.first];for(var M=e.glyphStartIndex+1;M<x-1;M++)g.push(le(m*l.getoffsetX(M),v,y,n,f,h,e.segment,b,_,c,o,p));g.push(w.last)}else{if(i&&!n){var S=te(h,a).point,E=e.lineStartIndex+e.segment+1,L=new t.Point(c.getx(E),c.gety(E)),C=te(L,a),P=C.signedDistanceFromCamera>0?C.point:se(h,L,S,1,a),I=ae(e.writingMode,S,P,d);if(I)return I}var O=le(m*l.getoffsetX(e.glyphStartIndex),v,y,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,c,o,p);if(!O)return{notEnoughRoom:!0};g=[O]}for(var z=0,D=g;z<D.length;z+=1){var R=D[z];t.addDynamicAttributes(u,R.point,R.angle)}return{}}function se(t,e,r,n,i){var a=te(t.add(t.sub(e)._unit()),i).point,o=r.sub(a);return r.add(o._mult(n/o.mag()))}function le(e,r,n,i,a,o,s,l,c,u,f,h){var p=i?e-r:e+r,d=p>0?1:-1,g=0;i&&(d*=-1,g=Math.PI),d<0&&(g+=Math.PI);for(var m=d>0?l+s:l+s+1,v=a,y=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((m+=d)<l||m>=c)return null;if(y=v,w.push(v),void 0===(v=h[m])){var T=new t.Point(u.getx(m),u.gety(m)),k=te(T,f);if(k.signedDistanceFromCamera>0)v=h[m]=k.point;else{var A=m-d;v=se(0===x?o:new t.Point(u.getx(A),u.gety(A)),T,y,_-x+1,f)}}x+=b,b=y.dist(v)}var M=(_-x)/b,S=v.sub(y),E=S.mult(M)._add(y);E._add(S._unit()._perp()._mult(n*d));var L=g+Math.atan2(v.y-y.y,v.x-y.x);return w.push(E),{point:E,angle:L,path:w}}Kt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Kt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Kt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Kt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Kt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Kt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s<this.boxKeys.length;s++)o.push({key:this.boxKeys[s],x1:this.bboxes[4*s],y1:this.bboxes[4*s+1],x2:this.bboxes[4*s+2],y2:this.bboxes[4*s+3]});for(var l=0;l<this.circleKeys.length;l++){var c=this.circles[3*l],u=this.circles[3*l+1],f=this.circles[3*l+2];o.push({key:this.circleKeys[l],x1:c-f,y1:u-f,x2:c+f,y2:u+f})}return a?o.filter(a):o}var h={hitTest:i,seenUids:{box:{},circle:{}}};return this._forEachCell(t,e,r,n,this._queryCell,o,h,a),i?o.length>0:o},Kt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var c=[],u={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(a,s,o,l,this._queryCellCircle,c,u,i),n?c.length>0:c},Kt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Kt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Kt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Kt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,c=this.boxCells[i];if(null!==c)for(var u=this.bboxes,f=0,h=c;f<h.length;f+=1){var p=h[f];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(t<=u[d+2]&&e<=u[d+3]&&r>=u[d+0]&&n>=u[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:u[d],y1:u[d+1],x2:u[d+2],y2:u[d+3]})}}}var g=this.circleCells[i];if(null!==g)for(var m=this.circles,v=0,y=g;v<y.length;v+=1){var x=y[v];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circleAndRectCollide(m[b],m[b+1],m[b+2],t,e,r,n)&&(!s||s(this.circleKeys[x]))){if(o.hitTest)return a.push(!0),!0;var _=m[b],w=m[b+1],T=m[b+2];a.push({key:this.circleKeys[x],x1:_-T,y1:w-T,x2:_+T,y2:w+T})}}}},Kt.prototype._queryCellCircle=function(t,e,r,n,i,a,o,s){var l=o.circle,c=o.seenUids,u=this.boxCells[i];if(null!==u)for(var f=this.bboxes,h=0,p=u;h<p.length;h+=1){var d=p[h];if(!c.box[d]){c.box[d]=!0;var g=4*d;if(this._circleAndRectCollide(l.x,l.y,l.radius,f[g+0],f[g+1],f[g+2],f[g+3])&&(!s||s(this.boxKeys[d])))return a.push(!0),!0}}var m=this.circleCells[i];if(null!==m)for(var v=this.circles,y=0,x=m;y<x.length;y+=1){var b=x[y];if(!c.circle[b]){c.circle[b]=!0;var _=3*b;if(this._circlesCollide(v[_],v[_+1],v[_+2],l.x,l.y,l.radius)&&(!s||s(this.circleKeys[b])))return a.push(!0),!0}}},Kt.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToXCellCoord(t),c=this._convertToYCellCoord(e),u=this._convertToXCellCoord(r),f=this._convertToYCellCoord(n),h=l;h<=u;h++)for(var p=c;p<=f;p++){var d=this.xCellCount*p+h;if(i.call(this,t,e,r,n,d,a,o,s))return}},Kt.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},Kt.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},Kt.prototype._circlesCollide=function(t,e,r,n,i,a){var o=n-t,s=i-e,l=r+a;return l*l>o*o+s*s},Kt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var c=(o-i)/2,u=Math.abs(e-(i+c));if(u>c+r)return!1;if(l<=s||u<=c)return!0;var f=l-s,h=u-c;return f*f+h*h<=r*r};var ce=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function ue(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(ce,3*n)}}function fe(t,e,r){var n=e[0],i=e[1];return t[0]=r[0]*n+r[4]*i+r[12],t[1]=r[1]*n+r[5]*i+r[13],t[3]=r[3]*n+r[7]*i+r[15],t}var he=function(t,e,r){void 0===e&&(e=new Kt(t.width+200,t.height+200,25)),void 0===r&&(r=new Kt(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+100,this.screenBottomBoundary=t.height+100,this.gridRightBoundary=t.width+200,this.gridBottomBoundary=t.height+200};function pe(e,r,n){return r*(t.EXTENT/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}he.prototype.placeCollisionBox=function(t,e,r,n,i){var a=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),o=r*a.perspectiveRatio,s=t.x1*o+a.point.x,l=t.y1*o+a.point.y,c=t.x2*o+a.point.x,u=t.y2*o+a.point.y;return!this.isInsideGrid(s,l,c,u)||!e&&this.grid.hitTest(s,l,c,u,i)?{box:[],offscreen:!1}:{box:[s,l,c,u],offscreen:this.isOffscreen(s,l,c,u)}},he.prototype.placeCollisionCircles=function(e,r,n,i,a,o,s,l,c,u,f,h,p){var d=[],g=new t.Point(r.anchorX,r.anchorY),m=te(g,o),v=ee(this.transform.cameraToCenterDistance,m.signedDistanceFromCamera),y=(u?a/v:a*v)/t.ONE_EM,x=te(g,s).point,b=ie(y,i,r.lineOffsetX*y,r.lineOffsetY*y,!1,x,g,r,n,s,{}),_=!1,w=!1,T=!0;if(b){for(var k=.5*h*v+p,A=new t.Point(-100,-100),M=new t.Point(this.screenRightBoundary,this.screenBottomBoundary),S=new Jt,E=b.first,L=b.last,C=[],P=E.path.length-1;P>=1;P--)C.push(E.path[P]);for(var I=1;I<L.path.length;I++)C.push(L.path[I]);var O=2.5*k;if(l){var z=C.map((function(t){return te(t,l)}));C=z.some((function(t){return t.signedDistanceFromCamera<=0}))?[]:z.map((function(t){return t.point}))}var D=[];if(C.length>0){for(var R=C[0].clone(),F=C[0].clone(),B=1;B<C.length;B++)R.x=Math.min(R.x,C[B].x),R.y=Math.min(R.y,C[B].y),F.x=Math.max(F.x,C[B].x),F.y=Math.max(F.y,C[B].y);D=R.x>=A.x&&F.x<=M.x&&R.y>=A.y&&F.y<=M.y?[C]:F.x<A.x||R.x>M.x||F.y<A.y||R.y>M.y?[]:t.clipLine([C],A.x,A.y,M.x,M.y)}for(var N=0,j=D;N<j.length;N+=1){var U=j[N];S.reset(U,.25*k);var V=0;V=S.length<=.5*k?1:Math.ceil(S.paddedLength/O)+1;for(var q=0;q<V;q++){var H=q/Math.max(V-1,1),G=S.lerp(H),Y=G.x+100,W=G.y+100;d.push(Y,W,k,0);var X=Y-k,Z=W-k,J=Y+k,K=W+k;if(T=T&&this.isOffscreen(X,Z,J,K),w=w||this.isInsideGrid(X,Z,J,K),!e&&this.grid.hitTestCircle(Y,W,k,f)&&(_=!0,!c))return{circles:[],offscreen:!1,collisionDetected:_}}}}return{circles:!c&&_||!w?[]:d,offscreen:T,collisionDetected:_}},he.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,i=1/0,a=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var c=l[s],u=new t.Point(c.x+100,c.y+100);n=Math.min(n,u.x),i=Math.min(i,u.y),a=Math.max(a,u.x),o=Math.max(o,u.y),r.push(u)}for(var f={},h={},p=0,d=this.grid.query(n,i,a,o).concat(this.ignoredGrid.query(n,i,a,o));p<d.length;p+=1){var g=d[p],m=g.key;if(void 0===f[m.bucketInstanceId]&&(f[m.bucketInstanceId]={}),!f[m.bucketInstanceId][m.featureIndex]){var v=[new t.Point(g.x1,g.y1),new t.Point(g.x2,g.y1),new t.Point(g.x2,g.y2),new t.Point(g.x1,g.y2)];t.polygonIntersectsPolygon(r,v)&&(f[m.bucketInstanceId][m.featureIndex]=!0,void 0===h[m.bucketInstanceId]&&(h[m.bucketInstanceId]=[]),h[m.bucketInstanceId].push(m.featureIndex))}}return h},he.prototype.insertCollisionBox=function(t,e,r,n,i){var a={bucketInstanceId:r,featureIndex:n,collisionGroupID:i};(e?this.ignoredGrid:this.grid).insert(a,t[0],t[1],t[2],t[3])},he.prototype.insertCollisionCircles=function(t,e,r,n,i){for(var a=e?this.ignoredGrid:this.grid,o={bucketInstanceId:r,featureIndex:n,collisionGroupID:i},s=0;s<t.length;s+=4)a.insertCircle(o,t[s],t[s+1],t[s+2])},he.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var i=[r,n,0,1];return fe(i,i,e),{point:new t.Point((i[0]/i[3]+1)/2*this.transform.width+100,(-i[1]/i[3]+1)/2*this.transform.height+100),perspectiveRatio:.5+this.transform.cameraToCenterDistance/i[3]*.5}},he.prototype.isOffscreen=function(t,e,r,n){return r<100||t>=this.screenRightBoundary||n<100||e>this.screenBottomBoundary},he.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t<this.gridRightBoundary&&n>=0&&e<this.gridBottomBoundary},he.prototype.getViewportMatrix=function(){var e=t.identity([]);return t.translate(e,e,[-100,-100,0]),e};var de=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};de.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var ge=function(t,e,r,n,i){this.text=new de(t?t.text:null,e,r,i),this.icon=new de(t?t.icon:null,e,n,i)};ge.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var me=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},ve=function(){this.invProjMatrix=t.create(),this.viewportMatrix=t.create(),this.circles=[]},ye=function(t,e,r,n,i){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=i},xe=function(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}};function be(e,r,n,i,a){var o=t.getAnchorAlignment(e),s=-(o.horizontalAlign-.5)*r,l=-(o.verticalAlign-.5)*n,c=t.evaluateVariableOffset(e,i);return new t.Point(s+c[0]*a,l+c[1]*a)}function _e(e,r,n,i,a,o){var s=e.x1,l=e.x2,c=e.y1,u=e.y2,f=e.anchorPointX,h=e.anchorPointY,p=new t.Point(r,n);return i&&p._rotate(a?o:-o),{x1:s+p.x,y1:c+p.y,x2:l+p.x,y2:u+p.y,anchorPointX:f,anchorPointY:h}}xe.prototype.get=function(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){var e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:function(t){return t.collisionGroupID===e}}}return this.collisionGroups[t]};var we=function(t,e,r,n){this.transform=t.clone(),this.collisionIndex=new he(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=e,this.retainedQueryData={},this.collisionGroups=new xe(r),this.collisionCircleArrays={},this.prevPlacement=n,n&&(n.prevPlacement=void 0),this.placedOrientations={}};function Te(t,e,r,n,i){t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0)}we.prototype.getBucketParts=function(e,r,n,i){var a=n.getBucket(r),o=n.latestFeatureIndex;if(a&&o&&r.id===a.layerIds[0]){var s=n.collisionBoxArray,l=a.layers[0].layout,c=Math.pow(2,this.transform.zoom-n.tileID.overscaledZ),u=n.tileSize/t.EXTENT,f=this.transform.calculatePosMatrix(n.tileID.toUnwrapped()),h=\"map\"===l.get(\"text-pitch-alignment\"),p=\"map\"===l.get(\"text-rotation-alignment\"),d=pe(n,1,this.transform.zoom),g=Qt(f,h,p,this.transform,d),m=null;if(h){var v=$t(f,h,p,this.transform,d);m=t.multiply([],this.transform.labelPlaneMatrix,v)}this.retainedQueryData[a.bucketInstanceId]=new ye(a.bucketInstanceId,o,a.sourceLayerIndex,a.index,n.tileID);var y={bucket:a,layout:l,posMatrix:f,textLabelPlaneMatrix:g,labelToScreenMatrix:m,scale:c,textPixelRatio:u,holdingForFade:n.holdingForFade(),collisionBoxArray:s,partiallyEvaluatedTextSize:t.evaluateSizeForZoom(a.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(a.sourceID)};if(i)for(var x=0,b=a.sortKeyRanges;x<b.length;x+=1){var _=b[x],w=_.sortKey,T=_.symbolInstanceStart,k=_.symbolInstanceEnd;e.push({sortKey:w,symbolInstanceStart:T,symbolInstanceEnd:k,parameters:y})}else e.push({symbolInstanceStart:0,symbolInstanceEnd:a.symbolInstances.length,parameters:y})}},we.prototype.attemptAnchorPlacement=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d){var g,m=[f.textOffset0,f.textOffset1],v=be(t,r,n,m,i),y=this.collisionIndex.placeCollisionBox(_e(e,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate);if(d&&0===this.collisionIndex.placeCollisionBox(_e(d,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate).box.length)return;if(y.box.length>0)return this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(g=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:m,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:g},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:v,placedGlyphBoxes:y}},we.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,c=a.textLabelPlaneMatrix,u=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,g=a.collisionGroup,m=s.get(\"text-optional\"),v=s.get(\"icon-optional\"),y=s.get(\"text-allow-overlap\"),x=s.get(\"icon-allow-overlap\"),b=\"map\"===s.get(\"text-rotation-alignment\"),_=\"map\"===s.get(\"text-pitch-alignment\"),w=\"none\"!==s.get(\"icon-text-fit\"),T=\"viewport-y\"===s.get(\"symbol-z-order\"),k=y&&(x||!o.hasIconData()||v),A=x&&(y||!o.hasTextData()||m);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var M=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new me(!1,!1,!1);else{var p,T=!1,M=!1,S=!0,E=null,L={box:null,offscreen:null},C={box:null,offscreen:null},P=null,I=null,O=0,z=0,D=0;a.textFeatureIndex?O=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(O=e.featureIndex),a.verticalTextFeatureIndex&&(z=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,n=a,i.markUsedOrientation(o,n,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i<s.length;i+=1){if(s[i]===t.WritingMode.vertical?(L=n(),C=L):L=r(),L&&L.box&&L.box.length)break}else L=r()};if(s.get(\"text-variable-anchor\")){var N=s.get(\"text-variable-anchor\");if(i.prevPlacement&&i.prevPlacement.variableOffsets[e.crossTileID]){var j=i.prevPlacement.variableOffsets[e.crossTileID];N.indexOf(j.anchor)>0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,c=e.textBoxScale,u=w&&!x?r:null,h={box:[],offscreen:!1},p=y?2*N.length:N.length,d=0;d<p;++d){var m=N[d%N.length],v=d>=N.length,k=i.attemptAnchorPlacement(m,t,a,s,c,b,_,f,l,g,v,e,o,n,u);if(k&&(h=k.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=k.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox,n=L&&L.box&&L.box.length;return o.allowVerticalPlacement&&!n&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),L&&(T=L.box,S=L.offscreen);var V=F(L&&L.box);if(!T&&i.prevPlacement){var q=i.prevPlacement.variableOffsets[e.crossTileID];q&&(i.variableOffsets[e.crossTileID]=q,i.markUsedJustification(o,q.anchor,e,V))}}else{var H=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,y,f,l,g.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return H(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?H(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(L&&L.box&&L.box.length)}}if(T=(p=L)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),Y=t.evaluateSizeForFeature(o.textSizeData,d,G),W=s.get(\"text-padding\"),X=e.collisionCircleDiameter;P=i.collisionIndex.placeCollisionCircles(y,G,o.lineVertexArray,o.glyphOffsetArray,Y,l,c,u,n,_,g.predicate,X,W),T=y||P.circles.length>0&&!P.collisionDetected,S=S&&P.offscreen}if(a.iconFeatureIndex&&(D=a.iconFeatureIndex),a.iconBox){var Z=function(t){var e=w&&E?_e(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,g.predicate)};M=C&&C.box&&C.box.length&&a.verticalIconBox?(I=Z(a.verticalIconBox)).box.length>0:(I=Z(a.iconBox)).box.length>0,S=S&&I.offscreen}var J=m||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,K=v||0===e.numIconVertices;if(J||K?K?J||(M=M&&T):T=M&&T:M=T=M&&T,T&&p&&p.box&&(C&&C.box&&z?i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,z,g.ID):i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,O,g.ID)),M&&I&&i.collisionIndex.insertCollisionBox(I.box,s.get(\"icon-ignore-placement\"),o.bucketInstanceId,D,g.ID),P&&(T&&i.collisionIndex.insertCollisionCircles(P.circles,s.get(\"text-ignore-placement\"),o.bucketInstanceId,O,g.ID),n)){var Q=o.bucketInstanceId,$=i.collisionCircleArrays[Q];void 0===$&&($=i.collisionCircleArrays[Q]=new ve);for(var tt=0;tt<P.circles.length;tt+=4)$.circles.push(P.circles[tt+0]),$.circles.push(P.circles[tt+1]),$.circles.push(P.circles[tt+2]),$.circles.push(P.collisionDetected?1:0)}i.placements[e.crossTileID]=new me(T||k,M||A,S||o.justReloaded),r[e.crossTileID]=!0}};if(T)for(var S=o.getSortedSymbolIndexes(this.transform.angle),E=S.length-1;E>=0;--E){var L=S[E];M(o.symbolInstances.get(L),o.collisionArrays[L])}else for(var C=e.symbolInstanceStart;C<e.symbolInstanceEnd;C++)M(o.symbolInstances.get(C),o.collisionArrays[C]);if(n&&o.bucketInstanceId in this.collisionCircleArrays){var P=this.collisionCircleArrays[o.bucketInstanceId];t.invert(P.invProjMatrix,l),P.viewportMatrix=this.collisionIndex.getViewportMatrix()}o.justReloaded=!1},we.prototype.markUsedJustification=function(e,r,n,i){var a,o={left:n.leftJustifiedTextSymbolIndex,center:n.centerJustifiedTextSymbolIndex,right:n.rightJustifiedTextSymbolIndex};a=i===t.WritingMode.vertical?n.verticalPlacedTextSymbolIndex:o[t.getAnchorJustification(r)];for(var s=0,l=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex,n.verticalPlacedTextSymbolIndex];s<l.length;s+=1){var c=l[s];c>=0&&(e.text.placedSymbolArray.get(c).crossTileID=a>=0&&c!==a?0:n.crossTileID)}},we.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o<s.length;o+=1){var l=s[o];e.text.placedSymbolArray.get(l).placedOrientation=i}n.verticalPlacedTextSymbolIndex&&(e.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=a)},we.prototype.commit=function(t){this.commitTime=t,this.zoomAtLastRecencyCheck=this.transform.zoom;var e=this.prevPlacement,r=!1;this.prevZoomAdjustment=e?e.zoomAdjustment(this.transform.zoom):0;var n=e?e.symbolFadeChange(t):1,i=e?e.opacities:{},a=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(var s in this.placements){var l=this.placements[s],c=i[s];c?(this.opacities[s]=new ge(c,n,l.text,l.icon),r=r||l.text!==c.text.placed||l.icon!==c.icon.placed):(this.opacities[s]=new ge(null,n,l.text,l.icon,l.skipFade),r=r||l.text||l.icon)}for(var u in i){var f=i[u];if(!this.opacities[u]){var h=new ge(f,n,!1,!1);h.isHidden()||(this.opacities[u]=h,r=r||f.text.placed||f.icon.placed)}}for(var p in a)this.variableOffsets[p]||!this.opacities[p]||this.opacities[p].isHidden()||(this.variableOffsets[p]=a[p]);for(var d in o)this.placedOrientations[d]||!this.opacities[d]||this.opacities[d].isHidden()||(this.placedOrientations[d]=o[d]);r?this.lastPlacementChangeTime=t:\"number\"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)},we.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){var a=i[n],o=a.getBucket(t);o&&a.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,a.collisionBoxArray)}},we.prototype.updateBucketOpacities=function(e,r,n){var i=this;e.hasTextData()&&e.text.opacityVertexArray.clear(),e.hasIconData()&&e.icon.opacityVertexArray.clear(),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexArray.clear(),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexArray.clear();var a=e.layers[0].layout,o=new ge(null,0,!1,!1,!0),s=a.get(\"text-allow-overlap\"),l=a.get(\"icon-allow-overlap\"),c=a.get(\"text-variable-anchor\"),u=\"map\"===a.get(\"text-rotation-alignment\"),f=\"map\"===a.get(\"text-pitch-alignment\"),h=\"none\"!==a.get(\"icon-text-fit\"),p=new ge(null,0,s&&(l||!e.hasIconData()||a.get(\"icon-optional\")),l&&(s||!e.hasTextData()||a.get(\"text-optional\")),!0);!e.collisionArrays&&n&&(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData())&&e.deserializeCollisionBoxes(n);for(var d=function(t,e,r){for(var n=0;n<e/4;n++)t.opacityVertexArray.emplaceBack(r)},g=function(n){var a=e.symbolInstances.get(n),s=a.numHorizontalGlyphVertices,l=a.numVerticalGlyphVertices,g=a.crossTileID,m=r[g],v=i.opacities[g];m?v=o:v||(v=p,i.opacities[g]=v),r[g]=!0;var y=s>0||l>0,x=a.numIconVertices>0,b=i.placedOrientations[a.crossTileID],_=b===t.WritingMode.vertical,w=b===t.WritingMode.horizontal||b===t.WritingMode.horizontalOnly;if(y){var T=Pe(v.text),k=_?Ie:T;d(e.text,s,k);var A=w?Ie:T;d(e.text,l,A);var M=v.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=M||_?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=M||w?1:0);var S=i.variableOffsets[a.crossTileID];S&&i.markUsedJustification(e,S.anchor,a,b);var E=i.placedOrientations[a.crossTileID];E&&(i.markUsedJustification(e,\"left\",a,E),i.markUsedOrientation(e,E,a))}if(x){var L=Pe(v.icon),C=!(h&&a.verticalPlacedIconSymbolIndex&&_);if(a.placedIconSymbolIndex>=0){var P=C?L:Ie;d(e.icon,a.numIconVertices,P),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=v.icon.isHidden()}if(a.verticalPlacedIconSymbolIndex>=0){var I=C?Ie:L;d(e.icon,a.numVerticalIconVertices,I),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=v.icon.isHidden()}}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var O=e.collisionArrays[n];if(O){var z=new t.Point(0,0);if(O.textBox||O.verticalTextBox){var D=!0;if(c){var R=i.variableOffsets[g];R?(z=be(R.anchor,R.width,R.height,R.textOffset,R.textBoxScale),u&&z._rotate(f?i.transform.angle:-i.transform.angle)):D=!1}O.textBox&&Te(e.textCollisionBox.collisionVertexArray,v.text.placed,!D||_,z.x,z.y),O.verticalTextBox&&Te(e.textCollisionBox.collisionVertexArray,v.text.placed,!D||w,z.x,z.y)}var F=Boolean(!w&&O.verticalIconBox);O.iconBox&&Te(e.iconCollisionBox.collisionVertexArray,v.icon.placed,F,h?z.x:0,h?z.y:0),O.verticalIconBox&&Te(e.iconCollisionBox.collisionVertexArray,v.icon.placed,!F,h?z.x:0,h?z.y:0)}}},m=0;m<e.symbolInstances.length;m++)g(m);if(e.sortFeatures(this.transform.angle),this.retainedQueryData[e.bucketInstanceId]&&(this.retainedQueryData[e.bucketInstanceId].featureSortOrder=e.featureSortOrder),e.hasTextData()&&e.text.opacityVertexBuffer&&e.text.opacityVertexBuffer.updateData(e.text.opacityVertexArray),e.hasIconData()&&e.icon.opacityVertexBuffer&&e.icon.opacityVertexBuffer.updateData(e.icon.opacityVertexArray),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexBuffer&&e.iconCollisionBox.collisionVertexBuffer.updateData(e.iconCollisionBox.collisionVertexArray),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexBuffer&&e.textCollisionBox.collisionVertexBuffer.updateData(e.textCollisionBox.collisionVertexArray),e.bucketInstanceId in this.collisionCircleArrays){var v=this.collisionCircleArrays[e.bucketInstanceId];e.placementInvProjMatrix=v.invProjMatrix,e.placementViewportMatrix=v.viewportMatrix,e.collisionCircleArray=v.circles,delete this.collisionCircleArrays[e.bucketInstanceId]}},we.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment},we.prototype.zoomAdjustment=function(t){return Math.max(0,(this.transform.zoom-t)/1.5)},we.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},we.prototype.stillRecent=function(t,e){var r=this.zoomAtLastRecencyCheck===e?1-this.zoomAdjustment(e):1;return this.zoomAtLastRecencyCheck=e,this.commitTime+this.fadeDuration*r>t},we.prototype.setStale=function(){this.stale=!0};var ke=Math.pow(2,25),Ae=Math.pow(2,24),Me=Math.pow(2,17),Se=Math.pow(2,16),Ee=Math.pow(2,9),Le=Math.pow(2,8),Ce=Math.pow(2,1);function Pe(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*ke+e*Ae+r*Me+e*Se+r*Ee+e*Le+r*Ce+e}var Ie=0,Oe=function(t){this._sortAcrossTiles=\"viewport-y\"!==t.layout.get(\"symbol-z-order\")&&void 0!==t.layout.get(\"symbol-sort-key\").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Oe.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex<t.length;){var o=t[this._currentTileIndex];if(e.getBucketParts(a,n,o,this._sortAcrossTiles),this._currentTileIndex++,i())return!0}for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,a.sort((function(t,e){return t.sortKey-e.sortKey})));this._currentPartIndex<a.length;){var s=a[this._currentPartIndex];if(e.placeLayerBucketPart(s,this._seenCrossTileIDs,r),this._currentPartIndex++,i())return!0}return!1};var ze=function(t,e,r,n,i,a,o){this.placement=new we(t,i,a,o),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};ze.prototype.isDone=function(){return this._done},ze.prototype.continuePlacement=function(e,r,n){for(var i=this,a=t.browser.now(),o=function(){var e=t.browser.now()-a;return!i._forceFullPlacement&&e>2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Oe(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},ze.prototype.commit=function(t){return this.placement.commit(t),this.placement};var De=512/t.EXTENT/2,Re=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;n<e.length;n++){var i=e.get(n),a=i.key;this.indexedSymbolInstances[a]||(this.indexedSymbolInstances[a]=[]),this.indexedSymbolInstances[a].push({crossTileID:i.crossTileID,coord:this.getScaledCoordinates(i,t)})}};Re.prototype.getScaledCoordinates=function(e,r){var n=r.canonical.z-this.tileID.canonical.z,i=De/Math.pow(2,n);return{x:Math.floor((r.canonical.x*t.EXTENT+e.anchorX)*i),y:Math.floor((r.canonical.y*t.EXTENT+e.anchorY)*i)}},Re.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),i=0;i<t.length;i++){var a=t.get(i);if(!a.crossTileID){var o=this.indexedSymbolInstances[a.key];if(o)for(var s=this.getScaledCoordinates(a,e),l=0,c=o;l<c.length;l+=1){var u=c[l];if(Math.abs(u.coord.x-s.x)<=n&&Math.abs(u.coord.y-s.y)<=n&&!r[u.crossTileID]){r[u.crossTileID]=!0,a.crossTileID=u.crossTileID;break}}}}};var Fe=function(){this.maxCrossTileID=0};Fe.prototype.generate=function(){return++this.maxCrossTileID};var Be=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Be.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],i={};for(var a in n){var o=n[a];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),i[o.tileID.key]=o}this.indexes[r]=i}this.lng=t},Be.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0;n<e.symbolInstances.length;n++){e.symbolInstances.get(n).crossTileID=0}this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var i=this.usedCrossTileIDs[t.overscaledZ];for(var a in this.indexes){var o=this.indexes[a];if(Number(a)>t.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var c=o[t.scaledTo(Number(a)).key];c&&c.findMatches(e.symbolInstances,t,i)}}for(var u=0;u<e.symbolInstances.length;u++){var f=e.symbolInstances.get(u);f.crossTileID||(f.crossTileID=r.generate(),i[f.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new Re(t,e.symbolInstances,e.bucketInstanceId),!0},Be.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,i=e.indexedSymbolInstances[r];n<i.length;n+=1){var a=i[n];delete this.usedCrossTileIDs[t][a.crossTileID]}},Be.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var i in n)t[n[i].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[i]),delete n[i],e=!0)}return e};var Ne=function(){this.layerIndexes={},this.crossTileIDs=new Fe,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Ne.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Be);var i=!1,a={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],c=l.getBucket(t);c&&t.id===c.layerIds[0]&&(c.bucketInstanceId||(c.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,c,this.crossTileIDs)&&(i=!0),a[c.bucketInstanceId]=!0)}return n.removeStaleBuckets(a)&&(i=!0),i},Ne.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach((function(t){e[t]=!0})),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var je=function(e,r){return t.emitValidationErrors(e,r&&r.filter((function(t){return\"source.canvas\"!==t.identifier})))},Ue=t.pick(Ut,[\"addLayer\",\"removeLayer\",\"setPaintProperty\",\"setLayoutProperty\",\"setFilter\",\"addSource\",\"removeSource\",\"setLayerZoomRange\",\"setLight\",\"setTransition\",\"setGeoJSONSourceData\"]),Ve=t.pick(Ut,[\"setCenter\",\"setZoom\",\"setBearing\",\"setPitch\"]),qe=function(){var e={},r=t.styleSpec.$version;for(var n in t.styleSpec.$root){var i=t.styleSpec.$root[n];if(i.required){var a=null;null!=(a=\"version\"===n?r:\"array\"===i.type?[]:{})&&(e[n]=a)}}return e}(),He=function(e){function r(n,i){var a=this;void 0===i&&(i={}),e.call(this),this.map=n,this.dispatcher=new k(Bt(),this),this.imageManager=new h,this.imageManager.setEventedParent(this),this.glyphManager=new x(n._requestManager,i.localIdeographFontFamily),this.lineAtlas=new T(256,512),this.crossTileSymbolIndex=new Ne,this._layers={},this._serializedLayers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ZoomHistory,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast(\"setReferrer\",t.getReferrer());var o=this;this._rtlTextPluginCallback=r.registerForPluginStateChange((function(e){var r={pluginStatus:e.pluginStatus,pluginURL:e.pluginURL};o.dispatcher.broadcast(\"syncRTLPluginState\",r,(function(e,r){if((t.triggerPluginCompletionEvent(e),r)&&r.every((function(t){return t})))for(var n in o.sourceCaches)o.sourceCaches[n].reload()}))})),this.on(\"data\",(function(t){if(\"source\"===t.dataType&&\"metadata\"===t.sourceDataType){var e=a.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in a._layers){var i=a._layers[n];i.source===r.id&&a._validateLayer(i)}}}}))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"}));var i=\"boolean\"==typeof r.validate?r.validate:!t.isMapboxURL(e);e=this.map._requestManager.normalizeStyleURL(e,r.accessToken);var a=this.map._requestManager.transformRequest(e,t.ResourceType.Style);this._request=t.getJSON(a,(function(e,r){n._request=null,e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,i)}))},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._request=t.browser.frame((function(){n._request=null,n._load(e,!1!==r.validate)}))},r.prototype.loadEmpty=function(){this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._load(qe,!1)},r.prototype._load=function(e,r){if(!r||!je(this,t.validateStyle(e))){for(var n in this._loaded=!0,this.stylesheet=e,e.sources)this.addSource(n,e.sources[n],{validate:!1});e.sprite?this._loadSprite(e.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var i=jt(this.stylesheet.layers);this._order=i.map((function(t){return t.id})),this._layers={},this._serializedLayers={};for(var a=0,o=i;a<o.length;a+=1){var s=o[a];(s=t.createStyleLayer(s)).setEventedParent(this,{layer:{id:s.id}}),this._layers[s.id]=s,this._serializedLayers[s.id]=s.serialize()}this.dispatcher.broadcast(\"setLayers\",this._serializeLayers(this._order)),this.light=new w(this.stylesheet.light),this.fire(new t.Event(\"data\",{dataType:\"style\"})),this.fire(new t.Event(\"style.load\"))}},r.prototype._loadSprite=function(e){var r=this;this._spriteRequest=function(e,r,n){var i,a,o,s=t.browser.devicePixelRatio>1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,u())})),c=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),(function(t,e){c=null,o||(o=t,a=e,u())}));function u(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],c=l.width,u=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,g=l.stretchX,m=l.stretchY,v=l.content,y=new t.RGBAImage({width:c,height:u});t.RGBAImage.copy(e,y,{x:f,y:h},{x:0,y:0},{width:c,height:u}),r[s]={data:y,pixelRatio:d,sdf:p,stretchX:g,stretchY:m,content:v}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),c&&(c.cancel(),c=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast(\"setImages\",r._availableImages),r.fire(new t.Event(\"data\",{dataType:\"style\"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=this._layers[i];\"custom\"!==a.type&&e.push(a.serialize())}return e},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},r.prototype.update=function(e){if(this._loaded){var r=this._changed;if(this._changed){var n=Object.keys(this._updatedLayers),i=Object.keys(this._removedLayers);for(var a in(n.length||i.length)&&this._updateWorkerLayers(n,i),this._updatedSources){var o=this._updatedSources[a];\"reload\"===o?this._reloadSource(a):\"clear\"===o&&this._clearSource(a)}for(var s in this._updateTilesForChangedImages(),this._updatedPaintProps)this._layers[s].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates()}for(var l in this.sourceCaches)this.sourceCaches[l].used=!1;for(var c=0,u=this._order;c<u.length;c+=1){var f=u[c],h=this._layers[f];h.recalculate(e,this._availableImages),!h.isHidden(e.zoom)&&h.source&&(this.sourceCaches[h.source].used=!0)}this.light.recalculate(e),this.z=e.zoom,r&&this.fire(new t.Event(\"data\",{dataType:\"style\"}))}},r.prototype._updateTilesForChangedImages=function(){var t=Object.keys(this._changedImages);if(t.length){for(var e in this.sourceCaches)this.sourceCaches[e].reloadTilesForDependencies([\"icons\",\"patterns\"],t);this._changedImages={}}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast(\"updateLayers\",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),je(this,t.validateStyle(e)))return!1;(e=t.clone$1(e)).layers=jt(e.layers);var n=Zt(this.serialize(),e).filter((function(t){return!(t.command in Ve)}));if(0===n.length)return!1;var i=n.filter((function(t){return!(t.command in Ue)}));if(i.length>0)throw new Error(\"Unimplemented: \"+i.map((function(t){return t.command})).join(\", \")+\".\");return n.forEach((function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0)||!this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n)){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Ct(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else{var a;if(\"custom\"===e.type){if(je(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&\"custom\"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,\"layers.\"+i.id+\".filter\",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;\"geojson\"===o&&i?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o=\"vector\"===a?e.sourceLayer:void 0;\"vector\"!==a||o?r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is requred to remove its specific state property.\"))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if(\"vector\"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&\"raster\"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s<l.length;s+=1){var c=l[s][o];if(c)for(var u=0,f=c;u<f.length;u+=1){var h=f[u];i.push(h)}}}}i.sort((function(t,e){return e.intersectionZ-t.intersectionZ}));for(var p=[],d=this._order.length-1;d>=0;d--){var g=this._order[d];if(r(g))for(var m=i.length-1;m>=0;m--){var v=i[m].feature;if(n[v.layer.id]<d)break;p.push(v),i.pop()}else for(var y=0,x=t;y<x.length;y+=1){var b=x[y][g];if(b)for(var _=0,w=b;_<w.length;_+=1){var T=w[_];p.push(T.feature)}}}return p},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,\"queryRenderedFeatures.filter\",r.filter,null,r);var i={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error(\"parameters.layers must be an Array.\"))),[];for(var a=0,o=r.layers;a<o.length;a+=1){var s=o[a],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error(\"The layer '\"+s+\"' does not exist in the map's style and cannot be queried for features.\"))),[];i[l.source]=!0}}var c=[];for(var u in r.availableImages=this._availableImages,this.sourceCaches)r.layers&&!i[u]||c.push(F(this.sourceCaches[u],this._layers,this._serializedLayers,e,r,n));return this.placement&&c.push(function(t,e,r,n,i,a,o){for(var s={},l=a.queryRenderedSymbols(n),c=[],u=0,f=Object.keys(l).map(Number);u<f.length;u+=1){var h=f[u];c.push(o[h])}c.sort(B);for(var p=function(){var r=g[d],n=r.featureIndex.lookupSymbolFeatures(l[r.bucketInstanceId],e,r.bucketIndex,r.sourceLayerIndex,i.filter,i.layers,i.availableImages,t);for(var a in n){var o=s[a]=s[a]||[],c=n[a];c.sort((function(t,e){var n=r.featureSortOrder;if(n){var i=n.indexOf(t.featureIndex);return n.indexOf(e.featureIndex)-i}return e.featureIndex-t.featureIndex}));for(var u=0,f=c;u<f.length;u+=1){var h=f[u];o.push(h)}}},d=0,g=c;d<g.length;d+=1)p();var m=function(e){s[e].forEach((function(n){var i=n.feature,a=t[e],o=r[a.source].getFeatureState(i.layer[\"source-layer\"],i.id);i.source=i.layer.source,i.layer[\"source-layer\"]&&(i.sourceLayer=i.layer[\"source-layer\"]),i.state=o}))};for(var v in s)m(v);return s}(this._layers,this._serializedLayers,this.sourceCaches,e,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(c)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,\"querySourceFeatures.filter\",r.filter,null,r);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map((function(e){return t.getTileByID(e)})),n=[],i={},a=0;a<r.length;a++){var o=r[a],s=o.tileID.canonical.key;i[s]||(i[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called \"'+t+'\" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"loadWorkerSource\",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e,r){void 0===r&&(r={}),this._checkLoaded();var n=this.light.getLight(),i=!1;for(var a in e)if(!t.deepEqual(e[a],n[a])){i=!0;break}if(i){var o={now:t.browser.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e,r),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,i,a){return void 0===a&&(a={}),(!a||!1!==a.validate)&&je(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.styleSpec},i)))},r.prototype._remove=function(){for(var e in this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),t.evented.off(\"pluginStateChange\",this._rtlTextPluginCallback),this._layers){this._layers[e].setEventedParent(null)}for(var r in this.sourceCaches)this.sourceCaches[r].clearTiles(),this.sourceCaches[r].setEventedParent(null);this.imageManager.setEventedParent(null),this.setEventedParent(null),this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(e,r,n,i,a){void 0===a&&(a=!1);for(var o=!1,s=!1,l={},c=0,u=this._order;c<u.length;c+=1){var f=u[c],h=this._layers[f];if(\"symbol\"===h.type){if(!l[h.source]){var p=this.sourceCaches[h.source];l[h.source]=p.getRenderableIds(!0).map((function(t){return p.getTileByID(t)})).sort((function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)}))}var d=this.crossTileSymbolIndex.addLayer(h,l[h.source],e.center.lng);o=o||d}}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((a=a||this._layerOrderChanged||0===n)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(t.browser.now(),e.zoom))&&(this.pauseablePlacement=new ze(e,this._order,a,r,n,i,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,l),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(t.browser.now()),s=!0),o&&this.pauseablePlacement.placement.setStale()),s||o)for(var g=0,m=this._order;g<m.length;g+=1){var v=m[g],y=this._layers[v];\"symbol\"===y.type&&this.placement.updateLayerOpacities(y,l[y.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(t.browser.now())},r.prototype._releaseSymbolFadeTiles=function(){for(var t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r),this._updateTilesForChangedImages();var n=this.sourceCaches[e.source];n&&n.setDependencies(e.tileID.key,e.type,e.icons)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r.prototype.getResource=function(e,r,n){return t.makeRequest(r,n)},r}(t.Evented);He.getSourceType=function(t){return D[t]},He.setSourceType=function(t,e){D[t]=e},He.registerForPluginStateChange=t.registerForPluginStateChange;var Ge=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2}]),Ye=yr(\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\",\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}\"),We=yr(\"uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Xe=yr(\"uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}\"),Ze=yr(\"varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main(void) {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}\"),Je=yr(\"void main() {gl_FragColor=vec4(1.0);}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Ke=yr(\"uniform highp float u_intensity;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main() {\\n#pragma mapbox: initialize highp float weight\\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#pragma mapbox: define mediump float radius\\nconst highp float ZERO=1.0/255.0/16.0;\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main(void) {\\n#pragma mapbox: initialize highp float weight\\n#pragma mapbox: initialize mediump float radius\\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}\"),Qe=yr(\"uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(0.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}\"),$e=yr(\"varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),tr=yr(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd  =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz  /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),er=yr(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\"),rr=yr(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),nr=yr(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),ir=yr(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),ar=yr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),or=yr(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),sr=yr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),lr=yr(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform float u_maxzoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggeration=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/ pow(2.0,(u_zoom-u_maxzoom)*exaggeration+19.2562-u_zoom);gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),cr=yr(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),ur=yr(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),fr=yr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,vec2(v_lineprogress,0.5));gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define MAX_LINE_DISTANCE 32767.0\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_lineprogress=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0/MAX_LINE_DISTANCE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),hr=yr(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}\"),pr=yr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),dr=yr(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),gr=yr(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),mr=yr(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\"),vr=yr(\"#define SDF_PX 8.0\\n#define SDF 1.0\\n#define ICON 0.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}\");function yr(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n={};return{fragmentSource:t=t.replace(r,(function(t,e,r,i,a){return n[a]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"})),vertexSource:e=e.replace(r,(function(t,e,r,i,a){var o=\"float\"===i?\"vec2\":\"vec4\",s=a.match(/color/)?\"color\":o;return n[a]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+a+\" = a_\"+a+\";\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = a_\"+a+\";\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"}))}}var xr=Object.freeze({__proto__:null,prelude:Ye,background:We,backgroundPattern:Xe,circle:Ze,clippingMask:Je,heatmap:Ke,heatmapTexture:Qe,collisionBox:$e,collisionCircle:tr,debug:er,fill:rr,fillOutline:nr,fillOutlinePattern:ir,fillPattern:ar,fillExtrusion:or,fillExtrusionPattern:sr,hillshadePrepare:lr,hillshade:cr,line:ur,lineGradient:fr,linePattern:hr,lineSDF:pr,raster:dr,symbolIcon:gr,symbolSDF:mr,symbolTextAndIcon:vr}),br=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};br.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,c=0;!l&&c<n.length;c++)this.boundPaintVertexBuffers[c]!==n[c]&&(l=!0);var u=!this.vao||this.boundProgram!==e||this.boundLayoutVertexBuffer!==r||l||this.boundIndexBuffer!==i||this.boundVertexOffset!==a||this.boundDynamicVertexBuffer!==o||this.boundDynamicVertexBuffer2!==s;!t.extVertexArrayObject||u?this.freshBind(e,r,n,i,a,o,s):(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),i&&i.dynamicDraw&&i.bind(),s&&s.bind())},br.prototype.freshBind=function(t,e,r,n,i,a,o){var s,l=t.numAttributes,c=this.context,u=c.gl;if(c.extVertexArrayObject)this.vao&&this.destroy(),this.vao=c.extVertexArrayObject.createVertexArrayOES(),c.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=i,this.boundDynamicVertexBuffer=a,this.boundDynamicVertexBuffer2=o;else{s=c.currentNumAttributes||0;for(var f=l;f<s;f++)u.disableVertexAttribArray(f)}e.enableAttributes(u,t);for(var h=0,p=r;h<p.length;h+=1){p[h].enableAttributes(u,t)}a&&a.enableAttributes(u,t),o&&o.enableAttributes(u,t),e.bind(),e.setVertexAttribPointers(u,t,i);for(var d=0,g=r;d<g.length;d+=1){var m=g[d];m.bind(),m.setVertexAttribPointers(u,t,i)}a&&(a.bind(),a.setVertexAttribPointers(u,t,i)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(u,t,i)),c.currentNumAttributes=l},br.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var _r=function(t,e,r,n,i){var a=t.gl;this.program=a.createProgram();var o=r?r.defines():[];i&&o.push(\"#define OVERDRAW_INSPECTOR;\");var s=o.concat(Ye.fragmentSource,e.fragmentSource).join(\"\\n\"),l=o.concat(Ye.vertexSource,e.vertexSource).join(\"\\n\"),c=a.createShader(a.FRAGMENT_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(c,s),a.compileShader(c),a.attachShader(this.program,c);var u=a.createShader(a.VERTEX_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(u,l),a.compileShader(u),a.attachShader(this.program,u);for(var f=r?r.layoutAttributes:[],h=0;h<f.length;h++)a.bindAttribLocation(this.program,h,f[h].name);a.linkProgram(this.program),a.deleteShader(u),a.deleteShader(c),this.numAttributes=a.getProgramParameter(this.program,a.ACTIVE_ATTRIBUTES),this.attributes={};for(var p={},d=0;d<this.numAttributes;d++){var g=a.getActiveAttrib(this.program,d);g&&(this.attributes[g.name]=a.getAttribLocation(this.program,g.name))}for(var m=a.getProgramParameter(this.program,a.ACTIVE_UNIFORMS),v=0;v<m;v++){var y=a.getActiveUniform(this.program,v);y&&(p[y.name]=a.getUniformLocation(this.program,y.name))}this.fixedUniforms=n(t,p),this.binderUniforms=r?r.getUniforms(t,p):[]}}};function wr(t,e,r){var n=1/pe(r,1,e.transform.tileZoom),i=Math.pow(2,r.tileID.overscaledZ),a=r.tileSize*Math.pow(2,e.transform.tileZoom)/i,o=a*(r.tileID.canonical.x+r.tileID.wrap*i),s=a*r.tileID.canonical.y;return{u_image:0,u_texsize:r.imageAtlasTexture.size,u_scale:[n,t.fromScale,t.toScale],u_fade:t.t,u_pixel_coord_upper:[o>>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}_r.prototype.draw=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g){var m,v=t.gl;if(!this.failedToCreate){for(var y in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[y].set(o[y]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(m={},m[v.LINES]=2,m[v.TRIANGLES]=3,m[v.LINE_STRIP]=1,m)[e],b=0,_=u.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new br)).bind(t,this,l,p?p.getPaintVertexBuffers():[],c,w.vertexOffset,d,g),v.drawElements(e,w.primitiveLength*x,v.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var Tr=function(e,r,n,i){var a=r.style.light,o=a.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===a.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var c=a.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get(\"intensity\"),u_lightcolor:[c.r,c.g,c.b],u_vertical_gradient:+n,u_opacity:i}},kr=function(e,r,n,i,a,o,s){return t.extend(Tr(e,r,n,i),wr(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},Ar=function(t){return{u_matrix:t}},Mr=function(e,r,n,i){return t.extend(Ar(e),wr(n,r,i))},Sr=function(t,e){return{u_matrix:t,u_world:e}},Er=function(e,r,n,i,a){return t.extend(Mr(e,r,n,i),{u_world:a})},Lr=function(e,r,n,i){var a,o,s=e.transform;if(\"map\"===i.paint.get(\"circle-pitch-alignment\")){var l=pe(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===i.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get(\"circle-translate\"),i.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},Cr=function(t,e,r){var n=pe(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},Pr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},Ir=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Or=function(t){return{u_matrix:t}},zr=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:pe(e,1,r),u_intensity:n}};function Dr(e,r){var n=Math.pow(2,r.canonical.z),i=r.canonical.y;return[new t.MercatorCoordinate(0,i/n).toLngLat().lat,new t.MercatorCoordinate(0,(i+1)/n).toLngLat().lat]}var Rr=function(e,r,n){var i=e.transform;return{u_matrix:Ur(e,r,n),u_ratio:1/pe(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},Fr=function(e,r,n){return t.extend(Rr(e,r,n),{u_image:0})},Br=function(e,r,n,i){var a=e.transform,o=jr(r,a);return{u_matrix:Ur(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/pe(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},Nr=function(e,r,n,i,a){var o=e.transform,s=e.lineAtlas,l=jr(r,o),c=\"round\"===n.layout.get(\"line-cap\"),u=s.getDash(i.from,c),f=s.getDash(i.to,c),h=u.width*a.fromScale,p=f.width*a.toScale;return t.extend(Rr(e,r,n),{u_patternscale_a:[l/h,-u.height/2],u_patternscale_b:[l/p,-f.height/2],u_sdfgamma:s.width/(256*Math.min(h,p)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:u.y,u_tex_y_b:f.y,u_mix:a.t})};function jr(t,e){return 1/pe(t,1,e.tileZoom)}function Ur(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var Vr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get(\"raster-brightness-min\"),u_brightness_high:i.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=i.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get(\"raster-contrast\"),a>0?1/(1-a):1+a),u_spin_weights:qr(i.paint.get(\"raster-hue-rotate\"))};var a,o};function qr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Hr,Gr=function(t,e,r,n,i,a,o,s,l,c){var u=i.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:u.cameraToCenterDistance,u_pitch:u.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:u.width/u.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:c,u_texture:0}},Yr=function(e,r,n,i,a,o,s,l,c,u,f){var h=a.transform;return t.extend(Gr(e,r,n,i,a,o,s,l,c,u),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},Wr=function(e,r,n,i,a,o,s,l,c,u){return t.extend(Yr(e,r,n,i,a,o,s,l,!0,c,!0),{u_texsize_icon:u,u_texture_icon:1})},Xr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},Zr=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,c=Math.pow(2,n.tileID.overscaledZ),u=n.tileSize*Math.pow(2,r.transform.tileZoom)/c,f=u*(n.tileID.canonical.x+n.tileID.wrap*c),h=u*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/pe(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},Jr={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_maxzoom:new t.Uniform1f(e,r.u_maxzoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function Kr(e,r,n,i,a,o,s){for(var l=e.context,c=l.gl,u=e.useProgram(\"collisionBox\"),f=[],h=0,p=0,d=0;d<i.length;d++){var g=i[d],m=r.getTile(g),v=m.getBucket(n);if(v){var y=g.posMatrix;0===a[0]&&0===a[1]||(y=e.translatePosMatrix(g.posMatrix,m,a,o));var x=s?v.textCollisionBox:v.iconCollisionBox,b=v.collisionCircleArray;if(b.length>0){var _=t.create(),w=y;t.mul(_,v.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,v.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&u.draw(l,c.LINES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,Cr(y,e.transform,m),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram(\"collisionCircle\"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var A=0,M=0,S=f;M<S.length;M+=1)for(var E=S[M],L=0;L<E.circleArray.length/4;L++){var C=4*L,P=E.circleArray[C+0],I=E.circleArray[C+1],O=E.circleArray[C+2],z=E.circleArray[C+3];k.emplace(A++,P,I,O,z,0),k.emplace(A++,P,I,O,z,1),k.emplace(A++,P,I,O,z,2),k.emplace(A++,P,I,O,z,3)}(!Hr||Hr.length<2*h)&&(Hr=function(e){var r=2*e,n=new t.StructArrayLayout3ui6;n.resize(r),n._trim();for(var i=0;i<r;i++){var a=6*i;n.uint16[a+0]=4*i+0,n.uint16[a+1]=4*i+1,n.uint16[a+2]=4*i+2,n.uint16[a+3]=4*i+2,n.uint16[a+4]=4*i+3,n.uint16[a+5]=4*i+0}return n}(h));for(var D=l.createIndexBuffer(Hr,!0),R=l.createVertexBuffer(k,t.collisionCircleLayout.members,!0),F=0,B=f;F<B.length;F+=1){var N=B[F],j=Pr(N.transform,N.invTransform,e.transform);T.draw(l,c.TRIANGLES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,j,n.id,R,D,t.SegmentVector.simpleSegment(0,2*N.circleOffset,N.circleArray.length,N.circleArray.length/2),null,e.transform.zoom,null,null,null)}R.destroy(),D.destroy()}}var Qr=t.identity(new Float32Array(16));function $r(e,r,n,i,a,o){var s=t.getAnchorAlignment(e),l=-(s.horizontalAlign-.5)*r,c=-(s.verticalAlign-.5)*n,u=t.evaluateVariableOffset(e,i);return new t.Point((l/a+u[0])*o,(c/a+u[1])*o)}function tn(e,r,n,i,a,o,s,l,c,u,f){var h=e.text.placedSymbolArray,p=e.text.dynamicLayoutVertexArray,d=e.icon.dynamicLayoutVertexArray,g={};p.clear();for(var m=0;m<h.length;m++){var v=h.get(m),y=e.allowVerticalPlacement&&!v.placedOrientation,x=v.hidden||!v.crossTileID||y?null:i[v.crossTileID];if(x){var b=new t.Point(v.anchorX,v.anchorY),_=te(b,n?l:s),w=ee(o.cameraToCenterDistance,_.signedDistanceFromCamera),T=a.evaluateSizeForFeature(e.textSizeData,u,v)*w/t.ONE_EM;n&&(T*=e.tilePixelRatio/c);for(var k=x.width,A=x.height,M=$r(x.anchor,k,A,x.textOffset,x.textBoxScale,T),S=n?te(b.add(M),s).point:_.point.add(r?M.rotate(-o.angle):M),E=e.allowVerticalPlacement&&v.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,L=0;L<v.numGlyphs;L++)t.addDynamicAttributes(p,S,E);f&&v.associatedIconIndex>=0&&(g[v.associatedIconIndex]={shiftedAnchor:S,angle:E})}else ue(v.numGlyphs,p)}if(f){d.clear();for(var C=e.icon.placedSymbolArray,P=0;P<C.length;P++){var I=C.get(P);if(I.hidden)ue(I.numGlyphs,d);else{var O=g[P];if(O)for(var z=0;z<I.numGlyphs;z++)t.addDynamicAttributes(d,O.shiftedAnchor,O.angle);else ue(I.numGlyphs,d)}}e.icon.dynamicLayoutVertexBuffer.updateData(d)}e.text.dynamicLayoutVertexBuffer.updateData(p)}function en(t,e,r){return r.iconsInText&&e?\"symbolTextAndIcon\":t?\"symbolSDF\":\"symbolIcon\"}function rn(e,r,n,i,a,o,s,l,c,u,f,h){for(var p=e.context,d=p.gl,g=e.transform,m=\"map\"===l,v=\"map\"===c,y=m&&\"point\"!==n.layout.get(\"symbol-placement\"),x=m&&!v&&!y,b=void 0!==n.layout.get(\"symbol-sort-key\").constantOr(1),_=e.depthModeForSublayer(0,At.ReadOnly),w=n.layout.get(\"text-variable-anchor\"),T=[],k=0,A=i;k<A.length;k+=1){var M=A[k],S=r.getTile(M),E=S.getBucket(n);if(E){var L=a?E.text:E.icon;if(L&&L.segments.get().length){var C=L.programConfigurations.get(n.id),P=a||E.sdfIcons,I=a?E.textSizeData:E.iconSizeData,O=v||0!==g.pitch,z=e.useProgram(en(P,a,E),C),D=t.evaluateSizeForZoom(I,g.zoom),R=void 0,F=[0,0],B=void 0,N=void 0,j=null,U=void 0;if(a){if(B=S.glyphAtlasTexture,N=d.LINEAR,R=S.glyphAtlasTexture.size,E.iconsInText){F=S.imageAtlasTexture.size,j=S.imageAtlasTexture;var V=\"composite\"===I.kind||\"camera\"===I.kind;U=O||e.options.rotating||e.options.zooming||V?d.LINEAR:d.NEAREST}}else{var q=1!==n.layout.get(\"icon-size\").constantOr(0)||E.iconsNeedLinear;B=S.imageAtlasTexture,N=P||e.options.rotating||e.options.zooming||q||O?d.LINEAR:d.NEAREST,R=S.imageAtlasTexture.size}var H=pe(S,1,e.transform.zoom),G=Qt(M.posMatrix,v,m,e.transform,H),Y=$t(M.posMatrix,v,m,e.transform,H),W=w&&E.hasTextData(),X=\"none\"!==n.layout.get(\"icon-text-fit\")&&W&&E.hasIconData();y&&ne(E,M.posMatrix,e,a,G,Y,v,u);var Z=e.translatePosMatrix(M.posMatrix,S,o,s),J=y||a&&w||X?Qr:G,K=e.translatePosMatrix(Y,S,o,s,!0),Q=P&&0!==n.paint.get(a?\"text-halo-width\":\"icon-halo-width\").constantOr(1),$={program:z,buffers:L,uniformValues:P?E.iconsInText?Wr(I.kind,D,x,v,e,Z,J,K,R,F):Yr(I.kind,D,x,v,e,Z,J,K,a,R,!0):Gr(I.kind,D,x,v,e,Z,J,K,a,R),atlasTexture:B,atlasTextureIcon:j,atlasInterpolation:N,atlasInterpolationIcon:U,isSDF:P,hasHalo:Q};if(b)for(var tt=0,et=L.segments.get();tt<et.length;tt+=1){var rt=et[tt];T.push({segments:new t.SegmentVector([rt]),sortKey:rt.sortKey,state:$})}else T.push({segments:L.segments,sortKey:0,state:$})}}}b&&T.sort((function(t,e){return t.sortKey-e.sortKey}));for(var nt=0,it=T;nt<it.length;nt+=1){var at=it[nt],ot=at.state;if(p.activeTexture.set(d.TEXTURE0),ot.atlasTexture.bind(ot.atlasInterpolation,d.CLAMP_TO_EDGE),ot.atlasTextureIcon&&(p.activeTexture.set(d.TEXTURE1),ot.atlasTextureIcon&&ot.atlasTextureIcon.bind(ot.atlasInterpolationIcon,d.CLAMP_TO_EDGE)),ot.isSDF){var st=ot.uniformValues;ot.hasHalo&&(st.u_is_halo=1,nn(ot.buffers,at.segments,n,e,ot.program,_,f,h,st)),st.u_is_halo=0}nn(ot.buffers,at.segments,n,e,ot.program,_,f,h,ot.uniformValues)}}function nn(t,e,r,n,i,a,o,s,l){var c=n.context,u=c.gl;i.draw(c,u.TRIANGLES,a,o,s,Et.disabled,l,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function an(t,e,r,n,i,a,o){var s,l,c,u,f,h=t.context.gl,p=r.paint.get(\"fill-pattern\"),d=p&&p.constantOr(1),g=r.getCrossfadeParameters();o?(l=d&&!r.getPaintProperty(\"fill-outline-color\")?\"fillOutlinePattern\":\"fillOutline\",s=h.LINES):(l=d?\"fillPattern\":\"fill\",s=h.TRIANGLES);for(var m=0,v=n;m<v.length;m+=1){var y=v[m],x=e.getTile(y);if(!d||x.patternsLoaded()){var b=x.getBucket(r);if(b){var _=b.programConfigurations.get(r.id),w=t.useProgram(l,_);d&&(t.context.activeTexture.set(h.TEXTURE0),x.imageAtlasTexture.bind(h.LINEAR,h.CLAMP_TO_EDGE),_.updatePaintBuffers(g));var T=p.constantOr(null);if(T&&x.imageAtlas){var k=x.imageAtlas,A=k.patternPositions[T.to.toString()],M=k.patternPositions[T.from.toString()];A&&M&&_.setConstantPatternPositions(A,M)}var S=t.translatePosMatrix(y.posMatrix,x,r.paint.get(\"fill-translate\"),r.paint.get(\"fill-translate-anchor\"));if(o){u=b.indexBuffer2,f=b.segments2;var E=[h.drawingBufferWidth,h.drawingBufferHeight];c=\"fillOutlinePattern\"===l&&d?Er(S,t,g,x,E):Sr(S,E)}else u=b.indexBuffer,f=b.segments,c=d?Mr(S,t,g,x):Ar(S);w.draw(t.context,s,i,t.stencilModeForClipping(y),a,Et.disabled,c,r.id,b.layoutVertexBuffer,u,f,r.paint,t.transform.zoom,_)}}}}function on(t,e,r,n,i,a,o){for(var s=t.context,l=s.gl,c=r.paint.get(\"fill-extrusion-pattern\"),u=c.constantOr(1),f=r.getCrossfadeParameters(),h=r.paint.get(\"fill-extrusion-opacity\"),p=0,d=n;p<d.length;p+=1){var g=d[p],m=e.getTile(g),v=m.getBucket(r);if(v){var y=v.programConfigurations.get(r.id),x=t.useProgram(u?\"fillExtrusionPattern\":\"fillExtrusion\",y);u&&(t.context.activeTexture.set(l.TEXTURE0),m.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),y.updatePaintBuffers(f));var b=c.constantOr(null);if(b&&m.imageAtlas){var _=m.imageAtlas,w=_.patternPositions[b.to.toString()],T=_.patternPositions[b.from.toString()];w&&T&&y.setConstantPatternPositions(w,T)}var k=t.translatePosMatrix(g.posMatrix,m,r.paint.get(\"fill-extrusion-translate\"),r.paint.get(\"fill-extrusion-translate-anchor\")),A=r.paint.get(\"fill-extrusion-vertical-gradient\"),M=u?kr(k,t,A,h,g,f,m):Tr(k,t,A,h);x.draw(s,s.gl.TRIANGLES,i,a,o,Et.backCCW,M,r.id,v.layoutVertexBuffer,v.indexBuffer,v.segments,r.paint,t.transform.zoom,y)}}}function sn(t,e,r,n,i,a){var o=t.context,s=o.gl,l=e.fbo;if(l){var c=t.useProgram(\"hillshade\");o.activeTexture.set(s.TEXTURE0),s.bindTexture(s.TEXTURE_2D,l.colorAttachment.get());var u=function(t,e,r){var n=r.paint.get(\"hillshade-shadow-color\"),i=r.paint.get(\"hillshade-highlight-color\"),a=r.paint.get(\"hillshade-accent-color\"),o=r.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===r.paint.get(\"hillshade-illumination-anchor\")&&(o-=t.transform.angle);var s=!t.options.moving;return{u_matrix:t.transform.calculatePosMatrix(e.tileID.toUnwrapped(),s),u_image:0,u_latrange:Dr(t,e.tileID),u_light:[r.paint.get(\"hillshade-exaggeration\"),o],u_shadow:n,u_highlight:i,u_accent:a}}(t,e,r);c.draw(o,s.TRIANGLES,n,i,a,Et.disabled,u,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}}function ln(e,r,n,i,a,o,s){var l=e.context,c=l.gl,u=r.dem;if(u&&u.data){var f=u.dim,h=u.stride,p=u.getPixels();if(l.activeTexture.set(c.TEXTURE1),l.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(h),r.demTexture){var d=r.demTexture;d.update(p,{premultiply:!1}),d.bind(c.NEAREST,c.CLAMP_TO_EDGE)}else r.demTexture=new t.Texture(l,p,c.RGBA,{premultiply:!1}),r.demTexture.bind(c.NEAREST,c.CLAMP_TO_EDGE);l.activeTexture.set(c.TEXTURE0);var g=r.fbo;if(!g){var m=new t.Texture(l,{width:f,height:f,data:null},c.RGBA);m.bind(c.LINEAR,c.CLAMP_TO_EDGE),(g=r.fbo=l.createFramebuffer(f,f,!0)).colorAttachment.set(m.texture)}l.bindFramebuffer.set(g.framebuffer),l.viewport.set([0,0,f,f]),e.useProgram(\"hillshadePrepare\").draw(l,c.TRIANGLES,a,o,s,Et.disabled,function(e,r,n){var i=r.stride,a=t.create();return t.ortho(a,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(a,a,[0,-t.EXTENT,0]),{u_matrix:a,u_image:1,u_dimension:[i,i],u_zoom:e.overscaledZ,u_maxzoom:n,u_unpack:r.getUnpackVector()}}(r.tileID,u,i),n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function cn(e,r,n,i,a){var o=i.paint.get(\"raster-fade-duration\");if(o>0){var s=t.browser.now(),l=(s-e.timeAdded)/o,c=r?(s-r.timeAdded)/o:-1,u=n.getSource(),f=a.coveringZoomLevel({tileSize:u.tileSize,roundZoom:u.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-c,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var un=new t.Color(1,0,0,1),fn=new t.Color(0,1,0,1),hn=new t.Color(0,0,1,1),pn=new t.Color(1,0,1,1),dn=new t.Color(0,1,1,1);function gn(t){var e=t.transform.padding;mn(t,t.transform.height-(e.top||0),3,un),mn(t,e.bottom||0,3,fn),vn(t,e.left||0,3,hn),vn(t,t.transform.width-(e.right||0),3,pn);var r=t.transform.centerPoint;!function(t,e,r,n){yn(t,e-1,r-10,2,20,n),yn(t,e-10,r-1,20,2,n)}(t,r.x,t.transform.height-r.y,dn)}function mn(t,e,r,n){yn(t,0,e+r/2,t.transform.width,r,n)}function vn(t,e,r,n){yn(t,e-r/2,0,r,t.transform.height,n)}function yn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function xn(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=At.disabled,c=Mt.disabled,u=e.colorModeForRenderPass();i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,c,u,Et.disabled,Ir(o,t.Color.red),\"$debug\",e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var f=r.getTileByID(n.key).latestRawTileData,h=f&&f.byteLength||0,p=Math.floor(h/1024),d=r.getTile(n).tileSize,g=512/Math.min(d,512)*(n.overscaledZ/e.transform.zoom)*.5,m=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(m+=\" => \"+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext(\"2d\");i.clearRect(0,0,r.width,r.height),i.shadowColor=\"white\",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle=\"white\",i.textBaseline=\"top\",i.font=\"bold 36px Open Sans, sans-serif\",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,m+\" \"+p+\"kb\"),s.draw(i,a.TRIANGLES,l,c,St.alphaBlended,Et.disabled,Ir(o,t.Color.transparent,g),\"$debug\",e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var bn={symbol:function(e,r,n,i,a){if(\"translucent\"===e.renderPass){var o=Mt.disabled,s=e.colorModeForRenderPass();n.layout.get(\"text-variable-anchor\")&&function(e,r,n,i,a,o,s){for(var l=r.transform,c=\"map\"===a,u=\"map\"===o,f=0,h=e;f<h.length;f+=1){var p=h[f],d=i.getTile(p),g=d.getBucket(n);if(g&&g.text&&g.text.segments.get().length){var m=g.textSizeData,v=t.evaluateSizeForZoom(m,l.zoom),y=pe(d,1,r.transform.zoom),x=Qt(p.posMatrix,u,c,r.transform,y),b=\"none\"!==n.layout.get(\"icon-text-fit\")&&g.hasIconData();if(v){var _=Math.pow(2,l.zoom-d.tileID.overscaledZ);tn(g,c,u,s,t.symbolSize,l,x,p.posMatrix,_,v,b)}}}}(i,e,n,r,n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),a),0!==n.paint.get(\"icon-opacity\").constantOr(1)&&rn(e,r,n,i,!1,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),n.layout.get(\"icon-rotation-alignment\"),n.layout.get(\"icon-pitch-alignment\"),n.layout.get(\"icon-keep-upright\"),o,s),0!==n.paint.get(\"text-opacity\").constantOr(1)&&rn(e,r,n,i,!0,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),n.layout.get(\"text-keep-upright\"),o,s),r.map.showCollisionBoxes&&(Kr(e,r,n,i,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),!0),Kr(e,r,n,i,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),!1))}},circle:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"circle-opacity\"),o=n.paint.get(\"circle-stroke-width\"),s=n.paint.get(\"circle-stroke-opacity\"),l=void 0!==n.layout.get(\"circle-sort-key\").constantOr(1);if(0!==a.constantOr(1)||0!==o.constantOr(1)&&0!==s.constantOr(1)){for(var c=e.context,u=c.gl,f=e.depthModeForSublayer(0,At.ReadOnly),h=Mt.disabled,p=e.colorModeForRenderPass(),d=[],g=0;g<i.length;g++){var m=i[g],v=r.getTile(m),y=v.getBucket(n);if(y){var x=y.programConfigurations.get(n.id),b={programConfiguration:x,program:e.useProgram(\"circle\",x),layoutVertexBuffer:y.layoutVertexBuffer,indexBuffer:y.indexBuffer,uniformValues:Lr(e,m,v,n)};if(l)for(var _=0,w=y.segments.get();_<w.length;_+=1){var T=w[_];d.push({segments:new t.SegmentVector([T]),sortKey:T.sortKey,state:b})}else d.push({segments:y.segments,sortKey:0,state:b})}}l&&d.sort((function(t,e){return t.sortKey-e.sortKey}));for(var k=0,A=d;k<A.length;k+=1){var M=A[k],S=M.state,E=S.programConfiguration,L=S.program,C=S.layoutVertexBuffer,P=S.indexBuffer,I=S.uniformValues,O=M.segments;L.draw(c,u.TRIANGLES,f,h,p,Et.disabled,I,n.id,C,P,O,n.paint,e.transform.zoom,E)}}}},heatmap:function(e,r,n,i){if(0!==n.paint.get(\"heatmap-opacity\"))if(\"offscreen\"===e.renderPass){var a=e.context,o=a.gl,s=Mt.disabled,l=new St([o.ONE,o.ONE],t.Color.transparent,[!0,!0,!0,!0]);!function(t,e,r){var n=t.gl;t.activeTexture.set(n.TEXTURE1),t.viewport.set([0,0,e.width/4,e.height/4]);var i=r.heatmapFbo;if(i)n.bindTexture(n.TEXTURE_2D,i.colorAttachment.get()),t.bindFramebuffer.set(i.framebuffer);else{var a=n.createTexture();n.bindTexture(n.TEXTURE_2D,a),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),i=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4,!1),function(t,e,r,n){var i=t.gl,a=t.extRenderToTextureHalfFloat?t.extTextureHalfFloat.HALF_FLOAT_OES:i.UNSIGNED_BYTE;i.texImage2D(i.TEXTURE_2D,0,i.RGBA,e.width/4,e.height/4,0,i.RGBA,a,null),n.colorAttachment.set(r)}(t,e,a,i)}}(a,e,n),a.clear({color:t.Color.transparent});for(var c=0;c<i.length;c++){var u=i[c];if(!r.hasRenderableParent(u)){var f=r.getTile(u),h=f.getBucket(n);if(h){var p=h.programConfigurations.get(n.id),d=e.useProgram(\"heatmap\",p),g=e.transform.zoom;d.draw(a,o.TRIANGLES,At.disabled,s,l,Et.disabled,zr(u.posMatrix,f,g,n.paint.get(\"heatmap-intensity\")),n.id,h.layoutVertexBuffer,h.indexBuffer,h.segments,n.paint,e.transform.zoom,p)}}}a.viewport.set([0,0,e.width,e.height])}else\"translucent\"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,i=n.gl,a=r.heatmapFbo;if(!a)return;n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,a.colorAttachment.get()),n.activeTexture.set(i.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new t.Texture(n,r.colorRamp,i.RGBA));o.bind(i.LINEAR,i.CLAMP_TO_EDGE),e.useProgram(\"heatmapTexture\").draw(n,i.TRIANGLES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:n,u_color_ramp:i,u_opacity:r.paint.get(\"heatmap-opacity\")}}(e,r,0,1),r.id,e.viewportBuffer,e.quadTriangleIndexBuffer,e.viewportSegments,r.paint,e.transform.zoom)}(e,n))},line:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"line-opacity\"),o=n.paint.get(\"line-width\");if(0!==a.constantOr(1)&&0!==o.constantOr(1)){var s=e.depthModeForSublayer(0,At.ReadOnly),l=e.colorModeForRenderPass(),c=n.paint.get(\"line-dasharray\"),u=n.paint.get(\"line-pattern\"),f=u.constantOr(1),h=n.paint.get(\"line-gradient\"),p=n.getCrossfadeParameters(),d=f?\"linePattern\":c?\"lineSDF\":h?\"lineGradient\":\"line\",g=e.context,m=g.gl,v=!0;if(h){g.activeTexture.set(m.TEXTURE0);var y=n.gradientTexture;if(!n.gradient)return;y||(y=n.gradientTexture=new t.Texture(g,n.gradient,m.RGBA)),y.bind(m.LINEAR,m.CLAMP_TO_EDGE)}for(var x=0,b=i;x<b.length;x+=1){var _=b[x],w=r.getTile(_);if(!f||w.patternsLoaded()){var T=w.getBucket(n);if(T){var k=T.programConfigurations.get(n.id),A=e.context.program.get(),M=e.useProgram(d,k),S=v||M.program!==A,E=u.constantOr(null);if(E&&w.imageAtlas){var L=w.imageAtlas,C=L.patternPositions[E.to.toString()],P=L.patternPositions[E.from.toString()];C&&P&&k.setConstantPatternPositions(C,P)}var I=f?Br(e,w,n,p):c?Nr(e,w,n,c,p):h?Fr(e,w,n):Rr(e,w,n);f?(g.activeTexture.set(m.TEXTURE0),w.imageAtlasTexture.bind(m.LINEAR,m.CLAMP_TO_EDGE),k.updatePaintBuffers(p)):c&&(S||e.lineAtlas.dirty)&&(g.activeTexture.set(m.TEXTURE0),e.lineAtlas.bind(g)),M.draw(g,m.TRIANGLES,s,e.stencilModeForClipping(_),l,Et.disabled,I,n.id,T.layoutVertexBuffer,T.indexBuffer,T.segments,n.paint,e.transform.zoom,k),v=!1}}}}}},fill:function(e,r,n,i){var a=n.paint.get(\"fill-color\"),o=n.paint.get(\"fill-opacity\");if(0!==o.constantOr(1)){var s=e.colorModeForRenderPass(),l=n.paint.get(\"fill-pattern\"),c=e.opaquePassEnabledForLayer()&&!l.constantOr(1)&&1===a.constantOr(t.Color.transparent).a&&1===o.constantOr(0)?\"opaque\":\"translucent\";if(e.renderPass===c){var u=e.depthModeForSublayer(1,\"opaque\"===e.renderPass?At.ReadWrite:At.ReadOnly);an(e,r,n,i,u,s,!1)}if(\"translucent\"===e.renderPass&&n.paint.get(\"fill-antialias\")){var f=e.depthModeForSublayer(n.getPaintProperty(\"fill-outline-color\")?2:0,At.ReadOnly);an(e,r,n,i,f,s,!0)}}},\"fill-extrusion\":function(t,e,r,n){var i=r.paint.get(\"fill-extrusion-opacity\");if(0!==i&&\"translucent\"===t.renderPass){var a=new At(t.context.gl.LEQUAL,At.ReadWrite,t.depthRangeFor3D);if(1!==i||r.paint.get(\"fill-extrusion-pattern\").constantOr(1))on(t,e,r,n,a,Mt.disabled,St.disabled),on(t,e,r,n,a,t.stencilModeFor3D(),t.colorModeForRenderPass());else{var o=t.colorModeForRenderPass();on(t,e,r,n,a,Mt.disabled,o)}}},hillshade:function(t,e,r,n){if(\"offscreen\"===t.renderPass||\"translucent\"===t.renderPass){for(var i=t.context,a=e.getSource().maxzoom,o=t.depthModeForSublayer(0,At.ReadOnly),s=t.colorModeForRenderPass(),l=\"translucent\"===t.renderPass?t.stencilConfigForOverlap(n):[{},n],c=l[0],u=0,f=l[1];u<f.length;u+=1){var h=f[u],p=e.getTile(h);p.needsHillshadePrepare&&\"offscreen\"===t.renderPass?ln(t,p,r,a,o,Mt.disabled,s):\"translucent\"===t.renderPass&&sn(t,p,r,o,c[h.overscaledZ],s)}i.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if(\"translucent\"===t.renderPass&&0!==r.paint.get(\"raster-opacity\")&&n.length)for(var i=t.context,a=i.gl,o=e.getSource(),s=t.useProgram(\"raster\"),l=t.colorModeForRenderPass(),c=o instanceof I?[{},n]:t.stencilConfigForOverlap(n),u=c[0],f=c[1],h=f[f.length-1].overscaledZ,p=!t.options.moving,d=0,g=f;d<g.length;d+=1){var m=g[d],v=t.depthModeForSublayer(m.overscaledZ-h,1===r.paint.get(\"raster-opacity\")?At.ReadWrite:At.ReadOnly,a.LESS),y=e.getTile(m),x=t.transform.calculatePosMatrix(m.toUnwrapped(),p);y.registerFadeDuration(r.paint.get(\"raster-fade-duration\"));var b=e.findLoadedParent(m,0),_=cn(y,b,e,r,t.transform),w=void 0,T=void 0,k=\"nearest\"===r.paint.get(\"raster-resampling\")?a.NEAREST:a.LINEAR;i.activeTexture.set(a.TEXTURE0),y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),i.activeTexture.set(a.TEXTURE1),b?(b.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),w=Math.pow(2,b.tileID.overscaledZ-y.tileID.overscaledZ),T=[y.tileID.canonical.x*w%1,y.tileID.canonical.y*w%1]):y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST);var A=Vr(x,T||[0,0],w||1,_,r);o instanceof I?s.draw(i,a.TRIANGLES,v,Mt.disabled,l,Et.disabled,A,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):s.draw(i,a.TRIANGLES,v,u[m.overscaledZ],l,Et.disabled,A,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}},background:function(t,e,r){var n=r.paint.get(\"background-color\"),i=r.paint.get(\"background-opacity\");if(0!==i){var a=t.context,o=a.gl,s=t.transform,l=s.tileSize,c=r.paint.get(\"background-pattern\");if(!t.isPatternMissing(c)){var u=!c&&1===n.a&&1===i&&t.opaquePassEnabledForLayer()?\"opaque\":\"translucent\";if(t.renderPass===u){var f=Mt.disabled,h=t.depthModeForSublayer(0,\"opaque\"===u?At.ReadWrite:At.ReadOnly),p=t.colorModeForRenderPass(),d=t.useProgram(c?\"backgroundPattern\":\"background\"),g=s.coveringTiles({tileSize:l});c&&(a.activeTexture.set(o.TEXTURE0),t.imageManager.bind(t.context));for(var m=r.getCrossfadeParameters(),v=0,y=g;v<y.length;v+=1){var x=y[v],b=t.transform.calculatePosMatrix(x.toUnwrapped()),_=c?Zr(b,i,t,c,{tileID:x,tileSize:l},m):Xr(b,i,n);d.draw(a,o.TRIANGLES,h,f,p,Et.disabled,_,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)xn(t,e,r[n])},custom:function(t,e,r){var n=t.context,i=r.implementation;if(\"offscreen\"===t.renderPass){var a=i.prerender;a&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),a.call(i,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if(\"translucent\"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(Mt.disabled);var o=\"3d\"===i.renderingMode?new At(t.context.gl.LEQUAL,At.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,At.ReadOnly);n.setDepthMode(o),i.render(n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}},_n=function(t,e){this.context=new Lt(t),this.transform=e,this._tileTextures={},this.setup(),this.numSublayers=Ct.maxUnderzooming+Ct.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Ne,this.gpuTimers={}};_n.prototype.resize=function(e,r){if(this.width=e*t.browser.devicePixelRatio,this.height=r*t.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var n=0,i=this.style._order;n<i.length;n+=1){var a=i[n];this.style._layers[a].resize()}},_n.prototype.setup=function(){var e=this.context,r=new t.StructArrayLayout2i4;r.emplaceBack(0,0),r.emplaceBack(t.EXTENT,0),r.emplaceBack(0,t.EXTENT),r.emplaceBack(t.EXTENT,t.EXTENT),this.tileExtentBuffer=e.createVertexBuffer(r,Ge.members),this.tileExtentSegments=t.SegmentVector.simpleSegment(0,0,4,2);var n=new t.StructArrayLayout2i4;n.emplaceBack(0,0),n.emplaceBack(t.EXTENT,0),n.emplaceBack(0,t.EXTENT),n.emplaceBack(t.EXTENT,t.EXTENT),this.debugBuffer=e.createVertexBuffer(n,Ge.members),this.debugSegments=t.SegmentVector.simpleSegment(0,0,4,5);var i=new t.StructArrayLayout4i8;i.emplaceBack(0,0,0,0),i.emplaceBack(t.EXTENT,0,t.EXTENT,0),i.emplaceBack(0,t.EXTENT,0,t.EXTENT),i.emplaceBack(t.EXTENT,t.EXTENT,t.EXTENT,t.EXTENT),this.rasterBoundsBuffer=e.createVertexBuffer(i,P.members),this.rasterBoundsSegments=t.SegmentVector.simpleSegment(0,0,4,2);var a=new t.StructArrayLayout2i4;a.emplaceBack(0,0),a.emplaceBack(1,0),a.emplaceBack(0,1),a.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(a,Ge.members),this.viewportSegments=t.SegmentVector.simpleSegment(0,0,4,2);var o=new t.StructArrayLayout1ui2;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=e.createIndexBuffer(o);var s=new t.StructArrayLayout3ui6;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=e.createIndexBuffer(s),this.emptyTexture=new t.Texture(e,{width:1,height:1,data:new Uint8Array([0,0,0,0])},e.gl.RGBA);var l=this.context.gl;this.stencilClearMode=new Mt({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)},_n.prototype.clearStencil=function(){var e=this.context,r=e.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var n=t.create();t.ortho(n,0,this.width,this.height,0,0,1),t.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram(\"clippingMask\").draw(e,r.TRIANGLES,At.disabled,this.stencilClearMode,St.disabled,Et.disabled,Or(n),\"$clipping\",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},_n.prototype._renderTileClippingMasks=function(t,e){if(this.currentStencilSource!==t.source&&t.isTileClipped()&&e&&e.length){this.currentStencilSource=t.source;var r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(St.disabled),r.setDepthMode(At.disabled);var i=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var a=0,o=e;a<o.length;a+=1){var s=o[a],l=this._tileClippingMaskIDs[s.key]=this.nextStencilID++;i.draw(r,n.TRIANGLES,At.disabled,new Mt({func:n.ALWAYS,mask:0},l,255,n.KEEP,n.KEEP,n.REPLACE),St.disabled,Et.disabled,Or(s.posMatrix),\"$clipping\",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},_n.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new Mt({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},_n.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new Mt({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},_n.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s<a;s++)o[s+i]=new Mt({func:r.GEQUAL,mask:255},s+this.nextStencilID,255,r.KEEP,r.KEEP,r.REPLACE);return this.nextStencilID+=a,[o,n]}return[(e={},e[i]=Mt.disabled,e),n]},_n.prototype.colorModeForRenderPass=function(){var e=this.context.gl;if(this._showOverdrawInspector){return new St([e.CONSTANT_COLOR,e.ONE],new t.Color(1/8,1/8,1/8,0),[!0,!0,!0,!0])}return\"opaque\"===this.renderPass?St.unblended:St.alphaBlended},_n.prototype.depthModeForSublayer=function(t,e,r){if(!this.opaquePassEnabledForLayer())return At.disabled;var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon;return new At(r||this.context.gl.LEQUAL,e,[n,n])},_n.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},_n.prototype.render=function(e,r){var n=this;this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(t.browser.now()),this.imageManager.beginFrame();var i=this.style._order,a=this.style.sourceCaches;for(var o in a){var s=a[o];s.used&&s.prepare(this.context)}var l,c,u={},f={},h={};for(var p in a){var d=a[p];u[p]=d.getVisibleCoordinates(),f[p]=u[p].slice().reverse(),h[p]=d.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(var g=0;g<i.length;g++){var m=i[g];if(this.style._layers[m].is3D()){this.opaquePassCutoff=g;break}}this.renderPass=\"offscreen\";for(var v=0,y=i;v<y.length;v+=1){var x=y[v],b=this.style._layers[x];if(b.hasOffscreenPass()&&!b.isHidden(this.transform.zoom)){var _=f[b.source];(\"custom\"===b.type||_.length)&&this.renderLayer(this,a[b.source],b,_)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.Color.black:t.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRangeFor3D=[0,1-(e._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass=\"opaque\",this.currentLayer=i.length-1;this.currentLayer>=0;this.currentLayer--){var w=this.style._layers[i[this.currentLayer]],T=a[w.source],k=u[w.source];this._renderTileClippingMasks(w,k),this.renderLayer(this,T,w,k)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer<i.length;this.currentLayer++){var A=this.style._layers[i[this.currentLayer]],M=a[A.source],S=(\"symbol\"===A.type?h:f)[A.source];this._renderTileClippingMasks(A,u[A.source]),this.renderLayer(this,M,A,S)}this.options.showTileBoundaries&&(t.values(this.style._layers).forEach((function(t){t.source&&!t.isHidden(n.transform.zoom)&&(t.source!==(c&&c.id)&&(c=n.style.sourceCaches[t.source]),(!l||l.getSource().maxzoom<c.getSource().maxzoom)&&(l=c))})),l&&bn.debug(this,l,l.getVisibleCoordinates()));this.options.showPadding&&gn(this),this.context.setDefault()},_n.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||\"custom\"===r.type||n.length)&&(this.id=r.id,this.gpuTimingStart(r),bn[r.type](t,e,r,n,this.style.placement.variableOffsets),this.gpuTimingEnd())},_n.prototype.gpuTimingStart=function(t){if(this.options.gpuTiming){var e=this.context.extTimerQuery,r=this.gpuTimers[t.id];r||(r=this.gpuTimers[t.id]={calls:0,cpuTime:0,query:e.createQueryEXT()}),r.calls++,e.beginQueryEXT(e.TIME_ELAPSED_EXT,r.query)}},_n.prototype.gpuTimingEnd=function(){if(this.options.gpuTiming){var t=this.context.extTimerQuery;t.endQueryEXT(t.TIME_ELAPSED_EXT)}},_n.prototype.collectGpuTimers=function(){var t=this.gpuTimers;return this.gpuTimers={},t},_n.prototype.queryGpuTimers=function(t){var e={};for(var r in t){var n=t[r],i=this.context.extTimerQuery,a=i.getQueryObjectEXT(n.query,i.QUERY_RESULT_EXT)/1e6;i.deleteQueryEXT(n.query),e[r]=a}return e},_n.prototype.translatePosMatrix=function(e,r,n,i,a){if(!n[0]&&!n[1])return e;var o=a?\"map\"===i?this.transform.angle:0:\"viewport\"===i?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var c=[a?n[0]:pe(r,n[0],this.transform.zoom),a?n[1]:pe(r,n[1],this.transform.zoom),0],u=new Float32Array(16);return t.translate(u,e,c),u},_n.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},_n.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},_n.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},_n.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e?e.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new _r(this.context,xr[t],e,Jr[t],this._showOverdrawInspector)),this.cache[r]},_n.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},_n.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},_n.prototype.initDebugOverlayCanvas=function(){if(null==this.debugOverlayCanvas){this.debugOverlayCanvas=t.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var e=this.context.gl;this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,e.RGBA)}},_n.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var wn=function(t,e){this.points=t,this.planes=e};wn.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new wn(a,o)};var Tn=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};Tn.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a<r.length;a++)n[a]=r[a]?this.min[a]:this.center[a],i[a]=r[a]?this.center[a]:this.max[a];return i[2]=this.max[2],new Tn(n,i)},Tn.prototype.distanceX=function(t){return Math.max(Math.min(this.max[0],t[0]),this.min[0])-t[0]},Tn.prototype.distanceY=function(t){return Math.max(Math.min(this.max[1],t[1]),this.min[1])-t[1]},Tn.prototype.intersects=function(e){for(var r=[[this.min[0],this.min[1],0,1],[this.max[0],this.min[1],0,1],[this.max[0],this.max[1],0,1],[this.min[0],this.max[1],0,1]],n=!0,i=0;i<e.planes.length;i++){for(var a=e.planes[i],o=0,s=0;s<r.length;s++)o+=t.dot$1(a,r[s])>=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var c=Number.MAX_VALUE,u=-Number.MAX_VALUE,f=0;f<e.points.length;f++){var h=e.points[f][l]-this.min[l];c=Math.min(c,h),u=Math.max(u,h)}if(u<0||c>this.max[l]-this.min[l])return 0}return 1};var kn=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=t,this.bottom=e,this.left=r,this.right=n};kn.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},kn.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},kn.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},kn.prototype.clone=function(){return new kn(this.top,this.bottom,this.left,this.right)},kn.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var An=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new kn,this._posMatrixCache={},this._alignedPosMatrixCache={}},Mn={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};An.prototype.clone=function(){var t=new An(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},Mn.minZoom.get=function(){return this._minZoom},Mn.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},Mn.maxZoom.get=function(){return this._maxZoom},Mn.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},Mn.minPitch.get=function(){return this._minPitch},Mn.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},Mn.maxPitch.get=function(){return this._maxPitch},Mn.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},Mn.renderWorldCopies.get=function(){return this._renderWorldCopies},Mn.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},Mn.worldSize.get=function(){return this.tileSize*this.scale},Mn.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},Mn.size.get=function(){return new t.Point(this.width,this.height)},Mn.bearing.get=function(){return-this.angle/Math.PI*180},Mn.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},Mn.pitch.get=function(){return this._pitch/Math.PI*180},Mn.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},Mn.fov.get=function(){return this._fov/Math.PI*180},Mn.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},Mn.zoom.get=function(){return this._zoom},Mn.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},Mn.center.get=function(){return this._center},Mn.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},Mn.padding.get=function(){return this._edgeInsets.toJSON()},Mn.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},Mn.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},An.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},An.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},An.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},An.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),c=s-1;c<=l+1;c++)0!==c&&r.push(new t.UnwrappedTileID(c,e));return r},An.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=wn.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var c=function(t){return{aabb:new Tn([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},u=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)u.push(c(-d)),u.push(c(d));for(u.push(c(0));u.length>0;){var g=u.pop(),m=g.x,v=g.y,y=g.fullyVisible;if(!y){var x=g.aabb.intersects(s);if(0===x)continue;y=2===x}var b=g.aabb.distanceX(o),_=g.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_)),T=3+(1<<h-g.zoom)-2;if(g.zoom===h||w>T&&g.zoom>=l)f.push({tileID:new t.OverscaledTileID(g.zoom===h?p:g.zoom,g.wrap,g.zoom,m,v),distanceSq:t.sqrLen([o[0]-.5-m,o[1]-.5-v])});else for(var k=0;k<4;k++){var A=(m<<1)+k%2,M=(v<<1)+(k>>1);u.push({aabb:g.aabb.quadrant(k),zoom:g.zoom+1,x:A,y:M,wrap:g.wrap,fullyVisible:y})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},An.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},Mn.unmodified.get=function(){return this._unmodified},An.prototype.zoomScale=function(t){return Math.pow(2,t)},An.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},An.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},An.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},Mn.point.get=function(){return this.project(this.center)},An.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},An.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},An.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},An.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},An.prototype.coordinateLocation=function(t){return t.toLngLat()},An.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[0]/i,s=n[0]/a,l=r[1]/i,c=n[1]/a,u=r[2]/i,f=n[2]/a,h=u===f?0:(0-u)/(f-u);return new t.MercatorCoordinate(t.number(o,s,h)/this.worldSize,t.number(l,c,h)/this.worldSize)},An.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},An.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},An.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},An.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},An.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},An.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},An.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,c=this.size,u=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-a<c.y?c.y/(o-a):0}if(this.lngRange){var h=this.lngRange;s=t.mercatorXfromLng(h[0])*this.worldSize,r=(l=t.mercatorXfromLng(h[1])*this.worldSize)-s<c.x?c.x/(l-s):0}var p=this.point,d=Math.max(r||0,e||0);if(d)return this.center=this.unproject(new t.Point(r?(l+s)/2:p.x,e?(o+a)/2:p.y)),this.zoom+=this.scaleZoom(d),this._unmodified=u,void(this._constraining=!1);if(this.latRange){var g=p.y,m=c.y/2;g-m<a&&(i=a+m),g+m>o&&(i=o-m)}if(this.lngRange){var v=p.x,y=c.x/2;v-y<s&&(n=s+y),v+y>l&&(n=l-y)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=u,this._constraining=!1}},An.prototype._calcMatrices=function(){if(this.height){var e=this._fov/2,r=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(e)*this.height;var n=Math.PI/2+this._pitch,i=this._fov*(.5+r.y/this.height),a=Math.sin(i)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-n-i,.01,Math.PI-.01)),o=this.point,s=o.x,l=o.y,c=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),u=this.height/50,f=new Float64Array(16);t.perspective(f,this._fov,this.width/this.height,u,c),f[8]=2*-r.x/this.width,f[9]=2*r.y/this.height,t.scale(f,f,[1,-1,1]),t.translate(f,f,[0,0,-this.cameraToCenterDistance]),t.rotateX(f,f,this._pitch),t.rotateZ(f,f,this.angle),t.translate(f,f,[-s,-l,0]),this.mercatorMatrix=t.scale([],f,[this.worldSize,this.worldSize,this.worldSize]),t.scale(f,f,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=f,this.invProjMatrix=t.invert([],this.projMatrix);var h=this.width%2/2,p=this.height%2/2,d=Math.cos(this.angle),g=Math.sin(this.angle),m=s-Math.round(s)+d*h+g*p,v=l-Math.round(l)+d*p+g*h,y=new Float64Array(f);if(t.translate(y,y,[m>.5?m-1:m,v>.5?v-1:v,0]),this.alignedProjMatrix=y,f=t.create(),t.scale(f,f,[this.width/2,-this.height/2,1]),t.translate(f,f,[1,-1,0]),this.labelPlaneMatrix=f,f=t.create(),t.scale(f,f,[1,-1,1]),t.translate(f,f,[-1,-1,0]),t.scale(f,f,[2/this.width,2/this.height,1]),this.glCoordMatrix=f,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(f=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=f,this._posMatrixCache={},this._alignedPosMatrixCache={}}},An.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},An.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},An.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s<l.length;s+=1){var c=l[s];n=Math.min(n,c.x),i=Math.min(i,c.y),a=Math.max(a,c.x),o=Math.max(o,c.y)}return[new t.Point(n,i),new t.Point(a,i),new t.Point(a,o),new t.Point(n,o),new t.Point(n,i)]},Object.defineProperties(An.prototype,Mn);var Sn=function(e){var r,n,i,a,o;this._hashName=e&&encodeURIComponent(e),t.bindAll([\"_getCurrentHash\",\"_onHashChange\",\"_updateHash\"],this),this._updateHash=(r=this._updateHashUnthrottled.bind(this),n=300,i=!1,a=null,o=function(){a=null,i&&(r(),a=setTimeout(o,n),i=!1)},function(){return i=!0,a||o(),a})};Sn.prototype.addTo=function(e){return this._map=e,t.window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},Sn.prototype.remove=function(){return t.window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},Sn.prototype.getHashString=function(e){var r=this._map.getCenter(),n=Math.round(100*this._map.getZoom())/100,i=Math.ceil((n*Math.LN2+Math.log(512/360/.5))/Math.LN10),a=Math.pow(10,i),o=Math.round(r.lng*a)/a,s=Math.round(r.lat*a)/a,l=this._map.getBearing(),c=this._map.getPitch(),u=\"\";if(u+=e?\"/\"+o+\"/\"+s+\"/\"+n:n+\"/\"+s+\"/\"+o,(l||c)&&(u+=\"/\"+Math.round(10*l)/10),c&&(u+=\"/\"+Math.round(c)),this._hashName){var f=this._hashName,h=!1,p=t.window.location.hash.slice(1).split(\"&\").map((function(t){var e=t.split(\"=\")[0];return e===f?(h=!0,e+\"=\"+u):t})).filter((function(t){return t}));return h||p.push(f+\"=\"+u),\"#\"+p.join(\"&\")}return\"#\"+u},Sn.prototype._getCurrentHash=function(){var e,r=this,n=t.window.location.hash.replace(\"#\",\"\");return this._hashName?(n.split(\"&\").map((function(t){return t.split(\"=\")})).forEach((function(t){t[0]===r._hashName&&(e=t)})),(e&&e[1]||\"\").split(\"/\")):n.split(\"/\")},Sn.prototype._onHashChange=function(){var t=this._getCurrentHash();if(t.length>=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},Sn.prototype._updateHashUnthrottled=function(){var e=this.getHashString();try{t.window.history.replaceState(t.window.history.state,\"\",e)}catch(t){}};var En={linearity:.3,easing:t.bezier(0,0,.3,1)},Ln=t.extend({deceleration:2500,maxSpeed:1400},En),Cn=t.extend({deceleration:20,maxSpeed:1400},En),Pn=t.extend({deceleration:1e3,maxSpeed:360},En),In=t.extend({deceleration:1e3,maxSpeed:90},En),On=function(t){this._map=t,this.clear()};function zn(t,e){(!t.duration||t.duration<e.duration)&&(t.duration=e.duration,t.easing=e.easing)}function Dn(e,r,n){var i=n.maxSpeed,a=n.linearity,o=n.deceleration,s=t.clamp(e*a/(r/1e3),-i,i),l=Math.abs(s)/(o*a);return{easing:n.easing,duration:1e3*l,amount:s*(l/2)}}On.prototype.clear=function(){this._inertiaBuffer=[]},On.prototype.record=function(e){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:t.browser.now(),settings:e})},On.prototype._drainInertiaBuffer=function(){for(var e=this._inertiaBuffer,r=t.browser.now();e.length>0&&r-e[0].time>160;)e.shift()},On.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n<i.length;n+=1){var a=i[n].settings;r.zoom+=a.zoomDelta||0,r.bearing+=a.bearingDelta||0,r.pitch+=a.pitchDelta||0,a.panDelta&&r.pan._add(a.panDelta),a.around&&(r.around=a.around),a.pinchAround&&(r.pinchAround=a.pinchAround)}var o=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,s={};if(r.pan.mag()){var l=Dn(r.pan.mag(),o,t.extend({},Ln,e||{}));s.offset=r.pan.mult(l.amount/r.pan.mag()),s.center=this._map.transform.center,zn(s,l)}if(r.zoom){var c=Dn(r.zoom,o,Cn);s.zoom=this._map.transform.zoom+c.amount,zn(s,c)}if(r.bearing){var u=Dn(r.bearing,o,Pn);s.bearing=this._map.transform.bearing+t.clamp(u.amount,-179,179),zn(s,u)}if(r.pitch){var f=Dn(r.pitch,o,In);s.pitch=this._map.transform.pitch+f.amount,zn(s,f)}if(s.zoom||s.bearing){var h=void 0===r.pinchAround?r.around:r.pinchAround;s.around=h?this._map.unproject(h):this._map.getCenter()}return this.clear(),t.extend(s,{noMoveStart:!0})}};var Rn=function(e){function n(n,i,a,o){void 0===o&&(o={});var s=r.mousePos(i.getCanvasContainer(),a),l=i.unproject(s);e.call(this,n,t.extend({point:s,lngLat:l,originalEvent:a},o)),this._defaultPrevented=!1,this.target=i}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Fn=function(e){function n(n,i,a){var o=\"touchend\"===n?a.changedTouches:a.touches,s=r.touchPos(i.getCanvasContainer(),o),l=s.map((function(t){return i.unproject(t)})),c=s.reduce((function(t,e,r,n){return t.add(e.div(n.length))}),new t.Point(0,0)),u=i.unproject(c);e.call(this,n,{points:s,point:c,lngLats:l,lngLat:u,originalEvent:a}),this._defaultPrevented=!1}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Bn=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),Nn=function(t,e){this._map=t,this._clickTolerance=e.clickTolerance};Nn.prototype.reset=function(){delete this._mousedownPos},Nn.prototype.wheel=function(t){return this._firePreventable(new Bn(t.type,this._map,t))},Nn.prototype.mousedown=function(t,e){return this._mousedownPos=e,this._firePreventable(new Rn(t.type,this._map,t))},Nn.prototype.mouseup=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.click=function(t,e){this._mousedownPos&&this._mousedownPos.dist(e)>=this._clickTolerance||this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.dblclick=function(t){return this._firePreventable(new Rn(t.type,this._map,t))},Nn.prototype.mouseover=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.mouseout=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.touchstart=function(t){return this._firePreventable(new Fn(t.type,this._map,t))},Nn.prototype.touchmove=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype.touchend=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype.touchcancel=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},Nn.prototype.isEnabled=function(){return!0},Nn.prototype.isActive=function(){return!1},Nn.prototype.enable=function(){},Nn.prototype.disable=function(){};var jn=function(t){this._map=t};jn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},jn.prototype.mousemove=function(t){this._map.fire(new Rn(t.type,this._map,t))},jn.prototype.mousedown=function(){this._delayContextMenu=!0},jn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new Rn(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},jn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new Rn(t.type,this._map,t)),this._map.listens(\"contextmenu\")&&t.preventDefault()},jn.prototype.isEnabled=function(){return!0},jn.prototype.isActive=function(){return!1},jn.prototype.enable=function(){},jn.prototype.disable=function(){};var Un=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Vn(t,e){for(var r={},n=0;n<t.length;n++)r[t[n].identifier]=e[n];return r}Un.prototype.isEnabled=function(){return!!this._enabled},Un.prototype.isActive=function(){return!!this._active},Un.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Un.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Un.prototype.mousedown=function(t,e){this.isEnabled()&&t.shiftKey&&0===t.button&&(r.disableDrag(),this._startPos=this._lastPos=e,this._active=!0)},Un.prototype.mousemoveWindow=function(t,e){if(this._active){var n=e;if(!(this._lastPos.equals(n)||!this._box&&n.dist(this._startPos)<this._clickTolerance)){var i=this._startPos;this._lastPos=n,this._box||(this._box=r.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var a=Math.min(i.x,n.x),o=Math.max(i.x,n.x),s=Math.min(i.y,n.y),l=Math.max(i.y,n.y);r.setTransform(this._box,\"translate(\"+a+\"px,\"+s+\"px)\"),this._box.style.width=o-a+\"px\",this._box.style.height=l-s+\"px\"}}},Un.prototype.mouseupWindow=function(e,n){var i=this;if(this._active&&0===e.button){var a=this._startPos,o=n;if(this.reset(),r.suppressClick(),a.x!==o.x||a.y!==o.y)return this._map.fire(new t.Event(\"boxzoomend\",{originalEvent:e})),{cameraAnimation:function(t){return t.fitScreenCoordinates(a,o,i._map.getBearing(),{linear:!0})}};this._fireEvent(\"boxzoomcancel\",e)}},Un.prototype.keydown=function(t){this._active&&27===t.keyCode&&(this.reset(),this._fireEvent(\"boxzoomcancel\",t))},Un.prototype.reset=function(){this._active=!1,this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(r.remove(this._box),this._box=null),r.enableDrag(),delete this._startPos,delete this._lastPos},Un.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var qn=function(t){this.reset(),this.numTouches=t.numTouches};qn.prototype.reset=function(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1},qn.prototype.touchstart=function(e,r,n){(this.centroid||n.length>this.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n<i.length;n+=1){var a=i[n];r._add(a)}return r.div(e.length)}(r),this.touches=Vn(n,r)))},qn.prototype.touchmove=function(t,e,r){if(!this.aborted&&this.centroid){var n=Vn(r,e);for(var i in this.touches){var a=this.touches[i],o=n[i];(!o||o.dist(a)>30)&&(this.aborted=!0)}}},qn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Hn=function(t){this.singleTap=new qn(t),this.numTaps=t.numTaps,this.reset()};Hn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Hn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Hn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Hn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Gn=function(){this._zoomIn=new Hn({numTouches:1,numTaps:2}),this._zoomOut=new Hn({numTouches:2,numTaps:1}),this.reset()};Gn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Gn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Gn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Gn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Gn.prototype.touchcancel=function(){this.reset()},Gn.prototype.enable=function(){this._enabled=!0},Gn.prototype.disable=function(){this._enabled=!1,this.reset()},Gn.prototype.isEnabled=function(){return this._enabled},Gn.prototype.isActive=function(){return this._active};var Yn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};Yn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},Yn.prototype._correctButton=function(t,e){return!1},Yn.prototype._move=function(t,e){return{}},Yn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},Yn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r&&(t.preventDefault(),this._moved||!(e.dist(r)<this._clickTolerance)))return this._moved=!0,this._lastPoint=e,this._move(r,e)},Yn.prototype.mouseupWindow=function(t){r.mouseButton(t)===this._eventButton&&(this._moved&&r.suppressClick(),this.reset())},Yn.prototype.enable=function(){this._enabled=!0},Yn.prototype.disable=function(){this._enabled=!1,this.reset()},Yn.prototype.isEnabled=function(){return this._enabled},Yn.prototype.isActive=function(){return this._active};var Wn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.mousedown=function(e,r){t.prototype.mousedown.call(this,e,r),this._lastPoint&&(this._active=!0)},e.prototype._correctButton=function(t,e){return 0===e&&!t.ctrlKey},e.prototype._move=function(t,e){return{around:e,panDelta:e.sub(t)}},e}(Yn),Xn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=.8*(e.x-t.x);if(r)return this._active=!0,{bearingDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Yn),Zn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=-.5*(e.y-t.y);if(r)return this._active=!0,{pitchDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Yn),Jn=function(t){this._minTouches=1,this._clickTolerance=t.clickTolerance||1,this.reset()};Jn.prototype.reset=function(){this._active=!1,this._touches={},this._sum=new t.Point(0,0)},Jn.prototype.touchstart=function(t,e,r){return this._calculateTransform(t,e,r)},Jn.prototype.touchmove=function(t,e,r){if(this._active)return t.preventDefault(),this._calculateTransform(t,e,r)},Jn.prototype.touchend=function(t,e,r){this._calculateTransform(t,e,r),this._active&&r.length<this._minTouches&&this.reset()},Jn.prototype.touchcancel=function(){this.reset()},Jn.prototype._calculateTransform=function(e,r,n){n.length>0&&(this._active=!0);var i=Vn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var c=i[l],u=this._touches[l];u&&(a._add(c),o._add(c.sub(u)),s++,i[l]=c)}if(this._touches=i,!(s<this._minTouches)&&o.mag()){var f=o.div(s);if(this._sum._add(f),!(this._sum.mag()<this._clickTolerance))return{around:a.div(s),panDelta:f}}},Jn.prototype.enable=function(){this._enabled=!0},Jn.prototype.disable=function(){this._enabled=!1,this.reset()},Jn.prototype.isEnabled=function(){return this._enabled},Jn.prototype.isActive=function(){return this._active};var Kn=function(){this.reset()};function Qn(t,e,r){for(var n=0;n<t.length;n++)if(t[n].identifier===r)return e[n]}Kn.prototype.reset=function(){this._active=!1,delete this._firstTwoTouches},Kn.prototype._start=function(t){},Kn.prototype._move=function(t,e,r){return{}},Kn.prototype.touchstart=function(t,e,r){this._firstTwoTouches||r.length<2||(this._firstTwoTouches=[r[0].identifier,r[1].identifier],this._start([e[0],e[1]]))},Kn.prototype.touchmove=function(t,e,r){if(this._firstTwoTouches){t.preventDefault();var n=this._firstTwoTouches,i=n[0],a=n[1],o=Qn(r,e,i),s=Qn(r,e,a);if(o&&s){var l=this._aroundCenter?null:o.add(s).div(2);return this._move([o,s],l,t)}}},Kn.prototype.touchend=function(t,e,n){if(this._firstTwoTouches){var i=this._firstTwoTouches,a=i[0],o=i[1],s=Qn(n,e,a),l=Qn(n,e,o);s&&l||(this._active&&r.suppressClick(),this.reset())}},Kn.prototype.touchcancel=function(){this.reset()},Kn.prototype.enable=function(t){this._enabled=!0,this._aroundCenter=!!t&&\"center\"===t.around},Kn.prototype.disable=function(){this._enabled=!1,this.reset()},Kn.prototype.isEnabled=function(){return this._enabled},Kn.prototype.isActive=function(){return this._active};function $n(t,e){return Math.log(t/e)/Math.LN2}var ti=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._distance,delete this._startDistance},e.prototype._start=function(t){this._startDistance=this._distance=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._distance;if(this._distance=t[0].dist(t[1]),this._active||!(Math.abs($n(this._distance,this._startDistance))<.1))return this._active=!0,{zoomDelta:$n(this._distance,r),pinchAround:e}},e}(Kn);function ei(t,e){return 180*t.angleWith(e)/Math.PI}var ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._minDiameter,delete this._startVector,delete this._vector},e.prototype._start=function(t){this._startVector=this._vector=t[0].sub(t[1]),this._minDiameter=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._vector;if(this._vector=t[0].sub(t[1]),this._active||!this._isBelowThreshold(this._vector))return this._active=!0,{bearingDelta:ei(this._vector,r),pinchAround:e}},e.prototype._isBelowThreshold=function(t){this._minDiameter=Math.min(this._minDiameter,t.mag());var e=25/(Math.PI*this._minDiameter)*360,r=ei(t,this._startVector);return Math.abs(r)<e},e}(Kn);function ni(t){return Math.abs(t.y)>Math.abs(t.x)}var ii=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,ni(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid){this._lastPoints=t,this._active=!0;return{pitchDelta:-.5*((n.y+i.y)/2)}}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return ni(t)&&ni(e)&&a}},e}(Kn),ai={panStep:100,bearingStep:15,pitchStep:10},oi=function(){var t=ai;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep};function si(t){return t*(2-t)}oi.prototype.reset=function(){this._active=!1},oi.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:\"keyboardHandler\",easing:si,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},oi.prototype.enable=function(){this._enabled=!0},oi.prototype.disable=function(){this._enabled=!1,this.reset()},oi.prototype.isEnabled=function(){return this._enabled},oi.prototype.isActive=function(){return this._active};var li=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=1/450,t.bindAll([\"_onWheel\",\"_onTimeout\",\"_onScrollFrame\",\"_onScrollFinished\"],this)};li.prototype.setZoomRate=function(t){this._defaultZoomRate=t},li.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},li.prototype.isEnabled=function(){return!!this._enabled},li.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},li.prototype.isZooming=function(){return!!this._zooming},li.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},li.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},li.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%4.000244140625==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},li.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(t)},li.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},li.prototype.renderFrame=function(){return this._onScrollFrame()},li.prototype._onScrollFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>4.000244140625?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,c=this._easing,u=!1;if(\"wheel\"===this._type&&l&&c){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=c(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):u=!0}else o=s,u=!0;return this._active=!0,u&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!u,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},li.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},li.prototype.reset=function(){this._active=!1};var ci=function(t,e){this._clickZoom=t,this._tapZoom=e};ci.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},ci.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},ci.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},ci.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var ui=function(){this.reset()};ui.prototype.reset=function(){this._active=!1},ui.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},ui.prototype.enable=function(){this._enabled=!0},ui.prototype.disable=function(){this._enabled=!1,this.reset()},ui.prototype.isEnabled=function(){return this._enabled},ui.prototype.isActive=function(){return this._active};var fi=function(){this._tap=new Hn({numTouches:1,numTaps:1}),this.reset()};fi.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},fi.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},fi.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},fi.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},fi.prototype.touchcancel=function(){this.reset()},fi.prototype.enable=function(){this._enabled=!0},fi.prototype.disable=function(){this._enabled=!1,this.reset()},fi.prototype.isEnabled=function(){return this._enabled},fi.prototype.isActive=function(){return this._active};var hi=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};hi.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},hi.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},hi.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},hi.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var pi=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};pi.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},pi.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},pi.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},pi.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var di=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};di.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},di.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},di.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},di.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},di.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},di.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var gi=function(t){return t.zoom||t.drag||t.pitch||t.rotate},mi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(t.Event);function vi(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var yi=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new On(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var i=this._el;this._listeners=[[i,\"touchstart\",{passive:!1}],[i,\"touchmove\",{passive:!1}],[i,\"touchend\",void 0],[i,\"touchcancel\",void 0],[i,\"mousedown\",void 0],[i,\"mousemove\",void 0],[i,\"mouseup\",void 0],[t.window.document,\"mousemove\",{capture:!0}],[t.window.document,\"mouseup\",void 0],[i,\"mouseover\",void 0],[i,\"mouseout\",void 0],[i,\"dblclick\",void 0],[i,\"click\",void 0],[i,\"keydown\",{capture:!1}],[i,\"keyup\",void 0],[i,\"wheel\",{passive:!1}],[i,\"contextmenu\",void 0],[t.window,\"blur\",void 0]];for(var a=0,o=this._listeners;a<o.length;a+=1){var s=o[a],l=s[0],c=s[1],u=s[2];r.addEventListener(l,c,l===t.window.document?this.handleWindowEvent:this.handleEvent,u)}};yi.prototype.destroy=function(){for(var e=0,n=this._listeners;e<n.length;e+=1){var i=n[e],a=i[0],o=i[1],s=i[2];r.removeEventListener(a,o,a===t.window.document?this.handleWindowEvent:this.handleEvent,s)}},yi.prototype._addDefaultHandlers=function(t){var e=this._map,r=e.getCanvasContainer();this._add(\"mapEvent\",new Nn(e,t));var n=e.boxZoom=new Un(e,t);this._add(\"boxZoom\",n);var i=new Gn,a=new ui;e.doubleClickZoom=new ci(a,i),this._add(\"tapZoom\",i),this._add(\"clickZoom\",a);var o=new fi;this._add(\"tapDragZoom\",o);var s=e.touchPitch=new ii;this._add(\"touchPitch\",s);var l=new Xn(t),c=new Zn(t);e.dragRotate=new pi(t,l,c),this._add(\"mouseRotate\",l,[\"mousePitch\"]),this._add(\"mousePitch\",c,[\"mouseRotate\"]);var u=new Wn(t),f=new Jn(t);e.dragPan=new hi(r,u,f),this._add(\"mousePan\",u),this._add(\"touchPan\",f,[\"touchZoom\",\"touchRotate\"]);var h=new ri,p=new ti;e.touchZoomRotate=new di(r,p,h,o),this._add(\"touchRotate\",h,[\"touchPan\",\"touchZoom\"]),this._add(\"touchZoom\",p,[\"touchPan\",\"touchRotate\"]);var d=e.scrollZoom=new li(e,this);this._add(\"scrollZoom\",d,[\"mousePan\"]);var g=e.keyboard=new oi;this._add(\"keyboard\",g),this._add(\"blockableMapEvent\",new jn(e));for(var m=0,v=[\"boxZoom\",\"doubleClickZoom\",\"tapDragZoom\",\"touchPitch\",\"dragRotate\",\"dragPan\",\"touchZoomRotate\",\"scrollZoom\",\"keyboard\"];m<v.length;m+=1){var y=v[m];t.interactive&&t[y]&&e[y].enable(t[y])}},yi.prototype._add=function(t,e,r){this._handlers.push({handlerName:t,handler:e,allowed:r}),this._handlersById[t]=e},yi.prototype.stop=function(){if(!this._updatingCamera){for(var t=0,e=this._handlers;t<e.length;t+=1){e[t].handler.reset()}this._inertia.clear(),this._fireEvents({},{}),this._changes=[]}},yi.prototype.isActive=function(){for(var t=0,e=this._handlers;t<e.length;t+=1){if(e[t].handler.isActive())return!0}return!1},yi.prototype.isZooming=function(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()},yi.prototype.isRotating=function(){return!!this._eventsInProgress.rotate},yi.prototype.isMoving=function(){return Boolean(gi(this._eventsInProgress))||this.isZooming()},yi.prototype._blockedByActive=function(t,e,r){for(var n in t)if(n!==r&&(!e||e.indexOf(n)<0))return!0;return!1},yi.prototype.handleWindowEvent=function(t){this.handleEvent(t,t.type+\"Window\")},yi.prototype._getMapTouches=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=i.target;this._el.contains(a)&&e.push(i)}return e},yi.prototype.handleEvent=function(t,e){if(\"blur\"!==t.type){this._updatingCamera=!0;for(var n=\"renderFrame\"===t.type?void 0:t,i={needsRenderFrame:!1},a={},o={},s=t.touches?this._getMapTouches(t.touches):void 0,l=s?r.touchPos(this._el,s):r.mousePos(this._el,t),c=0,u=this._handlers;c<u.length;c+=1){var f=u[c],h=f.handlerName,p=f.handler,d=f.allowed;if(p.isEnabled()){var g=void 0;this._blockedByActive(o,d,h)?p.reset():p[e||t.type]&&(g=p[e||t.type](t,l,s),this.mergeHandlerResult(i,a,g,h,n),g&&g.needsRenderFrame&&this._triggerRenderFrame()),(g||p.isActive())&&(o[h]=p)}}var m={};for(var v in this._previousActiveHandlers)o[v]||(m[v]=n);this._previousActiveHandlers=o,(Object.keys(m).length||vi(i))&&(this._changes.push([i,a,m]),this._triggerRenderFrame()),(Object.keys(o).length||vi(i))&&this._map._stop(!0),this._updatingCamera=!1;var y=i.cameraAnimation;y&&(this._inertia.clear(),this._fireEvents({},{}),this._changes=[],y(this._map))}else this.stop()},yi.prototype.mergeHandlerResult=function(e,r,n,i,a){if(n){t.extend(e,n);var o={handlerName:i,originalEvent:n.originalEvent||a};void 0!==n.zoomDelta&&(r.zoom=o),void 0!==n.panDelta&&(r.drag=o),void 0!==n.pitchDelta&&(r.pitch=o),void 0!==n.bearingDelta&&(r.rotate=o)}},yi.prototype._applyChanges=function(){for(var e={},r={},n={},i=0,a=this._changes;i<a.length;i+=1){var o=a[i],s=o[0],l=o[1],c=o[2];s.panDelta&&(e.panDelta=(e.panDelta||new t.Point(0,0))._add(s.panDelta)),s.zoomDelta&&(e.zoomDelta=(e.zoomDelta||0)+s.zoomDelta),s.bearingDelta&&(e.bearingDelta=(e.bearingDelta||0)+s.bearingDelta),s.pitchDelta&&(e.pitchDelta=(e.pitchDelta||0)+s.pitchDelta),void 0!==s.around&&(e.around=s.around),void 0!==s.pinchAround&&(e.pinchAround=s.pinchAround),s.noInertia&&(e.noInertia=s.noInertia),t.extend(r,l),t.extend(n,c)}this._updateMapTransform(e,r,n),this._changes=[]},yi.prototype._updateMapTransform=function(t,e,r){var n=this._map,i=n.transform;if(!vi(t))return this._fireEvents(e,r);var a=t.panDelta,o=t.zoomDelta,s=t.bearingDelta,l=t.pitchDelta,c=t.around,u=t.pinchAround;void 0!==u&&(c=u),n._stop(!0),c=c||n.transform.centerPoint;var f=i.pointLocation(a?c.sub(a):c);s&&(i.bearing+=s),l&&(i.pitch+=l),o&&(i.zoom+=o),i.setLocationAtPoint(f,c),this._map._update(),t.noInertia||this._inertia.record(t),this._fireEvents(e,r)},yi.prototype._fireEvents=function(e,r){var n=this,i=gi(this._eventsInProgress),a=gi(e),o={};for(var s in e){var l=e[s].originalEvent;this._eventsInProgress[s]||(o[s+\"start\"]=l),this._eventsInProgress[s]=e[s]}for(var c in!i&&a&&this._fireEvent(\"movestart\",a.originalEvent),o)this._fireEvent(c,o[c]);for(var u in e.rotate&&(this._bearingChanged=!0),a&&this._fireEvent(\"move\",a.originalEvent),e){var f=e[u].originalEvent;this._fireEvent(u,f)}var h,p={};for(var d in this._eventsInProgress){var g=this._eventsInProgress[d],m=g.handlerName,v=g.originalEvent;this._handlersById[m].isActive()||(delete this._eventsInProgress[d],h=r[m]||v,p[d+\"end\"]=h)}for(var y in p)this._fireEvent(y,p[y]);var x=gi(this._eventsInProgress);if((i||a)&&!x){this._updatingCamera=!0;var b=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),_=function(t){return 0!==t&&-n._bearingSnap<t&&t<n._bearingSnap};b?(_(b.bearing||this._map.getBearing())&&(b.bearing=0),this._map.easeTo(b,{originalEvent:h})):(this._map.fire(new t.Event(\"moveend\",{originalEvent:h})),_(this._map.getBearing())&&this._map.resetNorth()),this._bearingChanged=!1,this._updatingCamera=!1}},yi.prototype._fireEvent=function(e,r){this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},yi.prototype._triggerRenderFrame=function(){var t=this;void 0===this._frameId&&(this._frameId=this._map._requestRenderFrame((function(e){delete t._frameId,t.handleEvent(new mi(\"renderFrame\",{timeStamp:e})),t._applyChanges()})))};var xi=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll([\"_renderFrameCallback\"],this)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getCenter=function(){return new t.LngLat(this.transform.center.lng,this.transform.center.lat)},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.Point.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.getPadding=function(){return this.transform.padding},r.prototype.setPadding=function(t,e){return this.jumpTo({padding:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.resetNorthPitch=function(e,r){return this.easeTo(t.extend({bearing:0,pitch:0,duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.cameraForBounds=function(e,r){return e=t.LngLatBounds.convert(e),this._cameraForBoxAndBearing(e.getNorthWest(),e.getSouthEast(),0,r)},r.prototype._cameraForBoxAndBearing=function(e,r,n,i){var a={top:0,bottom:0,right:0,left:0};if(\"number\"==typeof(i=t.extend({padding:a,offset:[0,0],maxZoom:this.transform.maxZoom},i)).padding){var o=i.padding;i.padding={top:o,bottom:o,right:o,left:o}}i.padding=t.extend(a,i.padding);var s=this.transform,l=s.padding,c=s.project(t.LngLat.convert(e)),u=s.project(t.LngLat.convert(r)),f=c.rotate(-n*Math.PI/180),h=u.rotate(-n*Math.PI/180),p=new t.Point(Math.max(f.x,h.x),Math.max(f.y,h.y)),d=new t.Point(Math.min(f.x,h.x),Math.min(f.y,h.y)),g=p.sub(d),m=(s.width-(l.left+l.right+i.padding.left+i.padding.right))/g.x,v=(s.height-(l.top+l.bottom+i.padding.top+i.padding.bottom))/g.y;if(!(v<0||m<0)){var y=Math.min(s.scaleZoom(s.scale*Math.min(m,v)),i.maxZoom),x=t.Point.convert(i.offset),b=(i.padding.left-i.padding.right)/2,_=(i.padding.top-i.padding.bottom)/2,w=new t.Point(x.x+b,x.y+_).mult(s.scale/s.zoomScale(y));return{center:s.unproject(c.add(u).div(2).sub(w)),zoom:y,bearing:n}}t.warnOnce(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\")},r.prototype.fitBounds=function(t,e,r){return this._fitInternal(this.cameraForBounds(t,e),e,r)},r.prototype.fitScreenCoordinates=function(e,r,n,i,a){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(t.Point.convert(e)),this.transform.pointLocation(t.Point.convert(r)),n,i),i,a)},r.prototype._fitInternal=function(e,r,n){return e?(delete(r=t.extend(e,r)).padding,r.linear?this.easeTo(r,n):this.flyTo(r,n)):this},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,i=!1,a=!1,o=!1;return\"zoom\"in e&&n.zoom!==+e.zoom&&(i=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=t.LngLat.convert(e.center)),\"bearing\"in e&&n.bearing!==+e.bearing&&(a=!0,n.bearing=+e.bearing),\"pitch\"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),null==e.padding||n.isPaddingEqual(e.padding)||(n.padding=e.padding),this.fire(new t.Event(\"movestart\",r)).fire(new t.Event(\"move\",r)),i&&this.fire(new t.Event(\"zoomstart\",r)).fire(new t.Event(\"zoom\",r)).fire(new t.Event(\"zoomend\",r)),a&&this.fire(new t.Event(\"rotatestart\",r)).fire(new t.Event(\"rotate\",r)).fire(new t.Event(\"rotateend\",r)),o&&this.fire(new t.Event(\"pitchstart\",r)).fire(new t.Event(\"pitch\",r)).fire(new t.Event(\"pitchend\",r)),this.fire(new t.Event(\"moveend\",r))},r.prototype.easeTo=function(e,r){var n=this;this._stop(!1,e.easeId),(!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate||!e.essential&&t.browser.prefersReducedMotion)&&(e.duration=0);var i=this.transform,a=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=this.getPadding(),c=\"zoom\"in e?+e.zoom:a,u=\"bearing\"in e?this._normalizeBearing(e.bearing,o):o,f=\"pitch\"in e?+e.pitch:s,h=\"padding\"in e?e.padding:i.padding,p=t.Point.convert(e.offset),d=i.centerPoint.add(p),g=i.pointLocation(d),m=t.LngLat.convert(e.center||g);this._normalizeCenter(m);var v,y,x=i.project(g),b=i.project(m).sub(x),_=i.zoomScale(c-a);e.around&&(v=t.LngLat.convert(e.around),y=i.locationPoint(v));var w={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||c!==a,this._rotating=this._rotating||o!==u,this._pitching=this._pitching||f!==s,this._padding=!i.isPaddingEqual(h),this._easeId=e.easeId,this._prepareEase(r,e.noMoveStart,w),clearTimeout(this._easeEndTimeoutID),this._ease((function(e){if(n._zooming&&(i.zoom=t.number(a,c,e)),n._rotating&&(i.bearing=t.number(o,u,e)),n._pitching&&(i.pitch=t.number(s,f,e)),n._padding&&(i.interpolatePadding(l,h,e),d=i.centerPoint.add(p)),v)i.setLocationAtPoint(v,y);else{var g=i.zoomScale(i.zoom-a),m=c>a?Math.min(2,_):Math.max(.5,_),w=Math.pow(m,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(g));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event(\"movestart\",e)),this._zooming&&!n.zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&!n.rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&!n.pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event(\"zoomend\",e)),i&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),c=this.getPadding(),u=\"zoom\"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,p=\"padding\"in e?e.padding:a.padding,d=a.zoomScale(u-o),g=t.Point.convert(e.offset),m=a.centerPoint.add(g),v=a.pointLocation(m),y=t.LngLat.convert(e.center||v);this._normalizeCenter(y);var x=a.project(v),b=a.project(y).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if(\"minZoom\"in e){var A=t.clamp(Math.min(e.minZoom,o,u),a.minZoom,a.maxZoom),M=w/a.zoomScale(A-o);_=Math.sqrt(M/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function L(t){return(Math.exp(t)-Math.exp(-t))/2}function C(t){return(Math.exp(t)+Math.exp(-t))/2}var P=E(0),I=function(t){return C(P)/C(P+_*t)},O=function(t){return w*((C(P)*(L(e=P+_*t)/C(e))-L(P))/S)/k;var e},z=(E(1)-P)/_;if(Math.abs(k)<1e-6||!isFinite(z)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var D=T<w?-1:1;z=Math.abs(Math.log(T/w))/_,O=function(){return 0},I=function(t){return Math.exp(D*_*t)}}if(\"duration\"in e)e.duration=+e.duration;else{var R=\"screenSpeed\"in e?+e.screenSpeed/_:+e.speed;e.duration=1e3*z/R}return e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*z,d=1/I(i);a.zoom=1===e?u:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(c,p,e),m=a.centerPoint.add(g));var v=1===e?y:a.unproject(x.add(b.mult(O(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?v.wrap():v,m),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop()}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),bi=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};bi.prototype.getDefaultPosition=function(){return\"bottom-right\"},bi.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},bi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},bi.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n<r.length-1?\"&\":\"\")),t}),\"?\");e.href=t.config.FEEDBACK_URL+\"/\"+n+(this._map._hash?this._map._hash.getHashString(!0):\"\"),e.rel=\"noopener nofollow\"}},bi.prototype._updateData=function(t){!t||\"metadata\"!==t.sourceDataType&&\"style\"!==t.dataType||(this._updateAttributions(),this._updateEditLink())},bi.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map((function(t){return\"string\"!=typeof t?\"\":t}))):\"string\"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var i=r[n];if(i.used){var a=i.getSource();a.attribution&&t.indexOf(a.attribution)<0&&t.push(a.attribution)}}t.sort((function(t,e){return t.length-e.length}));var o=(t=t.filter((function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0}))).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},bi.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\")};var _i=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};_i.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},_i.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},_i.prototype.getDefaultPosition=function(){return\"bottom-left\"},_i.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},_i.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t){if(t[e].getSource().mapbox_logo)return!0}return!1}},_i.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var wi=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};wi.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},wi.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var i=n[r];if(i.id===t)return void(i.cancelled=!0)}},wi.prototype.run=function(t){void 0===t&&(t=0);var e=this._currentlyRunning=this._queue;this._queue=[];for(var r=0,n=e;r<n.length;r+=1){var i=n[r];if(!i.cancelled&&(i.callback(t),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},wi.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var Ti={\"FullscreenControl.Enter\":\"Enter fullscreen\",\"FullscreenControl.Exit\":\"Exit fullscreen\",\"GeolocateControl.FindMyLocation\":\"Find my location\",\"GeolocateControl.LocationNotAvailable\":\"Location not available\",\"LogoControl.Title\":\"Mapbox logo\",\"NavigationControl.ResetBearing\":\"Reset bearing to north\",\"NavigationControl.ZoomIn\":\"Zoom in\",\"NavigationControl.ZoomOut\":\"Zoom out\",\"ScaleControl.Feet\":\"ft\",\"ScaleControl.Meters\":\"m\",\"ScaleControl.Kilometers\":\"km\",\"ScaleControl.Miles\":\"mi\",\"ScaleControl.NauticalMiles\":\"nm\"},ki=t.window.HTMLImageElement,Ai=t.window.HTMLElement,Mi=t.window.ImageBitmap,Si={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:-2,maxZoom:22,minPitch:0,maxPitch:60,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,bearingSnap:7,clickTolerance:3,pitchWithRotate:!0,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:\"sans-serif\",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},Ei=function(n){function i(e){var r=this;if(null!=(e=t.extend({},Si,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(null!=e.minPitch&&e.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(null!=e.maxPitch&&e.maxPitch>60)throw new Error(\"maxPitch must be less than or equal to 60\");var i=new An(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new wi,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},Ti,e.locale),this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof Ai))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",(function(){return r._update(!1)})),this.on(\"moveend\",(function(){return r._update(!1)})),this.on(\"zoom\",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1)),this.handlers=new yi(this,e);var a=\"string\"==typeof e.hash&&e.hash||void 0;this._hash=e.hash&&new Sn(a).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new bi({customAttribution:e.customAttribution})),this.addControl(new _i,e.logoPosition),this.on(\"style.load\",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on(\"data\",(function(e){r._update(\"style\"===e.dataType),r.fire(new t.Event(e.dataType+\"data\",e))})),this.on(\"dataloading\",(function(e){r.fire(new t.Event(e.dataType+\"dataloading\",e))}))}n&&(i.__proto__=n),i.prototype=Object.create(n&&n.prototype),i.prototype.constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&e.getDefaultPosition&&(r=e.getDefaultPosition()),void 0===r&&(r=\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e))),this.fire(new t.Event(\"resize\",e)),a&&this.fire(new t.Event(\"moveend\",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between -2 and the current maxZoom, inclusive\")},i.prototype.getMinZoom=function(){return this.transform.minZoom},i.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()<t&&this.setPitch(t),this;throw new Error(\"minPitch must be between 0 and the current maxPitch, inclusive\")},i.prototype.getMinPitch=function(){return this.transform.minPitch},i.prototype.setMaxPitch=function(t){if((t=null==t?60:t)>60)throw new Error(\"maxPitch must be less than or equal to 60\");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if(\"mouseenter\"===t||\"mouseover\"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new Rn(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new Rn(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new Rn(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;if(void 0===r)return n.prototype.off.call(this,t,e);return this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o<a.length;o++){var s=a[o];if(s.layer===e&&s.listener===r){for(var l in s.delegates)i.off(l,s.delegates[l]);return a.splice(o,1),i}}}(this._delegatedListeners),this},i.prototype.queryRenderedFeatures=function(e,r){if(!this.style)return[];var n;if(void 0!==r||void 0===e||e instanceof t.Point||Array.isArray(e)||(r=e,e=void 0),r=r||{},(e=e||[[0,0],[this.transform.width,this.transform.height]])instanceof t.Point||\"number\"==typeof e[0])n=[t.Point.convert(e)];else{var i=t.Point.convert(e[0]),a=t.Point.convert(e[1]);n=[i,new t.Point(a.x,i.y),a,new t.Point(i.x,a.y),i]}return this.style.queryRenderedFeatures(n,r,this.transform)},i.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},i.prototype.setStyle=function(e,r){return!1!==(r=t.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&e?(this._diffStyle(e,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(e,r))},i.prototype._getUIString=function(t){var e=this._locale[t];if(null==e)throw new Error(\"Missing UI string '\"+t+\"'\");return e},i.prototype._updateStyle=function(t,e){return this.style&&(this.style.setEventedParent(null),this.style._remove()),t?(this.style=new He(this,e||{}),this.style.setEventedParent(this,{style:this.style}),\"string\"==typeof t?this.style.loadURL(t):this.style.loadJSON(t),this):(delete this.style,this)},i.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new He(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},i.prototype._diffStyle=function(e,r){var n=this;if(\"string\"==typeof e){var i=this._requestManager.normalizeStyleURL(e),a=this._requestManager.transformRequest(i,t.ResourceType.Style);t.getJSON(a,(function(e,i){e?n.fire(new t.ErrorEvent(e)):i&&n._updateDiff(i,r)}))}else\"object\"==typeof e&&this._updateDiff(e,r)},i.prototype._updateDiff=function(e,r){try{this.style.setState(e)&&this._update(!0)}catch(n){t.warnOnce(\"Unable to perform style diff: \"+(n.message||n.error||n)+\".  Rebuilding the style from scratch.\"),this._updateStyle(e,r)}},i.prototype.getStyle=function(){if(this.style)return this.style.serialize()},i.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce(\"There is no style added to the map.\")},i.prototype.addSource=function(t,e){return this._lazyInitEmptyStyle(),this.style.addSource(t,e),this._update(!0)},i.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error(\"There is no source with ID '\"+e+\"'\")))},i.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var i=r[n];if(\"loaded\"!==i.state&&\"errored\"!==i.state)return!1}}return!0},i.prototype.addSourceType=function(t,e,r){return this._lazyInitEmptyStyle(),this.style.addSourceType(t,e,r)},i.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0)},i.prototype.getSource=function(t){return this.style.getSource(t)},i.prototype.addImage=function(e,r,n){void 0===n&&(n={});var i=n.pixelRatio;void 0===i&&(i=1);var a=n.sdf;void 0===a&&(a=!1);var o=n.stretchX,s=n.stretchY,l=n.content;this._lazyInitEmptyStyle();if(r instanceof ki||Mi&&r instanceof Mi){var c=t.browser.getImageData(r),u=c.width,f=c.height,h=c.data;this.style.addImage(e,{data:new t.RGBAImage({width:u,height:f},h),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));var p=r.width,d=r.height,g=r.data,m=r;this.style.addImage(e,{data:new t.RGBAImage({width:p,height:d},new Uint8Array(g)),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0,userImage:m}),m.onAdd&&m.onAdd(this,e)}},i.prototype.updateImage=function(e,r){var n=this.style.getImage(e);if(!n)return this.fire(new t.ErrorEvent(new Error(\"The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.\")));var i=r instanceof ki||Mi&&r instanceof Mi?t.browser.getImageData(r):r,a=i.width,o=i.height,s=i.data;if(void 0===a||void 0===o)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));if(a!==n.data.width||o!==n.data.height)return this.fire(new t.ErrorEvent(new Error(\"The width and height of the updated image must be that same as the previous version of the image\")));var l=!(r instanceof ki||Mi&&r instanceof Mi);n.data.replace(s,l),this.style.updateImage(e,n)},i.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error(\"Missing required image id\"))),!1)},i.prototype.removeImage=function(t){this.style.removeImage(t)},i.prototype.loadImage=function(e,r){t.getImage(this._requestManager.transformRequest(e,t.ResourceType.Image),r)},i.prototype.listImages=function(){return this.style.listImages()},i.prototype.addLayer=function(t,e){return this._lazyInitEmptyStyle(),this.style.addLayer(t,e),this._update(!0)},i.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0)},i.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0)},i.prototype.getLayer=function(t){return this.style.getLayer(t)},i.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)},i.prototype.setFilter=function(t,e,r){return void 0===r&&(r={}),this.style.setFilter(t,e,r),this._update(!0)},i.prototype.getFilter=function(t){return this.style.getFilter(t)},i.prototype.setPaintProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setPaintProperty(t,e,r,n),this._update(!0)},i.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},i.prototype.setLayoutProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setLayoutProperty(t,e,r,n),this._update(!0)},i.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},i.prototype.setLight=function(t,e){return void 0===e&&(e={}),this._lazyInitEmptyStyle(),this.style.setLight(t,e),this._update(!0)},i.prototype.getLight=function(){return this.style.getLight()},i.prototype.setFeatureState=function(t,e){return this.style.setFeatureState(t,e),this._update()},i.prototype.removeFeatureState=function(t,e){return this.style.removeFeatureState(t,e),this._update()},i.prototype.getFeatureState=function(t){return this.style.getFeatureState(t)},i.prototype.getContainer=function(){return this._container},i.prototype.getCanvasContainer=function(){return this._canvasContainer},i.prototype.getCanvas=function(){return this._canvas},i.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]},i.prototype._detectMissingCSS=function(){\"rgb(250, 128, 114)\"!==t.window.getComputedStyle(this._missingCSSCanary).getPropertyValue(\"background-color\")&&t.warnOnce(\"This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.\")},i.prototype._setupContainer=function(){var t=this._container;t.classList.add(\"mapboxgl-map\"),(this._missingCSSCanary=r.create(\"div\",\"mapboxgl-canary\",t)).style.visibility=\"hidden\",this._detectMissingCSS();var e=this._canvasContainer=r.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=r.create(\"canvas\",\"mapboxgl-canvas\",e),this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",\"0\"),this._canvas.setAttribute(\"aria-label\",\"Map\");var n=this._containerDimensions();this._resizeCanvas(n[0],n[1]);var i=this._controlContainer=r.create(\"div\",\"mapboxgl-control-container\",t),a=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach((function(t){a[t]=r.create(\"div\",\"mapboxgl-ctrl-\"+t,i)}))},i.prototype._resizeCanvas=function(e,r){var n=t.browser.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+\"px\",this._canvas.style.height=r+\"px\"},i.prototype._setupPainter=function(){var r=t.extend({},e.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),n=this._canvas.getContext(\"webgl\",r)||this._canvas.getContext(\"experimental-webgl\",r);n?(this.painter=new _n(n,this.transform),t.webpSupported.testSupport(n)):this.fire(new t.ErrorEvent(new Error(\"Failed to initialize WebGL\")))},i.prototype._contextLost=function(e){e.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new t.Event(\"webglcontextlost\",{originalEvent:e}))},i.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event(\"webglcontextrestored\",{originalEvent:e}))},i.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},i.prototype._update=function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this},i.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},i.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},i.prototype._render=function(e){var r,n=this,i=0,a=this.painter.context.extTimerQuery;if(this.listens(\"gpu-timing-frame\")&&(r=a.createQueryEXT(),a.beginQueryEXT(a.TIME_ELAPSED_EXT,r),i=t.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(e),!this._removed){var o=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var s=this.transform.zoom,l=t.browser.now();this.style.zoomHistory.update(s,l);var c=new t.EvaluationParameters(s,{now:l,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),u=c.crossFadingFactor();1===u&&u===this._crossFadingFactor||(o=!0,this._crossFadingFactor=u),this.style.update(c)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens(\"gpu-timing-layer\")}),this.fire(new t.Event(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event(\"load\"))),this.style&&(this.style.hasTransitions()||o)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens(\"gpu-timing-frame\")){var f=t.browser.now()-i;a.endQueryEXT(a.TIME_ELAPSED_EXT,r),setTimeout((function(){var e=a.getQueryObjectEXT(r,a.QUERY_RESULT_EXT)/1e6;a.deleteQueryEXT(r),n.fire(new t.Event(\"gpu-timing-frame\",{cpuTime:f,gpuTime:e}))}),50)}if(this.listens(\"gpu-timing-layer\")){var h=this.painter.collectGpuTimers();setTimeout((function(){var e=n.painter.queryGpuTimers(h);n.fire(new t.Event(\"gpu-timing-layer\",{layerTimes:e}))}),50)}return this._sourcesDirty||this._styleDirty||this._placementDirty||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&(this._fullyLoaded||(this._fullyLoaded=!0),this.fire(new t.Event(\"idle\"))),this}},i.prototype.remove=function(){this._hash&&this._hash.remove();for(var e=0,r=this._controls;e<r.length;e+=1){r[e].onRemove(this)}this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),void 0!==t.window&&(t.window.removeEventListener(\"resize\",this._onWindowResize,!1),t.window.removeEventListener(\"online\",this._onWindowOnline,!1));var n=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");n&&n.loseContext(),Li(this._canvasContainer),Li(this._controlContainer),Li(this._missingCSSCanary),this._container.classList.remove(\"mapboxgl-map\"),this._removed=!0,this.fire(new t.Event(\"remove\"))},i.prototype.triggerRepaint=function(){var e=this;this.style&&!this._frame&&(this._frame=t.browser.frame((function(t){e._frame=null,e._render(t)})))},i.prototype._onWindowOnline=function(){this._update()},i.prototype._onWindowResize=function(t){this._trackResize&&this.resize({originalEvent:t})._update()},a.showTileBoundaries.get=function(){return!!this._showTileBoundaries},a.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},a.showPadding.get=function(){return!!this._showPadding},a.showPadding.set=function(t){this._showPadding!==t&&(this._showPadding=t,this._update())},a.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},a.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},a.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},a.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},a.repaint.get=function(){return!!this._repaint},a.repaint.set=function(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())},a.vertices.get=function(){return!!this._vertices},a.vertices.set=function(t){this._vertices=t,this._update()},i.prototype._setCacheLimits=function(e,r){t.setCacheLimits(e,r)},a.version.get=function(){return t.version},Object.defineProperties(i.prototype,a),i}(xi);function Li(t){t.parentNode&&t.parentNode.removeChild(t)}var Ci={showCompass:!0,showZoom:!0,visualizePitch:!1},Pi=function(e){var n=this;this.options=t.extend({},Ci,e),this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this.options.showZoom&&(t.bindAll([\"_setButtonTitle\",\"_updateZoomButtons\"],this),this._zoomInButton=this._createButton(\"mapboxgl-ctrl-zoom-in\",(function(t){return n._map.zoomIn({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomInButton).setAttribute(\"aria-hidden\",!0),this._zoomOutButton=this._createButton(\"mapboxgl-ctrl-zoom-out\",(function(t){return n._map.zoomOut({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomOutButton).setAttribute(\"aria-hidden\",!0)),this.options.showCompass&&(t.bindAll([\"_rotateCompassArrow\"],this),this._compass=this._createButton(\"mapboxgl-ctrl-compass\",(function(t){n.options.visualizePitch?n._map.resetNorthPitch({},{originalEvent:t}):n._map.resetNorth({},{originalEvent:t})})),this._compassIcon=r.create(\"span\",\"mapboxgl-ctrl-icon\",this._compass),this._compassIcon.setAttribute(\"aria-hidden\",!0))};Pi.prototype._updateZoomButtons=function(){var t=this._map.getZoom();this._zoomInButton.disabled=t===this._map.getMaxZoom(),this._zoomOutButton.disabled=t===this._map.getMinZoom()},Pi.prototype._rotateCompassArrow=function(){var t=this.options.visualizePitch?\"scale(\"+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+\") rotateX(\"+this._map.transform.pitch+\"deg) rotateZ(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\":\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassIcon.style.transform=t},Pi.prototype.onAdd=function(t){return this._map=t,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,\"ZoomIn\"),this._setButtonTitle(this._zoomOutButton,\"ZoomOut\"),this._map.on(\"zoom\",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,\"ResetBearing\"),this.options.visualizePitch&&this._map.on(\"pitch\",this._rotateCompassArrow),this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ii(this._map,this._compass,this.options.visualizePitch)),this._container},Pi.prototype.onRemove=function(){r.remove(this._container),this.options.showZoom&&this._map.off(\"zoom\",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off(\"pitch\",this._rotateCompassArrow),this._map.off(\"rotate\",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map},Pi.prototype._createButton=function(t,e){var n=r.create(\"button\",t,this._container);return n.type=\"button\",n.addEventListener(\"click\",e),n},Pi.prototype._setButtonTitle=function(t,e){var r=this._map._getUIString(\"NavigationControl.\"+e);t.title=r,t.setAttribute(\"aria-label\",r)};var Ii=function(e,n,i){void 0===i&&(i=!1),this._clickTolerance=10,this.element=n,this.mouseRotate=new Xn({clickTolerance:e.dragRotate._mouseRotate._clickTolerance}),this.map=e,i&&(this.mousePitch=new Zn({clickTolerance:e.dragRotate._mousePitch._clickTolerance})),t.bindAll([\"mousedown\",\"mousemove\",\"mouseup\",\"touchstart\",\"touchmove\",\"touchend\",\"reset\"],this),r.addEventListener(n,\"mousedown\",this.mousedown),r.addEventListener(n,\"touchstart\",this.touchstart,{passive:!1}),r.addEventListener(n,\"touchmove\",this.touchmove),r.addEventListener(n,\"touchend\",this.touchend),r.addEventListener(n,\"touchcancel\",this.reset)};function Oi(e,r,n){if(e=new t.LngLat(e.lng,e.lat),r){var i=new t.LngLat(e.lng-360,e.lat),a=new t.LngLat(e.lng+360,e.lat),o=n.locationPoint(e).distSqr(r);n.locationPoint(i).distSqr(r)<o?e=i:n.locationPoint(a).distSqr(r)<o&&(e=a)}for(;Math.abs(e.lng-n.center.lng)>180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ii.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ii.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ii.prototype.off=function(){var t=this.element;r.removeEventListener(t,\"mousedown\",this.mousedown),r.removeEventListener(t,\"touchstart\",this.touchstart,{passive:!1}),r.removeEventListener(t,\"touchmove\",this.touchmove),r.removeEventListener(t,\"touchend\",this.touchend),r.removeEventListener(t,\"touchcancel\",this.reset),this.offTemp()},Ii.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,\"mousemove\",this.mousemove),r.removeEventListener(t.window,\"mouseup\",this.mouseup)},Ii.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,\"mousemove\",this.mousemove),r.addEventListener(t.window,\"mouseup\",this.mouseup)},Ii.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ii.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ii.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ii.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ii.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),this.reset()},Ii.prototype.reset=function(){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()};var zi={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function Di(t,e,r){var n=t.classList;for(var i in zi)n.remove(\"mapboxgl-\"+r+\"-anchor-\"+i);n.add(\"mapboxgl-\"+r+\"-anchor-\"+e)}var Ri,Fi=function(e){function n(n,i){var a=this;if(e.call(this),(n instanceof t.window.HTMLElement||i)&&(n=t.extend({element:n},i)),t.bindAll([\"_update\",\"_onMove\",\"_onUp\",\"_addDragHandler\",\"_onMapClick\",\"_onKeyPress\"],this),this._anchor=n&&n.anchor||\"center\",this._color=n&&n.color||\"#3FB1CE\",this._draggable=n&&n.draggable||!1,this._state=\"inactive\",this._rotation=n&&n.rotation||0,this._rotationAlignment=n&&n.rotationAlignment||\"auto\",this._pitchAlignment=n&&n.pitchAlignment&&\"auto\"!==n.pitchAlignment?n.pitchAlignment:this._rotationAlignment,n&&n.element)this._element=n.element,this._offset=t.Point.convert(n&&n.offset||[0,0]);else{this._defaultMarker=!0,this._element=r.create(\"div\"),this._element.setAttribute(\"aria-label\",\"Map marker\");var o=r.createNS(\"http://www.w3.org/2000/svg\",\"svg\");o.setAttributeNS(null,\"display\",\"block\"),o.setAttributeNS(null,\"height\",\"41px\"),o.setAttributeNS(null,\"width\",\"27px\"),o.setAttributeNS(null,\"viewBox\",\"0 0 27 41\");var s=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");s.setAttributeNS(null,\"stroke\",\"none\"),s.setAttributeNS(null,\"stroke-width\",\"1\"),s.setAttributeNS(null,\"fill\",\"none\"),s.setAttributeNS(null,\"fill-rule\",\"evenodd\");var l=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");l.setAttributeNS(null,\"fill-rule\",\"nonzero\");var c=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");c.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),c.setAttributeNS(null,\"fill\",\"#000000\");for(var u=0,f=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}];u<f.length;u+=1){var h=f[u],p=r.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");p.setAttributeNS(null,\"opacity\",\"0.04\"),p.setAttributeNS(null,\"cx\",\"10.5\"),p.setAttributeNS(null,\"cy\",\"5.80029008\"),p.setAttributeNS(null,\"rx\",h.rx),p.setAttributeNS(null,\"ry\",h.ry),c.appendChild(p)}var d=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");d.setAttributeNS(null,\"fill\",this._color);var g=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");g.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),d.appendChild(g);var m=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");m.setAttributeNS(null,\"opacity\",\"0.25\"),m.setAttributeNS(null,\"fill\",\"#000000\");var v=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");v.setAttributeNS(null,\"d\",\"M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z\"),m.appendChild(v);var y=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");y.setAttributeNS(null,\"transform\",\"translate(6.0, 7.0)\"),y.setAttributeNS(null,\"fill\",\"#FFFFFF\");var x=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");x.setAttributeNS(null,\"transform\",\"translate(8.0, 8.0)\");var b=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");b.setAttributeNS(null,\"fill\",\"#000000\"),b.setAttributeNS(null,\"opacity\",\"0.25\"),b.setAttributeNS(null,\"cx\",\"5.5\"),b.setAttributeNS(null,\"cy\",\"5.5\"),b.setAttributeNS(null,\"r\",\"5.4999962\");var _=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");_.setAttributeNS(null,\"fill\",\"#FFFFFF\"),_.setAttributeNS(null,\"cx\",\"5.5\"),_.setAttributeNS(null,\"cy\",\"5.5\"),_.setAttributeNS(null,\"r\",\"5.4999962\"),x.appendChild(b),x.appendChild(_),l.appendChild(c),l.appendChild(d),l.appendChild(m),l.appendChild(y),l.appendChild(x),o.appendChild(l),this._element.appendChild(o),this._offset=t.Point.convert(n&&n.offset||[0,-14])}this._element.classList.add(\"mapboxgl-marker\"),this._element.addEventListener(\"dragstart\",(function(t){t.preventDefault()})),this._element.addEventListener(\"mousedown\",(function(t){t.preventDefault()})),this._element.addEventListener(\"focus\",(function(){var t=a._map.getContainer();t.scrollTop=0,t.scrollLeft=0})),Di(this._element,this._anchor,\"marker\"),this._popup=null}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on(\"move\",this._update),t.on(\"moveend\",this._update),this.setDraggable(this._draggable),this._update(),this._map.on(\"click\",this._onMapClick),this},n.prototype.remove=function(){return this._map&&(this._map.off(\"click\",this._onMapClick),this._map.off(\"move\",this._update),this._map.off(\"moveend\",this._update),this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler),this._map.off(\"mouseup\",this._onUp),this._map.off(\"touchend\",this._onUp),this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),delete this._map),r.remove(this._element),this._popup&&this._popup.remove(),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},n.prototype.getElement=function(){return this._element},n.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener(\"keypress\",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute(\"tabindex\")),t){if(!(\"offset\"in t.options)){var e=Math.sqrt(Math.pow(13.5,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-38.1],\"bottom-left\":[e,-1*(24.6+e)],\"bottom-right\":[-e,-1*(24.6+e)],left:[13.5,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat),this._originalTabIndex=this._element.getAttribute(\"tabindex\"),this._originalTabIndex||this._element.setAttribute(\"tabindex\",\"0\"),this._element.addEventListener(\"keypress\",this._onKeyPress)}return this},n.prototype._onKeyPress=function(t){var e=t.code,r=t.charCode||t.keyCode;\"Space\"!==e&&\"Enter\"!==e&&32!==r&&13!==r||this.togglePopup()},n.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},n.prototype.getPopup=function(){return this._popup},n.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},n.prototype._update=function(t){if(this._map){this._map.transform.renderWorldCopies&&(this._lngLat=Oi(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset);var e=\"\";\"viewport\"===this._rotationAlignment||\"auto\"===this._rotationAlignment?e=\"rotateZ(\"+this._rotation+\"deg)\":\"map\"===this._rotationAlignment&&(e=\"rotateZ(\"+(this._rotation-this._map.getBearing())+\"deg)\");var n=\"\";\"viewport\"===this._pitchAlignment||\"auto\"===this._pitchAlignment?n=\"rotateX(0deg)\":\"map\"===this._pitchAlignment&&(n=\"rotateX(\"+this._map.getPitch()+\"deg)\"),t&&\"moveend\"!==t.type||(this._pos=this._pos.round()),r.setTransform(this._element,zi[this._anchor]+\" translate(\"+this._pos.x+\"px, \"+this._pos.y+\"px) \"+n+\" \"+e)}},n.prototype.getOffset=function(){return this._offset},n.prototype.setOffset=function(e){return this._offset=t.Point.convert(e),this._update(),this},n.prototype._onMove=function(e){this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",\"pending\"===this._state&&(this._state=\"active\",this.fire(new t.Event(\"dragstart\"))),this.fire(new t.Event(\"drag\"))},n.prototype._onUp=function(){this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),\"active\"===this._state&&this.fire(new t.Event(\"dragend\")),this._state=\"inactive\"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||\"auto\",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&\"auto\"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Bi={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0};var Ni=0,ji=!1,Ui=function(e){function n(r){e.call(this),this.options=t.extend({},Bi,r),t.bindAll([\"_onSuccess\",\"_onError\",\"_onZoom\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.onAdd=function(e){var n;return this._map=e,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),n=this._setupUI,void 0!==Ri?n(Ri):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:\"geolocation\"}).then((function(t){Ri=\"denied\"!==t.state,n(Ri)})):(Ri=!!t.window.navigator.geolocation,n(Ri)),this._container},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off(\"zoom\",this._onZoom),this._map=void 0,Ni=0,ji=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitude<e.getWest()||r.longitude>e.getEast()||r.latitude<e.getSouth()||r.latitude>e.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event(\"outofmaxbounds\",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+\"px\",this._circleElement.style.height=i+\"px\"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var r=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=r,this._geolocateButton.setAttribute(\"aria-label\",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&ji)return;this._setErrorState()}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",!1===e){t.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var i=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute(\"aria-label\",i)}else{var a=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=a,this._geolocateButton.setAttribute(\"aria-label\",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new Fi(this._dotElement),this._circleElement=r.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new Fi({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",(function(e){var r=e.originalEvent&&\"resize\"===e.originalEvent.type;e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||r||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":Ni--,ji=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}if(\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),++Ni>1?(e={maximumAge:6e5,timeout:0},ji=!0):(e=this.options.positionOptions,ji=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Vi={maxWidth:100,unit:\"metric\"},qi=function(e){this.options=t.extend({},Vi,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function Hi(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&\"imperial\"===r.unit){var l=3.2808*s;if(l>5280)Gi(e,n,l/5280,t._getUIString(\"ScaleControl.Miles\"));else Gi(e,n,l,t._getUIString(\"ScaleControl.Feet\"))}else if(r&&\"nautical\"===r.unit){Gi(e,n,s/1852,t._getUIString(\"ScaleControl.NauticalMiles\"))}else s>=1e3?Gi(e,n,s/1e3,t._getUIString(\"ScaleControl.Kilometers\")):Gi(e,n,s,t._getUIString(\"ScaleControl.Meters\"))}function Gi(t,e,r,n){var i,a,o,s=(i=r,a=Math.pow(10,(\"\"+Math.floor(i)).length-1),o=(o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o),a*o),l=s/r;t.style.width=e*l+\"px\",t.innerHTML=s+\"&nbsp;\"+n}qi.prototype.getDefaultPosition=function(){return\"bottom-left\"},qi.prototype._onMove=function(){Hi(this._map,this._container,this.options)},qi.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",t.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},qi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},qi.prototype.setUnit=function(t){this.options.unit=t,Hi(this._map,this._container,this.options)};var Yi=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce(\"Full screen control 'container' must be a DOM element.\")),t.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in t.window.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in t.window.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in t.window.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in t.window.document&&(this._fullscreenchange=\"MSFullscreenChange\")};Yi.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},Yi.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},Yi.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},Yi.prototype._setupUI=function(){var e=this._fullscreenButton=r.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);r.create(\"span\",\"mapboxgl-ctrl-icon\",e).setAttribute(\"aria-hidden\",!0),e.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},Yi.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},Yi.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},Yi.prototype._isFullscreen=function(){return this._fullscreen},Yi.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},Yi.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var Wi={closeButton:!0,closeOnClick:!0,className:\"\",maxWidth:\"240px\"},Xi=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(Wi),r),t.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createContent=function(){this._content&&r.remove(this._content),this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(e){var n=this,i=this._lngLat||this._trackPointer;if(this._map&&i&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach((function(t){return n._container.classList.add(t)})),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=Oi(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||e)){var a=this._pos=this._trackPointer&&e?e:this._map.project(this._lngLat),o=this.options.anchor,s=function e(r){if(r){if(\"number\"==typeof r){var n=Math.round(Math.sqrt(.5*Math.pow(r,2)));return{center:new t.Point(0,0),top:new t.Point(0,r),\"top-left\":new t.Point(n,n),\"top-right\":new t.Point(-n,n),bottom:new t.Point(0,-r),\"bottom-left\":new t.Point(n,-n),\"bottom-right\":new t.Point(-n,-n),left:new t.Point(r,0),right:new t.Point(-r,0)}}if(r instanceof t.Point||Array.isArray(r)){var i=t.Point.convert(r);return{center:i,top:i,\"top-left\":i,\"top-right\":i,bottom:i,\"bottom-left\":i,\"bottom-right\":i,left:i,right:i}}return{center:t.Point.convert(r.center||[0,0]),top:t.Point.convert(r.top||[0,0]),\"top-left\":t.Point.convert(r[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(r[\"top-right\"]||[0,0]),bottom:t.Point.convert(r.bottom||[0,0]),\"bottom-left\":t.Point.convert(r[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(r[\"bottom-right\"]||[0,0]),left:t.Point.convert(r.left||[0,0]),right:t.Point.convert(r.right||[0,0])}}return e(new t.Point(0,0))}(this.options.offset);if(!o){var l,c=this._container.offsetWidth,u=this._container.offsetHeight;l=a.y+s.bottom.y<u?[\"top\"]:a.y>this._map.transform.height-u?[\"bottom\"]:[],a.x<c/2?l.push(\"left\"):a.x>this._map.transform.width-c/2&&l.push(\"right\"),o=0===l.length?\"bottom\":l.join(\"-\")}var f=a.add(s[o]).round();r.setTransform(this._container,zi[o]+\" translate(\"+f.x+\"px,\"+f.y+\"px)\"),Di(this._container,o,\"popup\")}},n.prototype._onClose=function(){this.remove()},n}(t.Evented);var Zi={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:Ei,NavigationControl:Pi,GeolocateControl:Ui,AttributionControl:bi,ScaleControl:qi,FullscreenControl:Yi,Popup:Xi,Marker:Fi,Style:He,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){Bt().acquire(zt)},clearPrewarmedResources:function(){var t=Rt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(zt),Rt=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()\"))},get accessToken(){return t.config.ACCESS_TOKEN},set accessToken(e){t.config.ACCESS_TOKEN=e},get baseApiUrl(){return t.config.API_URL},set baseApiUrl(e){t.config.API_URL=e},get workerCount(){return Dt.workerCount},set workerCount(t){Dt.workerCount=t},get maxParallelImageRequests(){return t.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(e){t.config.MAX_PARALLEL_IMAGE_REQUESTS=e},clearStorage:function(e){t.clearTileCache(e)},workerUrl:\"\"};return Zi})),r}))},{}],462:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=1<<t+1,r=new Array(e),n=0;n<e;++n)r[n]=a(t,n);return r};var n=t(\"convex-hull\");function i(t,e,r){for(var n=new Array(t),i=0;i<t;++i)n[i]=0,i===e&&(n[i]+=.5),i===r&&(n[i]+=.5);return n}function a(t,e){if(0===e||e===(1<<t+1)-1)return[];for(var r=[],a=[],o=0;o<=t;++o)if(e&1<<o){r.push(i(t,o-1,o-1)),a.push(null);for(var s=0;s<=t;++s)~e&1<<s&&(r.push(i(t,o-1,s-1)),a.push([o,s]))}var l=n(r),c=[];t:for(o=0;o<l.length;++o){var u=l[o],f=[];for(s=0;s<u.length;++s){if(!a[u[s]])continue t;f.push(a[u[s]].slice())}c.push(f)}return c}},{\"convex-hull\":141}],463:[function(t,e,r){var n=t(\"./normalize\"),i=t(\"gl-mat4/create\"),a=t(\"gl-mat4/clone\"),o=t(\"gl-mat4/determinant\"),s=t(\"gl-mat4/invert\"),l=t(\"gl-mat4/transpose\"),c={length:t(\"gl-vec3/length\"),normalize:t(\"gl-vec3/normalize\"),dot:t(\"gl-vec3/dot\"),cross:t(\"gl-vec3/cross\")},u=i(),f=i(),h=[0,0,0,0],p=[[0,0,0],[0,0,0],[0,0,0]],d=[0,0,0];function g(t,e,r,n,i){t[0]=e[0]*n+r[0]*i,t[1]=e[1]*n+r[1]*i,t[2]=e[2]*n+r[2]*i}e.exports=function(t,e,r,i,m,v){if(e||(e=[0,0,0]),r||(r=[0,0,0]),i||(i=[0,0,0]),m||(m=[0,0,0,1]),v||(v=[0,0,0,1]),!n(u,t))return!1;if(a(f,u),f[3]=0,f[7]=0,f[11]=0,f[15]=1,Math.abs(o(f)<1e-8))return!1;var y,x,b,_,w,T,k,A=u[3],M=u[7],S=u[11],E=u[12],L=u[13],C=u[14],P=u[15];if(0!==A||0!==M||0!==S){if(h[0]=A,h[1]=M,h[2]=S,h[3]=P,!s(f,f))return!1;l(f,f),y=m,b=f,_=(x=h)[0],w=x[1],T=x[2],k=x[3],y[0]=b[0]*_+b[4]*w+b[8]*T+b[12]*k,y[1]=b[1]*_+b[5]*w+b[9]*T+b[13]*k,y[2]=b[2]*_+b[6]*w+b[10]*T+b[14]*k,y[3]=b[3]*_+b[7]*w+b[11]*T+b[15]*k}else m[0]=m[1]=m[2]=0,m[3]=1;if(e[0]=E,e[1]=L,e[2]=C,function(t,e){t[0][0]=e[0],t[0][1]=e[1],t[0][2]=e[2],t[1][0]=e[4],t[1][1]=e[5],t[1][2]=e[6],t[2][0]=e[8],t[2][1]=e[9],t[2][2]=e[10]}(p,u),r[0]=c.length(p[0]),c.normalize(p[0],p[0]),i[0]=c.dot(p[0],p[1]),g(p[1],p[1],p[0],1,-i[0]),r[1]=c.length(p[1]),c.normalize(p[1],p[1]),i[0]/=r[1],i[1]=c.dot(p[0],p[2]),g(p[2],p[2],p[0],1,-i[1]),i[2]=c.dot(p[1],p[2]),g(p[2],p[2],p[1],1,-i[2]),r[2]=c.length(p[2]),c.normalize(p[2],p[2]),i[1]/=r[2],i[2]/=r[2],c.cross(d,p[1],p[2]),c.dot(p[0],d)<0)for(var I=0;I<3;I++)r[I]*=-1,p[I][0]*=-1,p[I][1]*=-1,p[I][2]*=-1;return v[0]=.5*Math.sqrt(Math.max(1+p[0][0]-p[1][1]-p[2][2],0)),v[1]=.5*Math.sqrt(Math.max(1-p[0][0]+p[1][1]-p[2][2],0)),v[2]=.5*Math.sqrt(Math.max(1-p[0][0]-p[1][1]+p[2][2],0)),v[3]=.5*Math.sqrt(Math.max(1+p[0][0]+p[1][1]+p[2][2],0)),p[2][1]>p[1][2]&&(v[0]=-v[0]),p[0][2]>p[2][0]&&(v[1]=-v[1]),p[1][0]>p[0][1]&&(v[2]=-v[2]),!0}},{\"./normalize\":464,\"gl-mat4/clone\":284,\"gl-mat4/create\":286,\"gl-mat4/determinant\":287,\"gl-mat4/invert\":299,\"gl-mat4/transpose\":312,\"gl-vec3/cross\":368,\"gl-vec3/dot\":373,\"gl-vec3/length\":383,\"gl-vec3/normalize\":390}],464:[function(t,e,r){e.exports=function(t,e){var r=e[15];if(0===r)return!1;for(var n=1/r,i=0;i<16;i++)t[i]=e[i]*n;return!0}},{}],465:[function(t,e,r){var n=t(\"gl-vec3/lerp\"),i=t(\"mat4-recompose\"),a=t(\"mat4-decompose\"),o=t(\"gl-mat4/determinant\"),s=t(\"quat-slerp\"),l=f(),c=f(),u=f();function f(){return{translate:h(),scale:h(1),skew:h(),perspective:[0,0,0,1],quaternion:[0,0,0,1]}}function 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n.identity(t),n.fromRotationTranslation(t,s,e),t[3]=o[0],t[7]=o[1],t[11]=o[2],t[15]=o[3],n.identity(i),0!==a[2]&&(i[9]=a[2],n.multiply(t,t,i)),0!==a[1]&&(i[9]=0,i[8]=a[1],n.multiply(t,t,i)),0!==a[0]&&(i[8]=0,i[4]=a[0],n.multiply(t,t,i)),n.scale(t,t,r),t}},{\"gl-mat4/create\":286,\"gl-mat4/fromRotationTranslation\":290,\"gl-mat4/identity\":297,\"gl-mat4/multiply\":301,\"gl-mat4/scale\":309,\"gl-mat4/translate\":311}],467:[function(t,e,r){\"use strict\";e.exports=Math.log2||function(t){return Math.log(t)*Math.LOG2E}},{}],468:[function(t,e,r){\"use strict\";var n=t(\"binary-search-bounds\"),i=t(\"mat4-interpolate\"),a=t(\"gl-mat4/invert\"),o=t(\"gl-mat4/rotateX\"),s=t(\"gl-mat4/rotateY\"),l=t(\"gl-mat4/rotateZ\"),c=t(\"gl-mat4/lookAt\"),u=t(\"gl-mat4/translate\"),f=(t(\"gl-mat4/scale\"),t(\"gl-vec3/normalize\")),h=[0,0,0];function 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i=this.computedMatrix,a=i[0],o=i[4],s=i[8],u=i[1],f=i[5],h=i[9],p=i[2],d=i[6],g=i[10],m=e*a+r*u,v=e*o+r*f,y=e*s+r*h,x=-(d*y-g*v),b=-(g*m-p*y),_=-(p*v-d*m),w=Math.sqrt(Math.max(0,1-Math.pow(x,2)-Math.pow(b,2)-Math.pow(_,2))),T=c(x,b,_,w);T>1e-6?(x/=T,b/=T,_/=T,w/=T):(x=b=_=0,w=1);var k=this.computedRotation,A=k[0],M=k[1],S=k[2],E=k[3],L=A*w+E*x+M*_-S*b,C=M*w+E*b+S*x-A*_,P=S*w+E*_+A*b-M*x,I=E*w-A*x-M*b-S*_;if(n){x=p,b=d,_=g;var O=Math.sin(n)/l(x,b,_);x*=O,b*=O,_*=O,I=I*(w=Math.cos(e))-(L=L*w+I*x+C*_-P*b)*x-(C=C*w+I*b+P*x-L*_)*b-(P=P*w+I*_+L*b-C*x)*_}var z=c(L,C,P,I);z>1e-6?(L/=z,C/=z,P/=z,I/=z):(L=C=P=0,I=1),this.rotation.set(t,L,C,P,I)},h.lookAt=function(t,e,r,n){this.recalcMatrix(t),r=r||this.computedCenter,e=e||this.computedEye,n=n||this.computedUp;var a=this.computedMatrix;i(a,e,r,n);var o=this.computedRotation;s(o,a[0],a[1],a[2],a[4],a[5],a[6],a[8],a[9],a[10]),u(o,o),this.rotation.set(t,o[0],o[1],o[2],o[3]);for(var l=0,c=0;c<3;++c)l+=Math.pow(r[c]-e[c],2);this.radius.set(t,.5*Math.log(Math.max(l,1e-6))),this.center.set(t,r[0],r[1],r[2])},h.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},h.setMatrix=function(t,e){var r=this.computedRotation;s(r,e[0],e[1],e[2],e[4],e[5],e[6],e[8],e[9],e[10]),u(r,r),this.rotation.set(t,r[0],r[1],r[2],r[3]);var n=this.computedMatrix;o(n,e);var i=n[15];if(Math.abs(i)>1e-6){var a=n[12]/i,l=n[13]/i,c=n[14]/i;this.recalcMatrix(t);var f=Math.exp(this.computedRadius[0]);this.center.set(t,a-n[2]*f,l-n[6]*f,c-n[10]*f),this.radius.idle(t)}else this.center.idle(t),this.radius.idle(t)},h.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},h.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-1/0,e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},h.getDistanceLimits=function(t){var e=this.radius.bounds;return 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+       "/*!\n",
+       " * pad-left <https://github.com/jonschlinkert/pad-left>\n",
+       " *\n",
+       " * Copyright (c) 2014-2015, Jon Schlinkert.\n",
+       " * Licensed under the MIT license.\n",
+       " */\n",
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+       "/*\n",
+       " * @copyright 2016 Sean Connelly (@voidqk), http://syntheti.cc\n",
+       " * @license MIT\n",
+       " * @preserve Project Home: https://github.com/voidqk/polybooljs\n",
+       " */\n",
+       "var n,i=t(\"./lib/build-log\"),a=t(\"./lib/epsilon\"),o=t(\"./lib/intersecter\"),s=t(\"./lib/segment-chainer\"),l=t(\"./lib/segment-selector\"),c=t(\"./lib/geojson\"),u=!1,f=a();function h(t,e,r){var i=n.segments(t),a=n.segments(e),o=r(n.combine(i,a));return n.polygon(o)}n={buildLog:function(t){return!0===t?u=i():!1===t&&(u=!1),!1!==u&&u.list},epsilon:function(t){return f.epsilon(t)},segments:function(t){var e=o(!0,f,u);return 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a=n[t],o=n[i],s=a[a.length-1],l=a[a.length-2],c=o[0],u=o[1];e.pointsCollinear(l,s,c)&&(r&&r.chainRemoveTail(t,s),a.pop(),s=l),e.pointsCollinear(s,c,u)&&(r&&r.chainRemoveHead(i,c),o.shift()),r&&r.chainJoin(t,i),n[t]=a.concat(o),n.splice(i,1)}})),i}},{}],511:[function(t,e,r){function n(t,e,r){var n=[];return t.forEach((function(t){var i=(t.myFill.above?8:0)+(t.myFill.below?4:0)+(t.otherFill&&t.otherFill.above?2:0)+(t.otherFill&&t.otherFill.below?1:0);0!==e[i]&&n.push({id:r?r.segmentId():-1,start:t.start,end:t.end,myFill:{above:1===e[i],below:2===e[i]},otherFill:null})})),r&&r.selected(n),n}var i={union:function(t,e){return n(t,[0,2,1,0,2,2,0,0,1,0,1,0,0,0,0,0],e)},intersect:function(t,e){return n(t,[0,0,0,0,0,2,0,2,0,0,1,1,0,2,1,0],e)},difference:function(t,e){return n(t,[0,0,0,0,2,0,2,0,1,1,0,0,0,1,2,0],e)},differenceRev:function(t,e){return n(t,[0,2,1,0,0,0,1,1,0,2,0,2,0,0,0,0],e)},xor:function(t,e){return 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n=e,i=0;i<r.length;)if(t[n++]!==r[i++])return!1;return!0},r.str2arr=function(t,e){var r=[],n=0;if(e&&\"hex\"===e)for(;n<t.length;)r.push(parseInt(t.slice(n,n+2),16)),n+=2;else for(;n<t.length;n++)r.push(255&t.charCodeAt(n));return r},r.readUInt16LE=function(t,e){return t[e]|t[e+1]<<8},r.readUInt16BE=function(t,e){return t[e+1]|t[e]<<8},r.readUInt32LE=function(t,e){return t[e]|t[e+1]<<8|t[e+2]<<16|16777216*t[e+3]},r.readUInt32BE=function(t,e){return t[e+3]|t[e+2]<<8|t[e+1]<<16|16777216*t[e]},o.prototype=Object.create(Error.prototype),o.prototype.constructor=o,r.ProbeError=o},{stream:569,\"stream-parser\":585}],514:[function(t,e,r){\"use strict\";function n(t,e){var r=new Error(t);return r.code=e,r}function i(t){try{return decodeURIComponent(escape(t))}catch(e){return t}}function a(t,e,r){this.input=t.subarray(e,r),this.start=e;var i=String.fromCharCode.apply(null,this.input.subarray(0,4));if(\"II*\\0\"!==i&&\"MM\\0*\"!==i)throw n(\"invalid TIFF 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0}},a.prototype.exif_format_read=function(t,e){var r;switch(t){case 1:case 2:return r=this.input[e];case 6:return(r=this.input[e])|33554430*(128&r);case 3:return r=this.read_uint16(e);case 8:return(r=this.read_uint16(e))|131070*(32768&r);case 4:return r=this.read_uint32(e);case 9:return 0|(r=this.read_uint32(e));case 5:case 10:case 11:case 12:case 7:default:return null}},a.prototype.scan_ifd=function(t,e,r){var a=this.read_uint16(e);e+=2;for(var o=0;o<a;o++){var s=this.read_uint16(e),l=this.read_uint16(e+2),c=this.read_uint32(e+4),u=this.exif_format_length(l),f=c*u,h=f<=4?e+8:this.read_uint32(e+8),p=!1;if(h+f>this.input.length)throw n(\"unexpected EOF\",\"EBADDATA\");for(var d=[],g=h,m=0;m<c;m++,g+=u){var v=this.exif_format_read(l,g);if(null===v){d=null;break}d.push(v)}if(Array.isArray(d)&&2===l&&(d=i(String.fromCharCode.apply(null,d)))&&\"\\0\"===d[d.length-1]&&(d=d.slice(0,-1)),this.is_subifd_link(t,s)&&Array.isArray(d)&&Number.isInteger(d[0])&&d[0]>0&&(this.ifds_to_read.push({id:s,offset:d[0]}),p=!0),!1===r({is_big_endian:this.big_endian,ifd:t,tag:s,format:l,count:c,entry_offset:e+this.start,data_length:f,data_offset:h+this.start,value:d,is_subifd_link:p}))return void(this.aborted=!0);e+=12}0===t&&this.ifds_to_read.push({id:1,offset:this.read_uint32(e)})},e.exports.ExifParser=a,e.exports.get_orientation=function(t){var e=0;try{return new a(t,0,t.length).each((function(t){if(0===t.ifd&&274===t.tag&&Array.isArray(t.value))return e=t.value[0],!1})),e}catch(t){return-1}}},{}],515:[function(t,e,r){\"use strict\";var n=t(\"./common\").readUInt16BE,i=t(\"./common\").readUInt32BE;function a(t,e){if(t.length<4+e)return null;var r=i(t,e);return t.length<r+e||r<8?null:{boxtype:String.fromCharCode.apply(null,t.slice(e+4,e+8)),data:t.slice(e+8,e+r),end:e+r}}function o(t,e){for(var r=0;;){var n=a(t,r);if(!n)break;switch(n.boxtype){case\"ispe\":e.sizes.push({width:i(n.data,4),height:i(n.data,8)});break;case\"irot\":e.transforms.push({type:\"irot\",value:3&n.data[0]});break;case\"imir\":e.transforms.push({type:\"imir\",value:1&n.data[0]})}r=n.end}}function s(t,e,r){for(var n=0,i=0;i<r;i++)n=256*n+(t[e+i]||0);return n}function l(t,e){for(var r=t[4]>>4&15,i=15&t[4],a=t[5]>>4&15,o=n(t,6),l=8,c=0;c<o;c++){var u=n(t,l),f=n(t,l+=2),h=s(t,l+=2,a),p=n(t,l+=a);if(l+=2,0===f&&1===p){var d=s(t,l,r),g=s(t,l+r,i);e.item_loc[u]={length:g,offset:d+h}}l+=p*(r+i)}}function c(t,e){for(var r=n(t,4),i=6,o=0;o<r;o++){var s=a(t,i);if(!s)break;if(\"infe\"===s.boxtype){for(var l=n(s.data,4),c=\"\",u=8;u<s.data.length&&s.data[u];u++)c+=String.fromCharCode(s.data[u]);e.item_inf[c]=l}i=s.end}}function u(t,e){for(var r=0;;){var n=a(t,r);if(!n)break;\"ipco\"===n.boxtype&&o(n.data,e),r=n.end}}e.exports.unbox=a,e.exports.readSizeFromMeta=function(t){var e={sizes:[],transforms:[],item_inf:{},item_loc:{}};if(function(t,e){for(var r=4;;){var n=a(t,r);if(!n)break;\"iprp\"===n.boxtype&&u(n.data,e),\"iloc\"===n.boxtype&&l(n.data,e),\"iinf\"===n.boxtype&&c(n.data,e),r=n.end}}(t,e),e.sizes.length){var r,n,i,o=(r=e.sizes,n=r.reduce((function(t,e){return t.width>e.width||t.width===e.width&&t.height>e.height?t:e})),i=r.reduce((function(t,e){return t.height>e.height||t.height===e.height&&t.width>e.width?t:e})),n.width>i.height||n.width===i.height&&n.height>i.width?n:i),s=1;e.transforms.forEach((function(t){var e={1:6,2:5,3:8,4:7,5:4,6:3,7:2,8:1},r={1:4,2:3,3:2,4:1,5:6,6:5,7:8,8:7};if(\"imir\"===t.type&&(s=0===t.value?r[s]:e[s=e[s=r[s]]]),\"irot\"===t.type)for(var n=0;n<t.value;n++)s=e[s]}));var f=null;return e.item_inf.Exif&&(f=e.item_loc[e.item_inf.Exif]),{width:o.width,height:o.height,orientation:e.transforms.length?s:null,variants:e.sizes,exif_location:f}}},e.exports.getMimeType=function(t){var e=String.fromCharCode.apply(null,t.slice(0,4)),r={};r[e]=!0;for(var n=8;n<t.length;n+=4)r[String.fromCharCode.apply(null,t.slice(n,n+4))]=!0;if(r.mif1||r.msf1||r.miaf)return\"avif\"===e||\"avis\"===e||\"avio\"===e?{type:\"avif\",mime:\"image/avif\"}:\"heic\"===e||\"heix\"===e?{type:\"heic\",mime:\"image/heic\"}:\"hevc\"===e||\"hevx\"===e?{type:\"heic\",mime:\"image/heic-sequence\"}:r.avif||r.avis?{type:\"avif\",mime:\"image/avif\"}:r.heic||r.heix||r.hevc||r.hevx||r.heis?r.msf1?{type:\"heif\",mime:\"image/heif-sequence\"}:{type:\"heif\",mime:\"image/heif\"}:{type:\"avif\",mime:\"image/avif\"}}},{\"./common\":513}],516:[function(t,e,r){\"use strict\";var n=t(\"../common\").str2arr,i=t(\"../common\").sliceEq,a=t(\"../common\").readUInt32BE,o=t(\"../miaf_utils\"),s=t(\"../exif_utils\"),l=n(\"ftyp\");e.exports=function(t){if(i(t,4,l)){var e=o.unbox(t,0);if(e){var r=o.getMimeType(e.data);if(r){for(var n,c=e.end;;){var u=o.unbox(t,c);if(!u)break;if(c=u.end,\"mdat\"===u.boxtype)return;if(\"meta\"===u.boxtype){n=u.data;break}}if(n){var f=o.readSizeFromMeta(n);if(f){var h={width:f.width,height:f.height,type:r.type,mime:r.mime,wUnits:\"px\",hUnits:\"px\"};if(f.variants.length>1&&(h.variants=f.variants),f.orientation&&(h.orientation=f.orientation),f.exif_location&&f.exif_location.offset+f.exif_location.length<=t.length){var p=a(t,f.exif_location.offset),d=t.slice(f.exif_location.offset+p+4,f.exif_location.offset+f.exif_location.length),g=s.get_orientation(d);g>0&&(h.orientation=g)}return h}}}}}}},{\"../common\":513,\"../exif_utils\":514,\"../miaf_utils\":515}],517:[function(t,e,r){\"use strict\";var n=t(\"../common\").str2arr,i=t(\"../common\").sliceEq,a=t(\"../common\").readUInt16LE,o=n(\"BM\");e.exports=function(t){if(!(t.length<26)&&i(t,0,o))return{width:a(t,18),height:a(t,22),type:\"bmp\",mime:\"image/bmp\",wUnits:\"px\",hUnits:\"px\"}}},{\"../common\":513}],518:[function(t,e,r){\"use strict\";var n=t(\"../common\").str2arr,i=t(\"../common\").sliceEq,a=t(\"../common\").readUInt16LE,o=n(\"GIF87a\"),s=n(\"GIF89a\");e.exports=function(t){if(!(t.length<10)&&(i(t,0,o)||i(t,0,s)))return{width:a(t,6),height:a(t,8),type:\"gif\",mime:\"image/gif\",wUnits:\"px\",hUnits:\"px\"}}},{\"../common\":513}],519:[function(t,e,r){\"use strict\";var n=t(\"../common\").readUInt16LE;e.exports=function(t){var e=n(t,0),r=n(t,2),i=n(t,4);if(0===e&&1===r&&i){for(var a=[],o={width:0,height:0},s=0;s<i;s++){var 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n=t(\"color-normalize\"),i=t(\"array-bounds\"),a=t(\"object-assign\"),o=t(\"glslify\"),s=t(\"pick-by-alias\"),l=t(\"flatten-vertex-data\"),c=t(\"earcut\"),u=t(\"array-normalize\"),f=t(\"to-float32\"),h=f.float32,p=f.fract32,d=t(\"es6-weak-map\"),g=t(\"parse-rect\"),m=t(\"array-find-index\");function v(t,e){if(!(this instanceof v))return new v(t,e);if(\"function\"==typeof t?(e||(e={}),e.regl=t):e=t,e.length&&(e.positions=e),!(t=e.regl).hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");this.gl=t._gl,this.regl=t,this.passes=[],this.shaders=v.shaders.has(t)?v.shaders.get(t):v.shaders.set(t,v.createShaders(t)).get(t),this.update(e)}e.exports=v,v.dashMult=2,v.maxPatternLength=256,v.precisionThreshold=3e6,v.maxPoints=1e4,v.maxLines=2048,v.shaders=new d,v.createShaders=function(t){var e,r=t.buffer({usage:\"static\",type:\"float\",data:[0,1,0,0,1,1,1,0]}),n={primitive:\"triangle strip\",instances:t.prop(\"count\"),count:4,offset:0,uniforms:{miterMode:function(t,e){return\"round\"===e.join?2:1},miterLimit:t.prop(\"miterLimit\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),thickness:t.prop(\"thickness\"),dashPattern:t.prop(\"dashTexture\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),dashSize:t.prop(\"dashLength\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]},depth:t.prop(\"depth\")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},depth:{enable:function(t,e){return!e.overlay}},stencil:{enable:!1},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\")},i=t(a({vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\\nattribute vec4 color;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\\n\\t// the order is important\\n\\treturn position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n}\\n\\nvoid main() {\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineOffset = lineTop * 2. - 1.;\\n\\n\\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\\n\\ttangent = normalize(diff * scale * viewport.zw);\\n\\tvec2 normal = vec2(-tangent.y, tangent.x);\\n\\n\\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\\n\\t\\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\\n\\n\\t\\t+ thickness * normal * .5 * lineOffset / viewport.zw;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D dashPattern;\\n\\nuniform float dashSize, pixelRatio, thickness, opacity, id;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvoid main() {\\n\\tfloat alpha = 1.;\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\\n\\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:16,divisor:1},color:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1}}},n));try{e=t(a({cull:{enable:!0,face:\"back\"},vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, nextCoord, prevCoord;\\nattribute vec4 aColor, bColor;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, translate;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\nuniform float miterLimit, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 tangent;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nconst float REVERSE_THRESHOLD = -.875;\\nconst float MIN_DIFF = 1e-6;\\n\\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\\n// TODO: precalculate dot products, normalize things beforehead etc.\\n// TODO: refactor to rectangular algorithm\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nbool isNaN( float val ){\\n  return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\\n}\\n\\nvoid main() {\\n\\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\\n\\n  vec2 adjustedScale;\\n  adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\\n  adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\\n\\n  vec2 scaleRatio = adjustedScale * viewport.zw;\\n\\tvec2 normalWidth = thickness / scaleRatio;\\n\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineBot = 1. - lineTop;\\n\\n\\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\\n\\n\\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\\n\\n\\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\\n\\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\\n\\n\\tvec2 prevDiff = aCoord - prevCoord;\\n\\tvec2 currDiff = bCoord - aCoord;\\n\\tvec2 nextDiff = nextCoord - bCoord;\\n\\n\\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\\n\\tvec2 currTangent = normalize(currDiff * scaleRatio);\\n\\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\\n\\n\\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\\n\\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\\n\\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\\n\\n\\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\\n\\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\\n\\n\\t// collapsed/unidirectional segment cases\\n\\t// FIXME: there should be more elegant solution\\n\\tvec2 prevTanDiff = abs(prevTangent - currTangent);\\n\\tvec2 nextTanDiff = abs(nextTangent - currTangent);\\n\\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\\n\\t\\tstartJoinDirection = currNormal;\\n\\t}\\n\\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\\n\\t\\tendJoinDirection = currNormal;\\n\\t}\\n\\tif (aCoord == bCoord) {\\n\\t\\tendJoinDirection = startJoinDirection;\\n\\t\\tcurrNormal = prevNormal;\\n\\t\\tcurrTangent = prevTangent;\\n\\t}\\n\\n\\ttangent = currTangent;\\n\\n\\t//calculate join shifts relative to normals\\n\\tfloat startJoinShift = dot(currNormal, startJoinDirection);\\n\\tfloat endJoinShift = dot(currNormal, endJoinDirection);\\n\\n\\tfloat startMiterRatio = abs(1. / startJoinShift);\\n\\tfloat endMiterRatio = abs(1. / endJoinShift);\\n\\n\\tvec2 startJoin = startJoinDirection * startMiterRatio;\\n\\tvec2 endJoin = endJoinDirection * endMiterRatio;\\n\\n\\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\\n\\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\\n\\tstartBotJoin = -startTopJoin;\\n\\n\\tendTopJoin = sign(endJoinShift) * endJoin * .5;\\n\\tendBotJoin = -endTopJoin;\\n\\n\\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\\n\\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\\n\\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\\n\\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\\n\\n\\t//miter anti-clipping\\n\\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\\n\\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\\n\\n\\t//prevent close to reverse direction switch\\n\\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\n\\tif (prevReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\\n\\t\\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\tbTopCoord -= normalWidth * endTopJoin;\\n\\t\\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\\n\\t}\\n\\n\\tif (nextReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\\n\\t\\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\taBotCoord -= normalWidth * startBotJoin;\\n\\t\\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\\n\\t}\\n\\n\\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\\n\\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\\n\\n\\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\\n\\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\\n\\n\\t//position is normalized 0..1 coord on the screen\\n\\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\\n\\n\\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\n\\tgl_Position = vec4(position  * 2.0 - 1.0, depth, 1);\\n\\n\\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\\n\\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\\n\\n\\t//bevel miter cutoffs\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n\\n\\t//round miter cutoffs\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D dashPattern;\\nuniform float dashSize, pixelRatio, thickness, opacity, id, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nvoid main() {\\n\\tfloat alpha = 1., distToStart, distToEnd;\\n\\tfloat cutoff = thickness * .5;\\n\\n\\t//bevel miter\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToStart + 1., 0.), 1.);\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToEnd + 1., 0.), 1.);\\n\\t\\t}\\n\\t}\\n\\n\\t// round miter\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - startCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - endCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\\n\\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1},bColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:4,divisor:1},prevCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:0,divisor:1},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},nextCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:24,divisor:1}}},n))}catch(t){e=i}return{fill:t({primitive:\"triangle\",elements:function(t,e){return e.triangles},offset:0,vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position, positionFract;\\n\\nuniform vec4 color;\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio, id;\\nuniform vec4 viewport;\\nuniform float opacity;\\n\\nvarying vec4 fragColor;\\n\\nconst float MAX_LINES = 256.;\\n\\nvoid main() {\\n\\tfloat depth = (MAX_LINES - 4. - id) / (MAX_LINES);\\n\\n\\tvec2 position = position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n\\tfragColor.a *= opacity;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n\\tgl_FragColor = fragColor;\\n}\\n\"]),uniforms:{scale:t.prop(\"scale\"),color:t.prop(\"fill\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]}},attributes:{position:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8},positionFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8}},blend:n.blend,depth:{enable:!1},scissor:n.scissor,stencil:n.stencil,viewport:n.viewport}),rect:i,miter:e}},v.defaults={dashes:null,join:\"miter\",miterLimit:1,thickness:10,cap:\"square\",color:\"black\",opacity:1,overlay:!1,viewport:null,range:null,close:!1,fill:null},v.prototype.render=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];e.length&&(t=this).update.apply(t,e),this.draw()},v.prototype.draw=function(){for(var t=this,e=[],r=arguments.length;r--;)e[r]=arguments[r];return(e.length?e:this.passes).forEach((function(e,r){var n;if(e&&Array.isArray(e))return(n=t).draw.apply(n,e);\"number\"==typeof e&&(e=t.passes[e]),e&&e.count>1&&e.opacity&&(t.regl._refresh(),e.fill&&e.triangles&&e.triangles.length>2&&t.shaders.fill(e),e.thickness&&(e.scale[0]*e.viewport.width>v.precisionThreshold||e.scale[1]*e.viewport.height>v.precisionThreshold||\"rect\"===e.join||!e.join&&(e.thickness<=2||e.count>=v.maxPoints)?t.shaders.rect(e):t.shaders.miter(e)))})),this},v.prototype.update=function(t){var e=this;if(t){null!=t.length?\"number\"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var r=this.regl,o=this.gl;if(t.forEach((function(t,f){var d=e.passes[f];if(void 0!==t)if(null!==t){if(\"number\"==typeof t[0]&&(t={positions:t}),t=s(t,{positions:\"positions points data coords\",thickness:\"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth\",join:\"lineJoin linejoin 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l=f({},o);l.frag=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\n\\nuniform float opacity;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat smoothStep(float edge0, float edge1, float x) {\\n\\tfloat t;\\n\\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\\n\\treturn t * t * (3.0 - 2.0 * t);\\n}\\n\\nvoid main() {\\n\\tfloat radius, alpha = 1.0, delta = fragWidth;\\n\\n\\tradius = length(2.0 * gl_PointCoord.xy - 1.0);\\n\\n\\tif (radius > 1.0 + delta) {\\n\\t\\tdiscard;\\n\\t}\\n\\n\\talpha -= smoothstep(1.0 - delta, 1.0 + delta, radius);\\n\\n\\tfloat borderRadius = fragBorderRadius;\\n\\tfloat ratio = smoothstep(borderRadius - delta, borderRadius + delta, radius);\\n\\tvec4 color = mix(fragColor, fragBorderColor, ratio);\\n\\tcolor.a *= alpha * opacity;\\n\\tgl_FragColor = color;\\n}\\n\"]),l.vert=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, 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borderSize * maxSize / 255.;\\n\\n  gl_PointSize = (size + borderSize) * pointSizeScale;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\\n  fragColor = color;\\n  fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n}\\n\"]),m&&(l.frag=l.frag.replace(\"smoothstep\",\"smoothStep\"),s.frag=s.frag.replace(\"smoothstep\",\"smoothStep\")),this.drawCircle=t(l)}b.defaults={color:\"black\",borderColor:\"transparent\",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4},b.prototype.render=function(){return 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r?[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var u=[],h=a.range(i,{lod:!0,px:[(i[2]-i[0])/o.width,(i[3]-i[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(c),g=0;g<r.length;g++){var m=r[g];d[m]=p?p[m]:1}l.subdata(d)}for(var v=h.length;v--;){var y=n(h[v],2),x=y[0],b=y[1];u.push(f({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return u},b.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var i=this.groups,a=this.gl,o=this.regl,s=this.maxSize,c=this.maxColors,h=this.palette;this.groups=i=r.map((function(e,r){var n=i[r];if(void 0===e)return n;null===e?e={positions:null}:\"function\"==typeof e?e={ondraw:e}:\"number\"==typeof e[0]&&(e={positions:e}),null===(e=p(e,{positions:\"positions data 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t.x.length?e.xAttr={buffer:o.buffer(t.x),offset:0,stride:4,count:t.x.length}:e.xAttr={buffer:t.x.buffer,offset:4*t.x.offset||0,stride:4*(t.x.stride||1),count:t.x.count},t.y.length?e.yAttr={buffer:o.buffer(t.y),offset:0,stride:4,count:t.y.length}:e.yAttr={buffer:t.y.buffer,offset:4*t.y.offset||0,stride:4*(t.y.stride||1),count:t.y.count},e.count=Math.max(e.xAttr.count,e.yAttr.count),t;t=g(t,\"float64\");var c=e.count=Math.floor(t.length/2),f=e.bounds=c?l(t,2):null;if(r.range||e.range||(delete e.range,r.range=f),r.marker||e.marker||(delete e.marker,r.marker=null),n&&(!0===n||c>n)?e.tree=u(t,{bounds:f}):n&&n.length&&(e.tree=n),e.tree){var h={primitive:\"points\",usage:\"static\",data:e.tree,type:\"uint32\"};e.elements?e.elements(h):e.elements=o.elements(h)}var p=v.float32(t);return i({data:p,usage:\"dynamic\"}),a({data:v.fract32(t,p),usage:\"dynamic\"}),s({data:new Uint8Array(c),type:\"uint8\",usage:\"stream\"}),t}},{marker:function(e,r,n){var 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E,L=n,C=L.count,P=L.color,I=L.borderColor,O=L.colorBuffer;if(t.tooManyColors){if(P.length||I.length){E=new Uint8Array(8*C);for(var z=0;z<C;z++){var D=P[z];E[8*z]=h[4*D],E[8*z+1]=h[4*D+1],E[8*z+2]=h[4*D+2],E[8*z+3]=h[4*D+3];var R=I[z];E[8*z+4]=h[4*R],E[8*z+5]=h[4*R+1],E[8*z+6]=h[4*R+2],E[8*z+7]=h[4*R+3]}}}else if(P.length||I.length){E=new Uint8Array(4*C+2);for(var F=0;F<C;F++)null!=P[F]&&(E[4*F]=P[F]%c,E[4*F+1]=Math.floor(P[F]/c)),null!=I[F]&&(E[4*F+2]=I[F]%c,E[4*F+3]=Math.floor(I[F]/c))}O({data:E||new Uint8Array(0),type:\"uint8\",usage:\"dynamic\"})}return n}))}},b.prototype.addMarker=function(t){var e,r=this.markerTextures,n=this.regl,i=this.markerCache,a=null==t?0:i.indexOf(t);if(a>=0)return a;if(t instanceof Uint8Array||t instanceof Uint8ClampedArray)e=t;else{e=new Uint8Array(t.length);for(var o=0,s=t.length;o<s;o++)e[o]=255*t[o]}var l=Math.floor(Math.sqrt(e.length));return 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i=.25*(t=t.slice()).length%e;i<n*e;i++)t.push(0,0,0,0);r.height<n&&r.resize(e,n),r.subimage({width:Math.min(.25*t.length,e),height:n,data:t},0,0)}},b.prototype.destroy=function(){return this.groups.forEach((function(t){t.sizeBuffer.destroy(),t.positionBuffer.destroy(),t.positionFractBuffer.destroy(),t.colorBuffer.destroy(),t.activation.forEach((function(t){return t&&t.destroy&&t.destroy()})),t.selectionBuffer.destroy(),t.elements&&t.elements.destroy()})),this.groups.length=0,this.paletteTexture.destroy(),this.markerTextures.forEach((function(t){return t&&t.destroy&&t.destroy()})),this};var _=t(\"object-assign\");e.exports=function(t,e){var r=new x(t,e),n=r.render.bind(r);return 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s.length>2?(s[0],s[2],n=s[1],i=s[3]):s.length?(n=s[0],i=s[1]):(s.x,n=s.y,s.x+s.width,i=s.y+s.height),l.length>2?(a=l[0],o=l[2],l[1],l[3]):l.length?(a=l[0],o=l[1]):(a=l.x,l.y,o=l.x+l.width,l.y+l.height),[a,n,o,i]}function p(t){if(\"number\"==typeof t)return[t,t,t,t];if(2===t.length)return[t[0],t[1],t[0],t[1]];var e=l(t);return[e.x,e.y,e.x+e.width,e.y+e.height]}e.exports=u,u.prototype.render=function(){for(var t,e=this,r=[],n=arguments.length;n--;)r[n]=arguments[n];return r.length&&(t=this).update.apply(t,r),this.regl.attributes.preserveDrawingBuffer?this.draw():(this.dirty?null==this.planned&&(this.planned=o((function(){e.draw(),e.dirty=!0,e.planned=null}))):(this.draw(),this.dirty=!0,o((function(){e.dirty=!1}))),this)},u.prototype.update=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=0;n<e.length;n++)this.updateItem(n,e[n]);this.traces=this.traces.filter(Boolean);for(var i=[],a=0,o=0;o<this.traces.length;o++){for(var s=this.traces[o],l=this.traces[o].passes,c=0;c<l.length;c++)i.push(this.passes[l[c]]);s.passOffset=a,a+=s.passes.length}return(t=this.scatter).update.apply(t,i),this}},u.prototype.updateItem=function(t,e){var r=this.regl;if(null===e)return this.traces[t]=null,this;if(!e)return this;var n,o=i(e,{data:\"data items columns rows values dimensions samples x\",snap:\"snap cluster\",size:\"sizes size radius\",color:\"colors color fill fill-color fillColor\",opacity:\"opacity alpha transparency opaque\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",borderColor:\"borderColors borderColor bordercolor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range ranges databox dataBox\",viewport:\"viewport viewBox viewbox\",domain:\"domain domains area areas\",padding:\"pad padding paddings pads margin margins\",transpose:\"transpose transposed\",diagonal:\"diagonal diag 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u=0;u<s.columns;u++)s.bounds[u]=a(o.data[u],1)}o.range&&(s.range=o.range,n=s.range&&\"number\"!=typeof s.range[0]),o.domain&&(s.domain=o.domain);var d=!1;null!=o.padding&&(Array.isArray(o.padding)&&o.padding.length===s.columns&&\"number\"==typeof o.padding[o.padding.length-1]?(s.padding=o.padding.map(p),d=!0):s.padding=p(o.padding));var g=s.columns,m=s.count,v=s.viewport.width,y=s.viewport.height,x=s.viewport.x,b=s.viewport.y,_=v/g,w=y/g;s.passes=[];for(var T=0;T<g;T++)for(var k=0;k<g;k++)if((s.diagonal||k!==T)&&(s.upper||!(T>k))&&(s.lower||!(T<k))){var A=f(s.id,T,k),M=this.passes[A]||(this.passes[A]={});if(o.data&&(o.transpose?M.positions={x:{buffer:s.buffer,offset:k,count:m,stride:g},y:{buffer:s.buffer,offset:T,count:m,stride:g}}:M.positions={x:{buffer:s.buffer,offset:k*m,count:m},y:{buffer:s.buffer,offset:T*m,count:m}},M.bounds=h(s.bounds,T,k)),o.domain||o.viewport||o.data){var S=d?h(s.padding,T,k):s.padding;if(s.domain){var E=h(s.domain,T,k),L=E[0],C=E[1],P=E[2],I=E[3];M.viewport=[x+L*v+S[0],b+C*y+S[1],x+P*v-S[2],b+I*y-S[3]]}else M.viewport=[x+k*_+_*S[0],b+T*w+w*S[1],x+(k+1)*_-_*S[2],b+(T+1)*w-w*S[3]]}o.color&&(M.color=s.color),o.size&&(M.size=s.size),o.marker&&(M.marker=s.marker),o.borderSize&&(M.borderSize=s.borderSize),o.borderColor&&(M.borderColor=s.borderColor),o.opacity&&(M.opacity=s.opacity),o.range&&(M.range=n?h(s.range,T,k):s.range||M.bounds),s.passes.push(A)}return this},u.prototype.draw=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=[],i=0;i<e.length;i++)if(\"number\"==typeof e[i]){var a=this.traces[e[i]],o=a.passes,l=a.passOffset;n.push.apply(n,s(l,l+o.length))}else if(e[i].length){var c=e[i],u=this.traces[i],f=u.passes,h=u.passOffset;f=f.map((function(t,e){n[h+e]=c}))}(t=this.scatter).draw.apply(t,n)}else this.scatter.draw();return this},u.prototype.destroy=function(){return 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+       "/*!\n",
+       " * repeat-string <https://github.com/jonschlinkert/repeat-string>\n",
+       " *\n",
+       " * Copyright (c) 2014-2015, Jon Schlinkert.\n",
+       " * Licensed under the MIT License.\n",
+       " */\n",
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i=this._validate(t,e,r,n.local.invalidDate);return{yearType:(this.leapYear(i)?\"embolismic\":\"common\")+\" \"+[\"deficient\",\"regular\",\"complete\"][this.daysInYear(i)%10-3]}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t<=0?t+1:t,o=this.jdEpoch+this._delay1(a)+this._delay2(a)+r+1;if(e<7){for(var s=7;s<=this.monthsInYear(t);s++)o+=this.daysInMonth(t,s);for(s=1;s<e;s++)o+=this.daysInMonth(t,s)}else for(s=7;s<e;s++)o+=this.daysInMonth(t,s);return o},_delay1:function(t){var e=Math.floor((235*t-234)/19),r=12084+13753*e,n=29*e+Math.floor(r/25920);return o(3*(n+1),7)<3&&n++,n},_delay2:function(t){var e=this._delay1(t-1),r=this._delay1(t);return this._delay1(t+1)-r==356?2:r-e==382?1:0},fromJD:function(t){t=Math.floor(t)+.5;for(var e=Math.floor(98496*(t-this.jdEpoch)/35975351)-1;t>=this.toJD(-1===e?1:e+1,7,1);)e++;for(var r=t<this.toJD(e,1,1)?7:1;t>this.toJD(e,r,this.daysInMonth(e,r));)r++;var n=t-this.toJD(e,r,1)+1;return 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e=Math.floor((30*(t-this.jdEpoch)+10646)/10631);e=e<=0?e-1:e;var r=Math.min(12,Math.ceil((t-29-this.toJD(e,1,1))/29.5)+1),n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.islamic=a},{\"../main\":644,\"object-assign\":487}],636:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r<t.length;r++){var n=parseInt(t[r],10);if(Math.abs(n)>19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 682*((e.year()-(e.year()>0?474:473))%2820+474+38)%2816<682},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-(n.dayOfWeek()+1)%7,\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t-(t>=0?474:473),s=474+o(a,2820);return r+(e<=7?31*(e-1):30*(e-1)+6)+Math.floor((682*s-110)/2816)+365*(s-1)+1029983*Math.floor(a/2820)+this.jdEpoch-1},fromJD:function(t){var e=(t=Math.floor(t)+.5)-this.toJD(475,1,1),r=Math.floor(e/1029983),n=o(e,1029983),i=2820;if(1029982!==n){var a=Math.floor(n/366),s=o(n,366);i=Math.floor((2134*a+2816*s+2815)/1028522)+a+1}var l=i+2820*r+474;l=l<=0?l-1:l;var 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i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(i.year());return a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(i.year());return a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)},_g2tYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)}}),n.calendars.taiwan=o},{\"../main\":644,\"object-assign\":487}],642:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\"),a=n.instance();function 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n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"UmmAlQura\",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Umm al-Qura\",epochs:[\"BH\",\"AH\"],monthNames:[\"Al-Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' Al-Thani\",\"Jumada Al-Awwal\",\"Jumada Al-Thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-Ahad\",\"Yawm al-Ithnain\",\"Yawm al-Thal\\u0101th\\u0101\\u2019\",\"Yawm al-Arba\\u2018\\u0101\\u2019\",\"Yawm al-Kham\\u012bs\",\"Yawm al-Jum\\u2018a\",\"Yawm al-Sabt\"],dayNamesMin:[\"Ah\",\"Ith\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!0}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 355===this.daysInYear(e.year())},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){for(var e=0,r=1;r<=12;r++)e+=this.daysInMonth(t,r);return e},daysInMonth:function(t,e){for(var r=this._validate(t,e,this.minDay,n.local.invalidMonth).toJD()-24e5+.5,i=0,a=0;a<o.length;a++){if(o[a]>r)return o[i]-o[i-1];i++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate),a=12*(i.year()-1)+i.month()-15292;return i.day()+o[a-1]-1+24e5-.5},fromJD:function(t){for(var e=t-24e5+.5,r=0,n=0;n<o.length&&!(o[n]>e);n++)r++;var i=r+15292,a=Math.floor((i-1)/12),s=a+1,l=i-12*a,c=e-o[r-1]+1;return this.newDate(s,l,c)},isValid:function(t,e,r){var i=n.baseCalendar.prototype.isValid.apply(this,arguments);return i&&(i=(t=null!=t.year?t.year:t)>=1276&&t<=1500),i},_validate:function(t,e,r,i){var a=n.baseCalendar.prototype._validate.apply(this,arguments);if(a.year<1276||a.year>1500)throw i.replace(/\\{0\\}/,this.local.name);return a}}),n.calendars.ummalqura=a;var 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n=t(\"object-assign\");function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(c.local.differentCalendars||c.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,\"d\"===r||\"w\"===r){var n=t.toJD()+e*(\"w\"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+(\"y\"===r?e:0),o=t.monthOfYear()+(\"m\"===r?e:0);i=t.day();\"y\"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):\"m\"===r&&(!function(t){for(;o<t.minMonth;)a--,o+=t.monthsInYear(a);for(var e=t.monthsInYear(a);o>e-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw 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r,s,l=o(t,e),c=l.on,u=l.off.concat(l.explicitOff),f={},h=t._fullLayout.annotations;if(!c.length&&!u.length)return;for(r=0;r<c.length;r++)(s=a(t.layout,\"annotations\",h[c[r]])).modifyItem(\"visible\",!0),n.extendFlat(f,s.getUpdateObj());for(r=0;r<u.length;r++)(s=a(t.layout,\"annotations\",h[u[r]])).modifyItem(\"visible\",!1),n.extendFlat(f,s.getUpdateObj());return i.call(\"update\",t,{},f)}}},{\"../../lib\":803,\"../../plot_api/plot_template\":843,\"../../registry\":931}],652:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../color\");e.exports=function(t,e,r,a){a(\"opacity\");var o=a(\"bgcolor\"),s=a(\"bordercolor\"),l=i.opacity(s);a(\"borderpad\");var c=a(\"borderwidth\"),u=a(\"showarrow\");if(a(\"text\",u?\" \":r._dfltTitle.annotation),a(\"textangle\"),n.coerceFont(a,\"font\",r.font),a(\"width\"),a(\"align\"),a(\"height\")&&a(\"valign\"),u){var f,h,p=a(\"arrowside\");-1!==p.indexOf(\"end\")&&(f=a(\"arrowhead\"),h=a(\"arrowsize\")),-1!==p.indexOf(\"start\")&&(a(\"startarrowhead\",f),a(\"startarrowsize\",h)),a(\"arrowcolor\",l?e.bordercolor:i.defaultLine),a(\"arrowwidth\",2*(l&&c||1)),a(\"standoff\"),a(\"startstandoff\")}var d=a(\"hovertext\"),g=r.hoverlabel||{};if(d){var m=a(\"hoverlabel.bgcolor\",g.bgcolor||(i.opacity(o)?i.rgb(o):i.defaultLine)),v=a(\"hoverlabel.bordercolor\",g.bordercolor||i.contrast(m));n.coerceFont(a,\"hoverlabel.font\",{family:g.font.family,size:g.font.size,color:g.font.color||v})}a(\"captureevents\",!!d)}},{\"../../lib\":803,\"../color\":666}],653:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib/to_log_range\");e.exports=function(t,e,r,a){e=e||{};var o=\"log\"===r&&\"linear\"===e.type,s=\"linear\"===r&&\"log\"===e.type;if(o||s)for(var l,c,u=t._fullLayout.annotations,f=e._id.charAt(0),h=0;h<u.length;h++)l=u[h],c=\"annotations[\"+h+\"].\",l[f+\"ref\"]===e._id&&p(f),l[\"a\"+f+\"ref\"]===e._id&&p(\"a\"+f);function p(t){var r=l[t],s=null;s=o?i(r,e.range):Math.pow(10,r),n(s)||(s=null),a(c+t,s)}}},{\"../../lib/to_log_range\":831,\"fast-isnumeric\":249}],654:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../plots/cartesian/axes\"),a=t(\"../../plots/array_container_defaults\"),o=t(\"./common_defaults\"),s=t(\"./attributes\");function l(t,e,r){function a(r,i){return n.coerce(t,e,s,r,i)}var l=a(\"visible\"),c=a(\"clicktoshow\");if(l||c){o(t,e,r,a);for(var u=e.showarrow,f=[\"x\",\"y\"],h=[-10,-30],p={_fullLayout:r},d=0;d<2;d++){var g=f[d],m=i.coerceRef(t,e,p,g,\"\",\"paper\");if(\"paper\"!==m)i.getFromId(p,m)._annIndices.push(e._index);if(i.coercePosition(e,p,a,m,g,.5),u){var v=\"a\"+g,y=i.coerceRef(t,e,p,v,\"pixel\",[\"pixel\",\"paper\"]);\"pixel\"!==y&&y!==m&&(y=e[v]=\"pixel\");var x=\"pixel\"===y?h[d]:.4;i.coercePosition(e,p,a,y,v,x)}a(g+\"anchor\"),a(g+\"shift\")}if(n.noneOrAll(t,e,[\"x\",\"y\"]),u&&n.noneOrAll(t,e,[\"ax\",\"ay\"]),c){var b=a(\"xclick\"),_=a(\"yclick\");e._xclick=void 0===b?e.x:i.cleanPosition(b,p,e.xref),e._yclick=void 0===_?e.y:i.cleanPosition(_,p,e.yref)}}}e.exports=function(t,e){a(t,e,{name:\"annotations\",handleItemDefaults:l})}},{\"../../lib\":803,\"../../plots/array_container_defaults\":849,\"../../plots/cartesian/axes\":854,\"./attributes\":649,\"./common_defaults\":652}],655:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../registry\"),a=t(\"../../plots/plots\"),o=t(\"../../lib\"),s=o.strTranslate,l=t(\"../../plots/cartesian/axes\"),c=t(\"../color\"),u=t(\"../drawing\"),f=t(\"../fx\"),h=t(\"../../lib/svg_text_utils\"),p=t(\"../../lib/setcursor\"),d=t(\"../dragelement\"),g=t(\"../../plot_api/plot_template\").arrayEditor,m=t(\"./draw_arrow_head\");function v(t,e){var r=t._fullLayout.annotations[e]||{},n=l.getFromId(t,r.xref),i=l.getFromId(t,r.yref);n&&n.setScale(),i&&i.setScale(),x(t,r,e,!1,n,i)}function y(t,e,r,n,i){var a=i[r],o=i[r+\"ref\"],s=-1!==r.indexOf(\"y\"),c=\"domain\"===l.getRefType(o),u=s?n.h:n.w;return t?c?a+(s?-e:e)/t._length:t.p2r(t.r2p(a)+e):a+(s?-e:e)/u}function x(t,e,r,a,v,x){var b,_,w=t._fullLayout,T=t._fullLayout._size,k=t._context.edits;a?(b=\"annotation-\"+a,_=a+\".annotations\"):(b=\"annotation\",_=\"annotations\");var A=g(t.layout,_,e),M=A.modifyBase,S=A.modifyItem,E=A.getUpdateObj;w._infolayer.selectAll(\".\"+b+'[data-index=\"'+r+'\"]').remove();var L=\"clip\"+w._uid+\"_ann\"+r;if(e._input&&!1!==e.visible){var C={x:{},y:{}},P=+e.textangle||0,I=w._infolayer.append(\"g\").classed(b,!0).attr(\"data-index\",String(r)).style(\"opacity\",e.opacity),O=I.append(\"g\").classed(\"annotation-text-g\",!0),z=k[e.showarrow?\"annotationTail\":\"annotationPosition\"],D=e.captureevents||k.annotationText||z,R=O.append(\"g\").style(\"pointer-events\",D?\"all\":null).call(p,\"pointer\").on(\"click\",(function(){t._dragging=!1,t.emit(\"plotly_clickannotation\",Y(n.event))}));e.hovertext&&R.on(\"mouseover\",(function(){var r=e.hoverlabel,n=r.font,i=this.getBoundingClientRect(),a=t.getBoundingClientRect();f.loneHover({x0:i.left-a.left,x1:i.right-a.left,y:(i.top+i.bottom)/2-a.top,text:e.hovertext,color:r.bgcolor,borderColor:r.bordercolor,fontFamily:n.family,fontSize:n.size,fontColor:n.color},{container:w._hoverlayer.node(),outerContainer:w._paper.node(),gd:t})})).on(\"mouseout\",(function(){f.loneUnhover(w._hoverlayer.node())}));var F=e.borderwidth,B=e.borderpad,N=F+B,j=R.append(\"rect\").attr(\"class\",\"bg\").style(\"stroke-width\",F+\"px\").call(c.stroke,e.bordercolor).call(c.fill,e.bgcolor),U=e.width||e.height,V=w._topclips.selectAll(\"#\"+L).data(U?[0]:[]);V.enter().append(\"clipPath\").classed(\"annclip\",!0).attr(\"id\",L).append(\"rect\"),V.exit().remove();var q=e.font,H=w._meta?o.templateString(e.text,w._meta):e.text,G=R.append(\"text\").classed(\"annotation-text\",!0).text(H);k.annotationText?G.call(h.makeEditable,{delegate:R,gd:t}).call(W).on(\"edit\",(function(r){e.text=r,this.call(W),S(\"text\",r),v&&v.autorange&&M(v._name+\".autorange\",!0),x&&x.autorange&&M(x._name+\".autorange\",!0),i.call(\"_guiRelayout\",t,E())})):G.call(W)}else n.selectAll(\"#\"+L).remove();function Y(t){var n={index:r,annotation:e._input,fullAnnotation:e,event:t};return a&&(n.subplotId=a),n}function W(r){return r.call(u.font,q).attr({\"text-anchor\":{left:\"start\",right:\"end\"}[e.align]||\"middle\"}),h.convertToTspans(r,t,X),r}function X(){var r=G.selectAll(\"a\");1===r.size()&&r.text()===G.text()&&R.insert(\"a\",\":first-child\").attr({\"xlink:xlink:href\":r.attr(\"xlink:href\"),\"xlink:xlink:show\":r.attr(\"xlink:show\")}).style({cursor:\"pointer\"}).node().appendChild(j.node());var n=R.select(\".annotation-text-math-group\"),f=!n.empty(),g=u.bBox((f?n:G).node()),b=g.width,_=g.height,A=e.width||b,D=e.height||_,B=Math.round(A+2*N),q=Math.round(D+2*N);function H(t,e){return\"auto\"===e&&(e=t<1/3?\"left\":t>2/3?\"right\":\"center\"),{center:0,middle:0,left:.5,bottom:-.5,right:-.5,top:.5}[e]}for(var W=!1,X=[\"x\",\"y\"],Z=0;Z<X.length;Z++){var J,K,Q,$,tt,et=X[Z],rt=e[et+\"ref\"]||et,nt=e[\"a\"+et+\"ref\"],it={x:v,y:x}[et],at=(P+(\"x\"===et?0:-90))*Math.PI/180,ot=B*Math.cos(at),st=q*Math.sin(at),lt=Math.abs(ot)+Math.abs(st),ct=e[et+\"anchor\"],ut=e[et+\"shift\"]*(\"x\"===et?1:-1),ft=C[et],ht=l.getRefType(rt);if(it&&\"domain\"!==ht){var pt=it.r2fraction(e[et]);(pt<0||pt>1)&&(nt===rt?((pt=it.r2fraction(e[\"a\"+et]))<0||pt>1)&&(W=!0):W=!0),J=it._offset+it.r2p(e[et]),$=.5}else{var dt=\"domain\"===ht;\"x\"===et?(Q=e[et],J=dt?it._offset+it._length*Q:J=T.l+T.w*Q):(Q=1-e[et],J=dt?it._offset+it._length*Q:J=T.t+T.h*Q),$=e.showarrow?.5:Q}if(e.showarrow){ft.head=J;var gt=e[\"a\"+et];if(tt=ot*H(.5,e.xanchor)-st*H(.5,e.yanchor),nt===rt){var mt=l.getRefType(nt);\"domain\"===mt?(\"y\"===et&&(gt=1-gt),ft.tail=it._offset+it._length*gt):\"paper\"===mt?\"y\"===et?(gt=1-gt,ft.tail=T.t+T.h*gt):ft.tail=T.l+T.w*gt:ft.tail=it._offset+it.r2p(gt),K=tt}else ft.tail=J+gt,K=tt+gt;ft.text=ft.tail+tt;var vt=w[\"x\"===et?\"width\":\"height\"];if(\"paper\"===rt&&(ft.head=o.constrain(ft.head,1,vt-1)),\"pixel\"===nt){var yt=-Math.max(ft.tail-3,ft.text),xt=Math.min(ft.tail+3,ft.text)-vt;yt>0?(ft.tail+=yt,ft.text+=yt):xt>0&&(ft.tail-=xt,ft.text-=xt)}ft.tail+=ut,ft.head+=ut}else K=tt=lt*H($,ct),ft.text=J+tt;ft.text+=ut,tt+=ut,K+=ut,e[\"_\"+et+\"padplus\"]=lt/2+K,e[\"_\"+et+\"padminus\"]=lt/2-K,e[\"_\"+et+\"size\"]=lt,e[\"_\"+et+\"shift\"]=tt}if(W)R.remove();else{var bt=0,_t=0;if(\"left\"!==e.align&&(bt=(A-b)*(\"center\"===e.align?.5:1)),\"top\"!==e.valign&&(_t=(D-_)*(\"middle\"===e.valign?.5:1)),f)n.select(\"svg\").attr({x:N+bt-1,y:N+_t}).call(u.setClipUrl,U?L:null,t);else{var wt=N+_t-g.top,Tt=N+bt-g.left;G.call(h.positionText,Tt,wt).call(u.setClipUrl,U?L:null,t)}V.select(\"rect\").call(u.setRect,N,N,A,D),j.call(u.setRect,F/2,F/2,B-F,q-F),R.call(u.setTranslate,Math.round(C.x.text-B/2),Math.round(C.y.text-q/2)),O.attr({transform:\"rotate(\"+P+\",\"+C.x.text+\",\"+C.y.text+\")\"});var kt,At=function(r,n){I.selectAll(\".annotation-arrow-g\").remove();var l=C.x.head,f=C.y.head,h=C.x.tail+r,p=C.y.tail+n,g=C.x.text+r,b=C.y.text+n,_=o.rotationXYMatrix(P,g,b),w=o.apply2DTransform(_),A=o.apply2DTransform2(_),L=+j.attr(\"width\"),z=+j.attr(\"height\"),D=g-.5*L,F=D+L,B=b-.5*z,N=B+z,U=[[D,B,D,N],[D,N,F,N],[F,N,F,B],[F,B,D,B]].map(A);if(!U.reduce((function(t,e){return t^!!o.segmentsIntersect(l,f,l+1e6,f+1e6,e[0],e[1],e[2],e[3])}),!1)){U.forEach((function(t){var e=o.segmentsIntersect(h,p,l,f,t[0],t[1],t[2],t[3]);e&&(h=e.x,p=e.y)}));var V=e.arrowwidth,q=e.arrowcolor,H=e.arrowside,G=I.append(\"g\").style({opacity:c.opacity(q)}).classed(\"annotation-arrow-g\",!0),Y=G.append(\"path\").attr(\"d\",\"M\"+h+\",\"+p+\"L\"+l+\",\"+f).style(\"stroke-width\",V+\"px\").call(c.stroke,c.rgb(q));if(m(Y,H,e),k.annotationPosition&&Y.node().parentNode&&!a){var W=l,X=f;if(e.standoff){var Z=Math.sqrt(Math.pow(l-h,2)+Math.pow(f-p,2));W+=e.standoff*(h-l)/Z,X+=e.standoff*(p-f)/Z}var 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n.coerce(t,e,s,r,i)}function c(t){var n=t+\"axis\",a={_fullLayout:{}};return a._fullLayout[n]=r[n],i.coercePosition(e,a,l,t,t,.5)}l(\"visible\")&&(o(t,e,a.fullLayout,l),c(\"x\"),c(\"y\"),c(\"z\"),n.noneOrAll(t,e,[\"x\",\"y\",\"z\"]),e.xref=\"x\",e.yref=\"y\",e.zref=\"z\",l(\"xanchor\"),l(\"yanchor\"),l(\"xshift\"),l(\"yshift\"),e.showarrow&&(e.axref=\"pixel\",e.ayref=\"pixel\",l(\"ax\",-10),l(\"ay\",-30),n.noneOrAll(t,e,[\"ax\",\"ay\"])))}e.exports=function(t,e,r){a(t,e,{name:\"annotations\",handleItemDefaults:l,fullLayout:r.fullLayout})}},{\"../../lib\":803,\"../../plots/array_container_defaults\":849,\"../../plots/cartesian/axes\":854,\"../annotations/common_defaults\":652,\"./attributes\":658}],661:[function(t,e,r){\"use strict\";var n=t(\"../annotations/draw\").drawRaw,i=t(\"../../plots/gl3d/project\"),a=[\"x\",\"y\",\"z\"];e.exports=function(t){for(var e=t.fullSceneLayout,r=t.dataScale,o=e.annotations,s=0;s<o.length;s++){for(var l=o[s],c=!1,u=0;u<3;u++){var 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g={xcalendar:p(d(\"x\"))},m=i.extendFlat({},g,{ycalendar:p(d(\"y\"))}),v=i.extendFlat({},m,{zcalendar:p(d(\"z\"))}),y=p([\"Sets the calendar system to use for `range` and `tick0`\",\"if this is a date axis. 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B,V,q,H,G,Y,W,X,Z,J,K,Q,$,tt=[],et=[],rt={hLinePoint:null,vLinePoint:null},nt=!1;if(Array.isArray(e))for(S=\"array\",q=0;q<e.length;q++)(G=t.calcdata[e[q].curveNumber||0])&&(Y=G[0].trace,\"skip\"!==G[0].trace.hoverinfo&&(et.push(G),\"h\"===Y.orientation&&(nt=!0)));else{for(H=0;H<t.calcdata.length;H++)G=t.calcdata[H],\"skip\"!==(Y=G[0].trace).hoverinfo&&v.isTraceInSubplots(Y,s)&&(et.push(G),\"h\"===Y.orientation&&(nt=!0));var it,at;if(!e.target)it=\"xpx\"in e?e.xpx:b[0]._length/2,at=\"ypx\"in e?e.ypx:_[0]._length/2;else{if(!1===c.triggerHandler(t,\"plotly_beforehover\",e))return;var ot=e.composedPath&&e.composedPath()[0];ot||(ot=e.target);var st=ot.getBoundingClientRect();it=e.clientX-st.left,at=e.clientY-st.top,l._calcInverseTransform(t);var lt=o.apply3DTransform(l._invTransform)(it,at);if(it=lt[0],at=lt[1],it<0||it>b[0]._length||at<0||at>_[0]._length)return d.unhoverRaw(t,e)}if(e.pointerX=it+b[0]._offset,e.pointerY=at+_[0]._offset,B=\"xval\"in e?v.flat(s,e.xval):v.p2c(b,it),V=\"yval\"in e?v.flat(s,e.yval):v.p2c(_,at),!i(B[0])||!i(V[0]))return o.warn(\"Fx.hover failed\",e,t),d.unhoverRaw(t,e)}var ct=1/0;function ut(t,r){for(H=0;H<et.length;H++)if((G=et[H])&&G[0]&&G[0].trace&&!0===(Y=G[0].trace).visible&&0!==Y._length&&-1===[\"carpet\",\"contourcarpet\"].indexOf(Y._module.name)){if(\"splom\"===Y.type?W=s[X=0]:(W=v.getSubplot(Y),X=s.indexOf(W)),Z=S,v.isUnifiedHover(Z)&&(Z=Z.charAt(0)),Q={cd:G,trace:Y,xa:b[X],ya:_[X],maxHoverDistance:P,maxSpikeDistance:O,index:!1,distance:Math.min(ct,P),spikeDistance:1/0,xSpike:void 0,ySpike:void 0,color:p.defaultLine,name:Y.name,x0:void 0,x1:void 0,y0:void 0,y1:void 0,xLabelVal:void 0,yLabelVal:void 0,zLabelVal:void 0,text:void 0},l[W]&&(Q.subplot=l[W]._subplot),l._splomScenes&&l._splomScenes[Y.uid]&&(Q.scene=l._splomScenes[Y.uid]),$=tt.length,\"array\"===Z){var n=e[H];\"pointNumber\"in n?(Q.index=n.pointNumber,Z=\"closest\"):(Z=\"\",\"xval\"in n&&(J=n.xval,Z=\"x\"),\"yval\"in 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x=y[0];i(x.x0)&&i(x.y0)&&(h=ht(x),(!rt.hLinePoint||rt.hLinePoint.spikeDistance>h.spikeDistance)&&(rt.hLinePoint=h))}}}}}function ft(t,e,r){for(var n,i=null,a=1/0,o=0;o<t.length;o++)n=t[o].spikeDistance,r&&0===o&&(n=-1/0),n<=a&&n<=e&&(i=t[o],a=n);return i}function ht(t){return t?{xa:t.xa,ya:t.ya,x:void 0!==t.xSpike?t.xSpike:(t.x0+t.x1)/2,y:void 0!==t.ySpike?t.ySpike:(t.y0+t.y1)/2,distance:t.distance,spikeDistance:t.spikeDistance,curveNumber:t.trace.index,color:t.color,pointNumber:t.index}:null}ut();var pt={fullLayout:l,container:l._hoverlayer,event:e},dt=t._spikepoints,gt={vLinePoint:rt.vLinePoint,hLinePoint:rt.hLinePoint};t._spikepoints=gt;var mt=function(){tt.sort((function(t,e){return t.distance-e.distance})),tt=function(t,e){for(var r=e.charAt(0),n=[],i=[],a=[],o=0;o<t.length;o++){var s=t[o];m.traceIs(s.trace,\"bar-like\")||m.traceIs(s.trace,\"box-violin\")?a.push(s):s.trace[r+\"period\"]?i.push(s):n.push(s)}return n.concat(i).concat(a)}(tt,S)};mt();var vt=S.charAt(0),yt=(\"x\"===vt||\"y\"===vt)&&tt[0]&&L[tt[0].trace.type];if(g&&0!==O&&0!==tt.length){var xt=ft(tt.filter((function(t){return t.ya.showspikes})),O,yt);rt.hLinePoint=ht(xt);var bt=ft(tt.filter((function(t){return t.xa.showspikes})),O,yt);rt.vLinePoint=ht(bt)}if(0===tt.length){var _t=d.unhoverRaw(t,e);return!g||null===rt.hLinePoint&&null===rt.vLinePoint||F(dt)&&R(t,rt,pt),_t}g&&F(dt)&&R(t,rt,pt);if(v.isXYhover(Z)&&0!==tt[0].length&&\"splom\"!==tt[0].trace.type){var wt=tt[0],Tt=(tt=E[wt.trace.type]?tt.filter((function(t){return t.trace.index===wt.trace.index})):[wt]).length,kt=N(\"x\",wt,l),At=N(\"y\",wt,l);ut(kt,At);var Mt,St=[],Et={},Lt=0,Ct=function(t){var e=E[t.trace.type]?C(t):t.trace.index;if(Et[e]){var r=Et[e]-1,n=St[r];r>0&&Math.abs(t.distance)<Math.abs(n.distance)&&(St[r]=t)}else Lt++,Et[e]=Lt,St.push(t)};for(Mt=0;Mt<Tt;Mt++)Ct(tt[Mt]);for(Mt=tt.length-1;Mt>Tt-1;Mt--)Ct(tt[Mt]);tt=St,mt()}var Pt=t._hoverdata,It=[],Ot=j(t),zt=U(t);for(q=0;q<tt.length;q++){var Dt=tt[q],Rt=v.makeEventData(Dt,Dt.trace,Dt.cd);if(!1!==Dt.hovertemplate){var Ft=!1;Dt.cd[Dt.index]&&Dt.cd[Dt.index].ht&&(Ft=Dt.cd[Dt.index].ht),Dt.hovertemplate=Ft||Dt.trace.hovertemplate||!1}if(Dt.xa&&Dt.ya){var Bt=Dt.x0+Dt.xa._offset,Nt=Dt.x1+Dt.xa._offset,jt=Dt.y0+Dt.ya._offset,Ut=Dt.y1+Dt.ya._offset,Vt=Math.min(Bt,Nt),qt=Math.max(Bt,Nt),Ht=Math.min(jt,Ut),Gt=Math.max(jt,Ut);Rt.bbox={x0:Vt+zt,x1:qt+zt,y0:Ht+Ot,y1:Gt+Ot}}Dt.eventData=[Rt],It.push(Rt)}t._hoverdata=It;var Yt=\"y\"===S&&(et.length>1||tt.length>1)||\"closest\"===S&&nt&&tt.length>1,Wt=p.combine(l.plot_bgcolor||p.background,l.paper_bgcolor),Xt=I(tt,{gd:t,hovermode:S,rotateLabels:Yt,bgColor:Wt,container:l._hoverlayer,outerContainer:l._paper.node(),commonLabelOpts:l.hoverlabel,hoverdistance:l.hoverdistance});v.isUnifiedHover(S)||(!function(t,e,r){var n,i,a,o,s,l,c,u=0,f=1,h=t.size(),p=new Array(h),d=0;function g(t){var e=t[0],r=t[t.length-1];if(i=e.pmin-e.pos-e.dp+e.size,a=r.pos+r.dp+r.size-e.pmax,i>.01){for(s=t.length-1;s>=0;s--)t[s].dp+=i;n=!1}if(!(a<.01)){if(i<-.01){for(s=t.length-1;s>=0;s--)t[s].dp-=a;n=!1}if(n){var c=0;for(o=0;o<t.length;o++)(l=t[o]).pos+l.dp+l.size>e.pmax&&c++;for(o=t.length-1;o>=0&&!(c<=0);o--)(l=t[o]).pos>e.pmax-1&&(l.del=!0,c--);for(o=0;o<t.length&&!(c<=0);o++)if((l=t[o]).pos<e.pmin+1)for(l.del=!0,c--,a=2*l.size,s=t.length-1;s>=0;s--)t[s].dp-=a;for(o=t.length-1;o>=0&&!(c<=0);o--)(l=t[o]).pos+l.dp+l.size>e.pmax&&(l.del=!0,c--)}}}t.each((function(t){var n=t[e],i=\"x\"===n._id.charAt(0),a=n.range;0===d&&a&&a[0]>a[1]!==i&&(f=-1),p[d++]=[{datum:t,traceIndex:t.trace.index,dp:0,pos:t.pos,posref:t.posref,size:t.by*(i?T:1)/2,pmin:0,pmax:i?r.width:r.height}]})),p.sort((function(t,e){return t[0].posref-e[0].posref||f*(e[0].traceIndex-t[0].traceIndex)}));for(;!n&&u<=h;){for(u++,n=!0,o=0;o<p.length-1;){var m=p[o],v=p[o+1],y=m[m.length-1],x=v[0];if((i=y.pos+y.dp+y.size-x.pos-x.dp+x.size)>.01&&y.pmin===x.pmin&&y.pmax===x.pmax){for(s=v.length-1;s>=0;s--)v[s].dp+=i;for(m.push.apply(m,v),p.splice(o+1,1),c=0,s=m.length-1;s>=0;s--)c+=m[s].dp;for(a=c/m.length,s=m.length-1;s>=0;s--)m[s].dp-=a;n=!1}else o++}p.forEach(g)}for(o=p.length-1;o>=0;o--){var b=p[o];for(s=b.length-1;s>=0;s--){var _=b[s],w=_.datum;w.offset=_.dp,w.del=_.del}}}(Xt,Yt?\"xa\":\"ya\",l),z(Xt,Yt,l._invScaleX,l._invScaleY));if(e.target&&e.target.tagName){var Zt=m.getComponentMethod(\"annotations\",\"hasClickToShow\")(t,It);f(n.select(e.target),Zt?\"pointer\":\"\")}if(!e.target||a||!function(t,e,r){if(!r||r.length!==t._hoverdata.length)return!0;for(var n=r.length-1;n>=0;n--){var i=r[n],a=t._hoverdata[n];if(i.curveNumber!==a.curveNumber||String(i.pointNumber)!==String(a.pointNumber)||String(i.pointNumbers)!==String(a.pointNumbers))return!0}return!1}(t,0,Pt))return;Pt&&t.emit(\"plotly_unhover\",{event:e,points:Pt});t.emit(\"plotly_hover\",{event:e,points:t._hoverdata,xaxes:b,yaxes:_,xvals:B,yvals:V})}(t,e,r,a)}))},r.loneHover=function(t,e){var r=!0;Array.isArray(t)||(r=!1,t=[t]);var i=e.gd,a=j(i),o=U(i),s=I(t.map((function(t){var r=t._x0||t.x0||t.x||0,n=t._x1||t.x1||t.x||0,s=t._y0||t.y0||t.y||0,l=t._y1||t.y1||t.y||0,c=t.eventData;if(c){var u=Math.min(r,n),f=Math.max(r,n),h=Math.min(s,l),d=Math.max(s,l),g=t.trace;if(m.traceIs(g,\"gl3d\")){var v=i._fullLayout[g.scene]._scene.container,y=v.offsetLeft,x=v.offsetTop;u+=y,f+=y,h+=x,d+=x}c.bbox={x0:u+o,x1:f+o,y0:h+a,y1:d+a},e.inOut_bbox&&e.inOut_bbox.push(c.bbox)}else c=!1;return{color:t.color||p.defaultLine,x0:t.x0||t.x||0,x1:t.x1||t.x||0,y0:t.y0||t.y||0,y1:t.y1||t.y||0,xLabel:t.xLabel,yLabel:t.yLabel,zLabel:t.zLabel,text:t.text,name:t.name,idealAlign:t.idealAlign,borderColor:t.borderColor,fontFamily:t.fontFamily,fontSize:t.fontSize,fontColor:t.fontColor,nameLength:t.nameLength,textAlign:t.textAlign,trace:t.trace||{index:0,hoverinfo:\"\"},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:t.hovertemplate||!1,hovertemplateLabels:t.hovertemplateLabels||!1,eventData:c}})),{gd:i,hovermode:\"closest\",rotateLabels:!1,bgColor:e.bgColor||p.background,container:n.select(e.container),outerContainer:e.outerContainer||e.container}),l=0,c=0;return s.sort((function(t,e){return t.y0-e.y0})).each((function(t,r){var n=t.y0-t.by/2;t.offset=n-5<l?l-n+5:0,l=n+t.by+t.offset,r===e.anchorIndex&&(c=t.offset)})).each((function(t){t.offset-=c})),z(s,!1,i._fullLayout._invScaleX,i._fullLayout._invScaleY),r?s:s.node()};var P=/<extra>([\\s\\S]*)<\\/extra>/;function I(t,e){var r=e.gd,i=r._fullLayout,a=e.hovermode,c=e.rotateLabels,f=e.bgColor,d=e.container,g=e.outerContainer,w=e.commonLabelOpts||{},T=e.fontFamily||y.HOVERFONT,k=e.fontSize||y.HOVERFONTSIZE,A=t[0],E=A.xa,L=A.ya,P=a.charAt(0),I=A[P+\"Label\"],z=g.getBoundingClientRect(),D=z.top,R=z.width,F=z.height,B=void 0!==I&&A.distance<=e.hoverdistance&&(\"x\"===a||\"y\"===a);if(B){var N,j,U=!0;for(N=0;N<t.length;N++)if(U&&void 0===t[N].zLabel&&(U=!1),j=t[N].hoverinfo||t[N].trace.hoverinfo){var V=Array.isArray(j)?j:j.split(\"+\");if(-1===V.indexOf(\"all\")&&-1===V.indexOf(a)){B=!1;break}}U&&(B=!1)}var q=d.selectAll(\"g.axistext\").data(B?[0]:[]);if(q.enter().append(\"g\").classed(\"axistext\",!0),q.exit().remove(),q.each((function(){var t=n.select(this),e=o.ensureSingle(t,\"path\",\"\",(function(t){t.style({\"stroke-width\":\"1px\"})})),l=o.ensureSingle(t,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),c=w.bgcolor||p.defaultLine,f=w.bordercolor||p.contrast(c),d=p.contrast(c),g={family:w.font.family||T,size:w.font.size||k,color:w.font.color||d};e.style({fill:c,stroke:f}),l.text(I).call(h.font,g).call(u.positionText,0,0).call(u.convertToTspans,r),t.attr(\"transform\",\"\");var m,v,y=l.node().getBoundingClientRect();if(\"x\"===a){var x=\"top\"===E.side?\"-\":\"\";l.attr(\"text-anchor\",\"middle\").call(u.positionText,0,\"top\"===E.side?D-y.bottom-M-S:D-y.top+M+S),m=E._offset+(A.x0+A.x1)/2,v=L._offset+(\"top\"===E.side?0:L._length);var b=y.width/2+S;m<b?(m=b,e.attr(\"d\",\"M-\"+(b-M)+\",0L-\"+(b-2*M)+\",\"+x+M+\"H\"+(S+y.width/2)+\"v\"+x+(2*S+y.height)+\"H-\"+b+\"V\"+x+M+\"Z\")):m>i.width-b?(m=i.width-b,e.attr(\"d\",\"M\"+(b-M)+\",0L\"+b+\",\"+x+M+\"v\"+x+(2*S+y.height)+\"H-\"+b+\"V\"+x+M+\"H\"+(b-2*M)+\"Z\")):e.attr(\"d\",\"M0,0L\"+M+\",\"+x+M+\"H\"+(S+y.width/2)+\"v\"+x+(2*S+y.height)+\"H-\"+(S+y.width/2)+\"V\"+x+M+\"H-\"+M+\"Z\")}else{var _,C,P;\"right\"===L.side?(_=\"start\",C=1,P=\"\",m=E._offset+E._length):(_=\"end\",C=-1,P=\"-\",m=E._offset),v=L._offset+(A.y0+A.y1)/2,l.attr(\"text-anchor\",_),e.attr(\"d\",\"M0,0L\"+P+M+\",\"+M+\"V\"+(S+y.height/2)+\"h\"+P+(2*S+y.width)+\"V-\"+(S+y.height/2)+\"H\"+P+M+\"V-\"+M+\"Z\");var O,z=y.height/2,R=D-y.top-z,F=\"clip\"+i._uid+\"commonlabel\"+L._id;if(m<y.width+2*S+M){O=\"M-\"+(M+S)+\"-\"+z+\"h-\"+(y.width-S)+\"V\"+z+\"h\"+(y.width-S)+\"Z\";var B=y.width-m+S;u.positionText(l,B,R),\"end\"===_&&l.selectAll(\"tspan\").each((function(){var 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r=e.currentTarget;r.setAttribute(\"data-attr\",\"zoom\"),r.setAttribute(\"data-val\",\"reset\"),f(t,e),r.setAttribute(\"data-attr\",\"resetLastSave\"),p(t,e),x(t,\"geo\"),x(t,\"mapbox\")}},u.toggleSpikelines={name:\"toggleSpikelines\",title:function(t){return c(t,\"Toggle Spike Lines\")},icon:o.spikeline,attr:\"_cartesianSpikesEnabled\",val:\"on\",click:function(t){var e=t._fullLayout,r=e._cartesianSpikesEnabled;e._cartesianSpikesEnabled=\"on\"===r?\"off\":\"on\",n.call(\"_guiRelayout\",t,function(t){for(var e=\"on\"===t._fullLayout._cartesianSpikesEnabled,r=a.list(t,null,!0),n={},i=0;i<r.length;i++){var o=r[i];n[o._name+\".showspikes\"]=!!e||o._showSpikeInitial}return n}(t))}},u.resetViewMapbox={name:\"resetViewMapbox\",_cat:\"resetView\",title:function(t){return c(t,\"Reset view\")},attr:\"reset\",icon:o.home,click:function(t){x(t,\"mapbox\")}},u.zoomInMapbox={name:\"zoomInMapbox\",_cat:\"zoomin\",title:function(t){return c(t,\"Zoom 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n=t(\"../../lib\"),i=t(\"../color\"),a=t(\"../../plot_api/plot_template\"),o=t(\"./attributes\");e.exports=function(t,e){var r=t.modebar||{},s=a.newContainer(e,\"modebar\");function l(t,e){return n.coerce(r,s,o,t,e)}l(\"orientation\"),l(\"bgcolor\",i.addOpacity(e.paper_bgcolor,.5));var c=i.contrast(i.rgb(e.modebar.bgcolor));l(\"color\",i.addOpacity(c,.3)),l(\"activecolor\",i.addOpacity(c,.7)),l(\"uirevision\",e.uirevision),l(\"add\"),l(\"remove\")}},{\"../../lib\":803,\"../../plot_api/plot_template\":843,\"../color\":666,\"./attributes\":725}],729:[function(t,e,r){\"use strict\";e.exports={moduleType:\"component\",name:\"modebar\",layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),manage:t(\"./manage\")}},{\"./attributes\":725,\"./defaults\":728,\"./manage\":730}],730:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axis_ids\"),i=t(\"../../traces/scatter/subtypes\"),a=t(\"../../registry\"),o=t(\"../fx/helpers\").isUnifiedHover,s=t(\"./modebar\"),l=t(\"./buttons\"),c=t(\"./constants\").DRAW_MODES;e.exports=function(t){var e=t._fullLayout,r=t._context,u=e._modeBar;if(r.displayModeBar||r.watermark){if(!Array.isArray(r.modeBarButtonsToRemove))throw new Error([\"*modeBarButtonsToRemove* configuration options\",\"must be an array.\"].join(\" \"));if(!Array.isArray(r.modeBarButtonsToAdd))throw new Error([\"*modeBarButtonsToAdd* configuration options\",\"must be an array.\"].join(\" \"));var f,h=r.modeBarButtons;f=Array.isArray(h)&&h.length?function(t){for(var e=0;e<t.length;e++)for(var r=t[e],n=0;n<r.length;n++){var i=r[n];if(\"string\"==typeof i){if(void 0===l[i])throw new Error([\"*modeBarButtons* configuration options\",\"invalid button name\"].join(\" \"));t[e][n]=l[i]}}return t}(h):!r.displayModeBar&&r.watermark?[]:function(t){var e=t._fullLayout,r=t._fullData,s=t._context;function u(t,e){if(\"string\"==typeof e){if(e.toLowerCase()===t.toLowerCase())return!0}else{var r=e.name,n=e._cat||e.name;if(r===t||n===t.toLowerCase())return!0}return!1}var f=e.modebar.add;\"string\"==typeof f&&(f=[f]);var h=e.modebar.remove;\"string\"==typeof h&&(h=[h]);var p=s.modeBarButtonsToAdd.concat(f.filter((function(t){for(var e=0;e<s.modeBarButtonsToRemove.length;e++)if(u(t,s.modeBarButtonsToRemove[e]))return!1;return!0}))),d=s.modeBarButtonsToRemove.concat(h.filter((function(t){for(var e=0;e<s.modeBarButtonsToAdd.length;e++)if(u(t,s.modeBarButtonsToAdd[e]))return!1;return!0}))),g=e._has(\"cartesian\"),m=e._has(\"gl3d\"),v=e._has(\"geo\"),y=e._has(\"pie\"),x=e._has(\"funnelarea\"),b=e._has(\"gl2d\"),_=e._has(\"ternary\"),w=e._has(\"mapbox\"),T=e._has(\"polar\"),k=e._has(\"sankey\"),A=function(t){for(var e=n.list({_fullLayout:t},null,!0),r=0;r<e.length;r++)if(!e[r].fixedrange)return!1;return!0}(e),M=o(e.hovermode),S=[];function 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t.match(n.segmentRE).forEach((function(t){var a=e[t.charAt(0)].drawn;if(void 0!==a){var o=t.substr(1).match(n.paramRE);!o||o.length<a||r.push(i.cleanNumber(o[a]))}})),r},r.getDataToPixel=function(t,e,n,i){var a,o=t._fullLayout._size;if(e)if(\"domain\"===i)a=function(t){return e._length*(n?1-t:t)+e._offset};else{var s=r.shapePositionToRange(e);a=function(t){return e._offset+e.r2p(s(t,!0))},\"date\"===e.type&&(a=r.decodeDate(a))}else a=n?function(t){return o.t+o.h*(1-t)}:function(t){return o.l+o.w*t};return a},r.getPixelToData=function(t,e,n,i){var a,o=t._fullLayout._size;if(e)if(\"domain\"===i)a=function(t){var r=(t-e._offset)/e._length;return n?1-r:r};else{var s=r.rangeToShapePosition(e);a=function(t){return s(e.p2r(t-e._offset))}}else a=n?function(t){return 1-(t-o.t)/o.h}:function(t){return(t-o.l)/o.w};return a},r.roundPositionForSharpStrokeRendering=function(t,e){var r=1===Math.round(e%2),n=Math.round(t);return r?n+.5:n},r.makeOptionsAndPlotinfo=function(t,e){var r=t._fullLayout.shapes[e]||{},n=t._fullLayout._plots[r.xref+r.yref];return!!n?n._hadPlotinfo=!0:(n={},r.xref&&\"paper\"!==r.xref&&(n.xaxis=t._fullLayout[r.xref+\"axis\"]),r.yref&&\"paper\"!==r.yref&&(n.yaxis=t._fullLayout[r.yref+\"axis\"])),n.xsizemode=r.xsizemode,n.ysizemode=r.ysizemode,n.xanchor=r.xanchor,n.yanchor=r.yanchor,{options:r,plotinfo:n}}},{\"../../lib\":803,\"./constants\":748}],758:[function(t,e,r){\"use strict\";var n=t(\"./draw\");e.exports={moduleType:\"component\",name:\"shapes\",layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),supplyDrawNewShapeDefaults:t(\"./draw_newshape/defaults\"),includeBasePlot:t(\"../../plots/cartesian/include_components\")(\"shapes\"),calcAutorange:t(\"./calc_autorange\"),draw:n.draw,drawOne:n.drawOne}},{\"../../plots/cartesian/include_components\":867,\"./attributes\":746,\"./calc_autorange\":747,\"./defaults\":749,\"./draw\":750,\"./draw_newshape/defaults\":753}],759:[function(t,e,r){\"use strict\";var n=t(\"../../plots/font_attributes\"),i=t(\"../../plots/pad_attributes\"),a=t(\"../../lib/extend\").extendDeepAll,o=t(\"../../plot_api/edit_types\").overrideAll,s=t(\"../../plots/animation_attributes\"),l=t(\"../../plot_api/plot_template\").templatedArray,c=t(\"./constants\"),u=l(\"step\",{visible:{valType:\"boolean\",dflt:!0},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\"},value:{valType:\"string\"},execute:{valType:\"boolean\",dflt:!0}});e.exports=o(l(\"slider\",{visible:{valType:\"boolean\",dflt:!0},active:{valType:\"number\",min:0,dflt:0},steps:u,lenmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"fraction\"},len:{valType:\"number\",min:0,dflt:1},x:{valType:\"number\",min:-2,max:3,dflt:0},pad:a(i({editType:\"arraydraw\"}),{},{t:{dflt:20}}),xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\"},y:{valType:\"number\",min:-2,max:3,dflt:0},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},transition:{duration:{valType:\"number\",min:0,dflt:150},easing:{valType:\"enumerated\",values:s.transition.easing.values,dflt:\"cubic-in-out\"}},currentvalue:{visible:{valType:\"boolean\",dflt:!0},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\"},offset:{valType:\"number\",dflt:10},prefix:{valType:\"string\"},suffix:{valType:\"string\"},font:n({})},font:n({}),activebgcolor:{valType:\"color\",dflt:c.gripBgActiveColor},bgcolor:{valType:\"color\",dflt:c.railBgColor},bordercolor:{valType:\"color\",dflt:c.railBorderColor},borderwidth:{valType:\"number\",min:0,dflt:c.railBorderWidth},ticklen:{valType:\"number\",min:0,dflt:c.tickLength},tickcolor:{valType:\"color\",dflt:c.tickColor},tickwidth:{valType:\"number\",min:0,dflt:1},minorticklen:{valType:\"number\",min:0,dflt:c.minorTickLength}}),\"arraydraw\",\"from-root\")},{\"../../lib/extend\":793,\"../../plot_api/edit_types\":836,\"../../plot_api/plot_template\":843,\"../../plots/animation_attributes\":848,\"../../plots/font_attributes\":883,\"../../plots/pad_attributes\":916,\"./constants\":760}],760:[function(t,e,r){\"use strict\";e.exports={name:\"sliders\",containerClassName:\"slider-container\",groupClassName:\"slider-group\",inputAreaClass:\"slider-input-area\",railRectClass:\"slider-rail-rect\",railTouchRectClass:\"slider-rail-touch-rect\",gripRectClass:\"slider-grip-rect\",tickRectClass:\"slider-tick-rect\",inputProxyClass:\"slider-input-proxy\",labelsClass:\"slider-labels\",labelGroupClass:\"slider-label-group\",labelClass:\"slider-label\",currentValueClass:\"slider-current-value\",railHeight:5,menuIndexAttrName:\"slider-active-index\",autoMarginIdRoot:\"slider-\",minWidth:30,minHeight:30,textPadX:40,arrowOffsetX:4,railRadius:2,railWidth:5,railBorder:4,railBorderWidth:1,railBorderColor:\"#bec8d9\",railBgColor:\"#f8fafc\",railInset:8,stepInset:10,gripRadius:10,gripWidth:20,gripHeight:20,gripBorder:20,gripBorderWidth:1,gripBorderColor:\"#bec8d9\",gripBgColor:\"#f6f8fa\",gripBgActiveColor:\"#dbdde0\",labelPadding:8,labelOffset:0,tickWidth:1,tickColor:\"#333\",tickOffset:25,tickLength:7,minorTickOffset:25,minorTickColor:\"#333\",minorTickLength:4,currentValuePadding:8,currentValueInset:0}},{}],761:[function(t,e,r){\"use 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r=x(y,e,t.label),n=r.node()&&o.bBox(r.node())||{width:0,height:0},i=c.lineCount(r);u.currentValueMaxWidth=Math.max(u.currentValueMaxWidth,Math.ceil(n.width)),u.currentValueHeight=Math.max(u.currentValueHeight,Math.ceil(n.height)),u.currentValueMaxLines=Math.max(u.currentValueMaxLines,i)})),u.currentValueTotalHeight=u.currentValueHeight+e.currentvalue.offset,y.remove()}u.height=u.currentValueTotalHeight+f.tickOffset+e.ticklen+f.labelOffset+u.labelHeight+e.pad.t+e.pad.b;var b=\"left\";s.isRightAnchor(e)&&(u.lx-=u.outerLength,b=\"right\"),s.isCenterAnchor(e)&&(u.lx-=u.outerLength/2,b=\"center\");var w=\"top\";s.isBottomAnchor(e)&&(u.ly-=u.height,w=\"bottom\"),s.isMiddleAnchor(e)&&(u.ly-=u.height/2,w=\"middle\"),u.outerLength=Math.ceil(u.outerLength),u.height=Math.ceil(u.height),u.lx=Math.round(u.lx),u.ly=Math.round(u.ly);var T={y:e.y,b:u.height*g[w],t:u.height*d[w]};\"fraction\"===e.lenmode?(T.l=0,T.xl=e.x-e.len*d[b],T.r=0,T.xr=e.x+e.len*g[b]):(T.x=e.x,T.l=u.outerLength*d[b],T.r=u.outerLength*g[b]),i.autoMargin(t,m(e),T)}function x(t,e,r){if(e.currentvalue.visible){var n,i,a=e._dims;switch(e.currentvalue.xanchor){case\"right\":n=a.inputAreaLength-f.currentValueInset-a.currentValueMaxWidth,i=\"left\";break;case\"center\":n=.5*a.inputAreaLength,i=\"middle\";break;default:n=f.currentValueInset,i=\"left\"}var l=s.ensureSingle(t,\"text\",f.labelClass,(function(t){t.attr({\"text-anchor\":i,\"data-notex\":1})})),u=e.currentvalue.prefix?e.currentvalue.prefix:\"\";if(\"string\"==typeof r)u+=r;else{var h=e.steps[e.active].label,d=e._gd._fullLayout._meta;d&&(h=s.templateString(h,d)),u+=h}e.currentvalue.suffix&&(u+=e.currentvalue.suffix),l.call(o.font,e.currentvalue.font).text(u).call(c.convertToTspans,e._gd);var g=c.lineCount(l),m=(a.currentValueMaxLines+1-g)*e.currentvalue.font.size*p;return c.positionText(l,n,m),l}}function b(t,e,r){s.ensureSingle(t,\"rect\",f.gripRectClass,(function(n){n.call(A,e,t,r).style(\"pointer-events\",\"all\")})).attr({width:f.gripWidth,height:f.gripHeight,rx:f.gripRadius,ry:f.gripRadius}).call(a.stroke,r.bordercolor).call(a.fill,r.bgcolor).style(\"stroke-width\",r.borderwidth+\"px\")}function _(t,e,r){var n=s.ensureSingle(t,\"text\",f.labelClass,(function(t){t.attr({\"text-anchor\":\"middle\",\"data-notex\":1})})),i=e.step.label,a=r._gd._fullLayout._meta;return a&&(i=s.templateString(i,a)),n.call(o.font,r.font).text(i).call(c.convertToTspans,r._gd),n}function w(t,e){var r=s.ensureSingle(t,\"g\",f.labelsClass),i=e._dims,a=r.selectAll(\"g.\"+f.labelGroupClass).data(i.labelSteps);a.enter().append(\"g\").classed(f.labelGroupClass,!0),a.exit().remove(),a.each((function(t){var r=n.select(this);r.call(_,t,e),o.setTranslate(r,E(e,t.fraction),f.tickOffset+e.ticklen+e.font.size*p+f.labelOffset+i.currentValueTotalHeight)}))}function T(t,e,r,n,i){var a=Math.round(n*(r._stepCount-1)),o=r._visibleSteps[a]._index;o!==r.active&&k(t,e,r,o,!0,i)}function k(t,e,r,n,a,o){var s=r.active;r.active=n,u(t.layout,f.name,r).applyUpdate(\"active\",n);var l=r.steps[r.active];e.call(S,r,o),e.call(x,r),t.emit(\"plotly_sliderchange\",{slider:r,step:r.steps[r.active],interaction:a,previousActive:s}),l&&l.method&&a&&(e._nextMethod?(e._nextMethod.step=l,e._nextMethod.doCallback=a,e._nextMethod.doTransition=o):(e._nextMethod={step:l,doCallback:a,doTransition:o},e._nextMethodRaf=window.requestAnimationFrame((function(){var r=e._nextMethod.step;r.method&&(r.execute&&i.executeAPICommand(t,r.method,r.args),e._nextMethod=null,e._nextMethodRaf=null)}))))}function A(t,e,r){var i=r.node(),o=n.select(e);function s(){return r.data()[0]}function l(){var t=s();e.emit(\"plotly_sliderstart\",{slider:t});var l=r.select(\".\"+f.gripRectClass);n.event.stopPropagation(),n.event.preventDefault(),l.call(a.fill,t.activebgcolor);var c=L(t,n.mouse(i)[0]);function u(){var t=s(),a=L(t,n.mouse(i)[0]);T(e,r,t,a,!1)}function h(){var t=s();t._dragging=!1,l.call(a.fill,t.bgcolor),o.on(\"mouseup\",null),o.on(\"mousemove\",null),o.on(\"touchend\",null),o.on(\"touchmove\",null),e.emit(\"plotly_sliderend\",{slider:t,step:t.steps[t.active]})}T(e,r,t,c,!0),t._dragging=!0,o.on(\"mousemove\",u),o.on(\"touchmove\",u),o.on(\"mouseup\",h),o.on(\"touchend\",h)}t.on(\"mousedown\",l),t.on(\"touchstart\",l)}function M(t,e){var r=t.selectAll(\"rect.\"+f.tickRectClass).data(e._visibleSteps),i=e._dims;r.enter().append(\"rect\").classed(f.tickRectClass,!0),r.exit().remove(),r.attr({width:e.tickwidth+\"px\",\"shape-rendering\":\"crispEdges\"}),r.each((function(t,r){var s=r%i.labelStride==0,l=n.select(this);l.attr({height:s?e.ticklen:e.minorticklen}).call(a.fill,e.tickcolor),o.setTranslate(l,E(e,r/(e._stepCount-1))-.5*e.tickwidth,(s?f.tickOffset:f.minorTickOffset)+i.currentValueTotalHeight)}))}function S(t,e,r){for(var 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o=e.length===r.length;if(!i&&!o)return{fullReplot:!0,calc:!0};var s,l,c=T.traceFlags();c.arrays={},c.nChanges=0,c.nChangesAnim=0;var u={getValObject:function(t){var e=f.getTraceValObject(l,t);return!l._module.animatable&&e.anim&&(e.anim=!1),e},flags:c,immutable:n,transition:i,newDataRevision:a,gd:t},p={};for(s=0;s<e.length;s++)if(r[s]){if(l=r[s]._fullInput,h.hasMakesDataTransform(l)&&(l=r[s]),p[l.uid])continue;p[l.uid]=1,it(e[s]._fullInput,l,[],u)}(c.calc||c.plot)&&(c.fullReplot=!0);i&&c.nChanges&&c.nChangesAnim&&(c.anim=c.nChanges===c.nChangesAnim&&o?\"all\":\"some\");return c}(t,c,v,x,b,A);if(X(t)&&(k.layoutReplot=!0),S.calc||k.calc){t.calcdata=void 0;for(var E=Object.getOwnPropertyNames(y),C=0;C<E.length;C++){var P=E[C],I=P.substring(0,5);if(\"xaxis\"===I||\"yaxis\"===I){var O=y[P]._emptyCategories;O&&O()}}}else h.supplyDefaultsUpdateCalc(t.calcdata,v);var z=[];if(a&&(t._transitionData={},h.createTransitionData(t),z.push((function(){return 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t.dtick=e>.3?\"D2\":\"D1\"}else\"category\"===t.type||\"multicategory\"===t.type?(t.tick0=0,t.dtick=Math.ceil(Math.max(e,1))):At(t)?(t.tick0=0,r=1,t.dtick=ot(e,r,at)):(t.tick0=0,r=n(10),t.dtick=ot(e,r,$));if(0===t.dtick&&(t.dtick=1),!i(t.dtick)&&\"string\"!=typeof t.dtick){var f=t.dtick;throw t.dtick=1,\"ax.dtick error: \"+String(f)}},V.tickIncrement=function(t,e,r,a){var o=r?-1:1;if(i(e))return s.increment(t,o*e);var l=e.charAt(0),c=o*Number(e.substr(1));if(\"M\"===l)return s.incrementMonth(t,c,a);if(\"L\"===l)return Math.log(Math.pow(10,t)+c)/Math.LN10;if(\"D\"===l){var u=\"D2\"===e?it:nt,f=t+.01*o,h=s.roundUp(s.mod(f,1),u,r);return Math.floor(f)+Math.log(n.round(Math.pow(10,h),1))/Math.LN10}throw\"unrecognized dtick \"+String(e)},V.tickFirst=function(t,e){var r=t.r2l||Number,a=s.simpleMap(t.range,r,void 0,void 0,e),o=a[1]<a[0],l=o?Math.floor:Math.ceil,c=X(a)[0],u=t.dtick,f=r(t.tick0);if(i(u)){var 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h=s.simpleMap(t.range,t.r2l),p=(Math.abs(h[1]-h[0])-(t._lBreaks||0))/1e4;for(a=0;a<t.ticktext.length&&!(Math.abs(e-f(t.tickvals[a]))<p);a++);if(a<t.ticktext.length)return o.text=String(t.ticktext[a]),o}function d(n){if(void 0===n)return!0;if(r)return\"none\"===n;var i={first:t._tmin,last:t._tmax}[n];return\"all\"!==n&&e!==i}var g=r?\"never\":\"none\"!==t.exponentformat&&d(t.showexponent)?\"hide\":\"\";if(\"date\"===u?function(t,e,r,n){var a=t._tickround,o=r&&t.hoverformat||V.getTickFormat(t);n&&(a=i(a)?4:{y:\"m\",m:\"d\",d:\"M\",M:\"S\",S:4}[a]);var l,c=s.formatDate(e.x,o,a,t._dateFormat,t.calendar,t._extraFormat),u=c.indexOf(\"\\n\");-1!==u&&(l=c.substr(u+1),c=c.substr(0,u));n&&(\"00:00:00\"===c||\"00:00\"===c?(c=l,l=\"\"):8===c.length&&(c=c.replace(/:00$/,\"\")));if(l)if(r)\"d\"===a?c+=\", \"+l:c=l+(c?\", \"+c:\"\");else if(t._inCalcTicks&&t._prevDateHead===l){var f=St(t),h=t._realSide||t.side;(!f&&\"top\"===h||f&&\"bottom\"===h)&&(c+=\"<br> \")}else 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a=n._fullLayout._zoomlayer.selectAll(\".select-outline-\"+r.id);if(a&&n._fullLayout._drawing){var o=v(a,t);o&&i.call(\"_guiRelayout\",n,{shapes:o}),n._fullLayout._drawing=!1}}r.selection={},r.selection.selectionDefs=t.selectionDefs=[],r.selection.mergedPolygons=t.mergedPolygons=[]}function N(t,e,r,n){var i,a,o,s=[],l=e.map((function(t){return t._id})),c=r.map((function(t){return t._id}));for(o=0;o<t.calcdata.length;o++)if(!0===(a=(i=t.calcdata[o])[0].trace).visible&&a._module&&a._module.selectPoints)if(!n||a.subplot!==n&&a.geo!==n)if(\"splom\"===a.type&&a._xaxes[l[0]]&&a._yaxes[c[0]]){var u=h(a._module,i,e[0],r[0]);u.scene=t._fullLayout._splomScenes[a.uid],s.push(u)}else if(\"sankey\"===a.type){var f=h(a._module,i,e[0],r[0]);s.push(f)}else{if(-1===l.indexOf(a.xaxis))continue;if(-1===c.indexOf(a.yaxis))continue;s.push(h(a._module,i,_(t,a.xaxis),_(t,a.yaxis)))}else s.push(h(a._module,i,e[0],r[0]));return s;function h(t,e,r,n){return{_module:t,cd:e,xaxis:r,yaxis:n}}}function j(t){var e=t.searchInfo.cd[0].trace,r=t.pointNumber,n=t.pointNumbers,i=n.length>0?n[0]:r;return!!e.selectedpoints&&e.selectedpoints.indexOf(i)>-1}function U(t,e,r){var n,a,o,s;for(n=0;n<e.length;n++){var l=e[n].cd[0].trace._fullInput,c=t._fullLayout._tracePreGUI[l.uid]||{};void 0===c.selectedpoints&&(c.selectedpoints=l._input.selectedpoints||null)}if(r){var u=r.points||[];for(n=0;n<e.length;n++)(s=e[n].cd[0].trace)._input.selectedpoints=s._fullInput.selectedpoints=[],s._fullInput!==s&&(s.selectedpoints=[]);for(n=0;n<u.length;n++){var f=u[n],h=f.data,p=f.fullData;f.pointIndices?([].push.apply(h.selectedpoints,f.pointIndices),s._fullInput!==s&&[].push.apply(p.selectedpoints,f.pointIndices)):(h.selectedpoints.push(f.pointIndex),s._fullInput!==s&&p.selectedpoints.push(f.pointIndex))}}else for(n=0;n<e.length;n++)delete(s=e[n].cd[0].trace).selectedpoints,delete s._input.selectedpoints,s._fullInput!==s&&delete s._fullInput.selectedpoints;var d=!1;for(n=0;n<e.length;n++){s=(o=(a=e[n]).cd)[0].trace,i.traceIs(s,\"regl\")&&(d=!0);var g=a._module,m=g.styleOnSelect||g.style;m&&(m(t,o,o[0].node3),o[0].nodeRangePlot3&&m(t,o,o[0].nodeRangePlot3))}d&&(w(t),T(t))}function V(t,e){if(Array.isArray(t))for(var r=e.cd,n=e.cd[0].trace,i=0;i<t.length;i++)t[i]=l(t[i],n,r);return t}function q(t,e){for(var r=[],n=0;n<t.length;n++){r[n]=[];for(var i=0;i<t[n].length;i++){r[n][i]=[],r[n][i][0]=i?\"L\":\"M\";for(var a=0;a<t[n][i].length;a++)r[n][i].push(t[n][i][a])}e||r[n].push([\"Z\",r[n][0][1],r[n][0][2]])}return r}e.exports={prepSelect:function(t,e,r,i,l){var c=u(l),v=f(l),x=p(l),_=h(l),w=d(l),T=\"drawcircle\"===l,E=\"drawline\"===l||T,L=i.gd,z=L._fullLayout,D=z._zoomlayer,j=i.element.getBoundingClientRect(),H=i.plotinfo,G=I(H),Y=e-j.left,W=r-j.top;z._calcInverseTransform(L);var X=y.apply3DTransform(z._invTransform)(Y,W);Y=X[0],W=X[1];var 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n=t(\"@plotly/d3\"),i=t(\"d3-geo\"),a=i.geoPath,o=i.geoDistance,s=t(\"d3-geo-projection\"),l=t(\"../../registry\"),c=t(\"../../lib\"),u=c.strTranslate,f=t(\"../../components/color\"),h=t(\"../../components/drawing\"),p=t(\"../../components/fx\"),d=t(\"../plots\"),g=t(\"../cartesian/axes\"),m=t(\"../cartesian/autorange\").getAutoRange,v=t(\"../../components/dragelement\"),y=t(\"../cartesian/select\").prepSelect,x=t(\"../cartesian/select\").clearSelect,b=t(\"../cartesian/select\").selectOnClick,_=t(\"./zoom\"),w=t(\"./constants\"),T=t(\"../../lib/geo_location_utils\"),k=t(\"../../lib/topojson_utils\"),A=t(\"topojson-client\").feature;function 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i=t[n],a=i[0].trace;\"choropleth\"===a.type&&(this.hasChoropleth=!0),!0===a.visible&&a._length>0&&a._module.calcGeoJSON(i,e)}if(!this.updateProjection(t,e)){this.viewInitial&&this.scope===r.scope||this.saveViewInitial(r),this.scope=r.scope,this.updateBaseLayers(e,r),this.updateDims(e,r),this.updateFx(e,r),d.generalUpdatePerTraceModule(this.graphDiv,this,t,r);var o=this.layers.frontplot.select(\".scatterlayer\");this.dataPoints.point=o.selectAll(\".point\"),this.dataPoints.text=o.selectAll(\"text\"),this.dataPaths.line=o.selectAll(\".js-line\");var s=this.layers.backplot.select(\".choroplethlayer\");this.dataPaths.choropleth=s.selectAll(\"path\"),this.render()}},S.updateProjection=function(t,e){var r=this.graphDiv,n=e[this.id],l=e._size,u=n.domain,f=n.projection,h=n.lonaxis,p=n.lataxis,d=h._ax,g=p._ax,v=this.projection=function(t){var e=t.projection,r=e.type,n=w.projNames[r];n=\"geo\"+c.titleCase(n);for(var l=(i[n]||s[n])(),u=t._isSatellite?180*Math.acos(1/e.distance)/Math.PI:t._isClipped?w.lonaxisSpan[r]/2:null,f=[\"center\",\"rotate\",\"parallels\",\"clipExtent\"],h=function(t){return t?l:[]},p=0;p<f.length;p++){var d=f[p];\"function\"!=typeof l[d]&&(l[d]=h)}l.isLonLatOverEdges=function(t){if(null===l(t))return!0;if(u){var e=l.rotate();return o(t,[-e[0],-e[1]])>u*Math.PI/180}return!1},l.getPath=function(){return a().projection(l)},l.getBounds=function(t){return l.getPath().bounds(t)},l.precision(w.precision),t._isSatellite&&l.tilt(e.tilt).distance(e.distance);u&&l.clipAngle(u-w.clipPad);return l}(n),y=[[l.l+l.w*u.x[0],l.t+l.h*(1-u.y[1])],[l.l+l.w*u.x[1],l.t+l.h*(1-u.y[0])]],x=n.center||{},b=f.rotation||{},_=h.range||[],T=p.range||[];if(n.fitbounds){d._length=y[1][0]-y[0][0],g._length=y[1][1]-y[0][1],d.range=m(r,d),g.range=m(r,g);var k=(d.range[0]+d.range[1])/2,A=(g.range[0]+g.range[1])/2;if(n._isScoped)x={lon:k,lat:A};else if(n._isClipped){x={lon:k,lat:A},b={lon:k,lat:A,roll:b.roll};var M=f.type,S=w.lonaxisSpan[M]/2||180,L=w.lataxisSpan[M]/2||90;_=[k-S,k+S],T=[A-L,A+L]}else x={lon:k,lat:A},b={lon:k,lat:b.lat,roll:b.roll}}v.center([x.lon-b.lon,x.lat-b.lat]).rotate([-b.lon,-b.lat,b.roll]).parallels(f.parallels);var C=E(_,T);v.fitExtent(y,C);var P=this.bounds=v.getBounds(C),I=this.fitScale=v.scale(),O=v.translate();if(n.fitbounds){var z=v.getBounds(E(d.range,g.range)),D=Math.min((P[1][0]-P[0][0])/(z[1][0]-z[0][0]),(P[1][1]-P[0][1])/(z[1][1]-z[0][1]));isFinite(D)?v.scale(D*I):c.warn(\"Something went wrong during\"+this.id+\"fitbounds computations.\")}else v.scale(f.scale*I);var R=this.midPt=[(P[0][0]+P[1][0])/2,(P[0][1]+P[1][1])/2];if(v.translate([O[0]+(R[0]-O[0]),O[1]+(R[1]-O[1])]).clipExtent(P),n._isAlbersUsa){var F=v([x.lon,x.lat]),B=v.translate();v.translate([B[0]-(F[0]-B[0]),B[1]-(F[1]-B[1])])}},S.updateBaseLayers=function(t,e){var r=this,i=r.topojson,a=r.layers,o=r.basePaths;function s(t){return\"lonaxis\"===t||\"lataxis\"===t}function l(t){return Boolean(w.lineLayers[t])}function c(t){return Boolean(w.fillLayers[t])}var u=(this.hasChoropleth?w.layersForChoropleth:w.layers).filter((function(t){return l(t)||c(t)?e[\"show\"+t]:!s(t)||e[t].showgrid})),p=r.framework.selectAll(\".layer\").data(u,String);p.exit().each((function(t){delete a[t],delete o[t],n.select(this).remove()})),p.enter().append(\"g\").attr(\"class\",(function(t){return\"layer \"+t})).each((function(t){var e=a[t]=n.select(this);\"bg\"===t?r.bgRect=e.append(\"rect\").style(\"pointer-events\",\"all\"):s(t)?o[t]=e.append(\"path\").style(\"fill\",\"none\"):\"backplot\"===t?e.append(\"g\").classed(\"choroplethlayer\",!0):\"frontplot\"===t?e.append(\"g\").classed(\"scatterlayer\",!0):l(t)?o[t]=e.append(\"path\").style(\"fill\",\"none\").style(\"stroke-miterlimit\",2):c(t)&&(o[t]=e.append(\"path\").style(\"stroke\",\"none\"))})),p.order(),p.each((function(r){var n=o[r],a=w.layerNameToAdjective[r];\"frame\"===r?n.datum(w.sphereSVG):l(r)||c(r)?n.datum(A(i,i.objects[r])):s(r)&&n.datum(function(t,e,r){var n,i,a,o=e[t],s=w.scopeDefaults[e.scope];\"lonaxis\"===t?(n=s.lonaxisRange,i=s.lataxisRange,a=function(t,e){return[t,e]}):\"lataxis\"===t&&(n=s.lataxisRange,i=s.lonaxisRange,a=function(t,e){return[e,t]});var l={type:\"linear\",range:[n[0],n[1]-1e-6],tick0:o.tick0,dtick:o.dtick};g.setConvert(l,r);var c=g.calcTicks(l);e.isScoped||\"lonaxis\"!==t||c.pop();for(var u=c.length,f=new Array(u),h=0;h<u;h++)for(var p=c[h].x,d=f[h]=[],m=i[0];m<i[1]+2.5;m+=2.5)d.push(a(p,m));return{type:\"MultiLineString\",coordinates:f}}(r,e,t)).call(f.stroke,e[r].gridcolor).call(h.dashLine,\"\",e[r].gridwidth),l(r)?n.call(f.stroke,e[a+\"color\"]).call(h.dashLine,\"\",e[a+\"width\"]):c(r)&&n.call(f.fill,e[a+\"color\"])}))},S.updateDims=function(t,e){var r=this.bounds,n=(e.framewidth||0)/2,i=r[0][0]-n,a=r[0][1]-n,o=r[1][0]-i+n,s=r[1][1]-a+n;h.setRect(this.clipRect,i,a,o,s),this.bgRect.call(h.setRect,i,a,o,s).call(f.fill,e.bgcolor),this.xaxis._offset=i,this.xaxis._length=o,this.yaxis._offset=a,this.yaxis._length=s},S.updateFx=function(t,e){var r=this,i=r.graphDiv,a=r.bgRect,o=t.dragmode,s=t.clickmode;if(!r.isStatic){var u;\"select\"===o?u=function(t,e){(t.range={})[r.id]=[h([e.xmin,e.ymin]),h([e.xmax,e.ymax])]}:\"lasso\"===o&&(u=function(t,e,n){(t.lassoPoints={})[r.id]=n.filtered.map(h)});var f={element:r.bgRect.node(),gd:i,plotinfo:{id:r.id,xaxis:r.xaxis,yaxis:r.yaxis,fillRangeItems:u},xaxes:[r.xaxis],yaxes:[r.yaxis],subplot:r.id,clickFn:function(t){2===t&&x(i)}};\"pan\"===o?(a.node().onmousedown=null,a.call(_(r,e)),a.on(\"dblclick.zoom\",(function(){var t=r.viewInitial,e={};for(var n in 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v=n/(f[2]-f[0])*(l[2]-l[0])+l[0],y=i/(f[3]-f[1])*(l[3]-l[1])+l[1];c.boxInited||(c.boxStart[0]=v,c.boxStart[1]=y,c.dragStart[0]=n,c.dragStart[1]=i),c.boxEnd[0]=v,c.boxEnd[1]=y,c.boxInited=!0,c.boxEnabled||c.boxStart[0]===c.boxEnd[0]&&c.boxStart[1]===c.boxEnd[1]||(c.boxEnabled=!0);var x=Math.abs(c.dragStart[0]-n)<g,b=Math.abs(c.dragStart[1]-i)<g;if(!function(){for(var e=t.graphDiv._fullLayout._axisConstraintGroups,r=t.xaxis._id,n=t.yaxis._id,i=0;i<e.length;i++)if(-1!==e[i][r]){if(-1!==e[i][n])return!0;break}return!1}()||x&&b)x&&(c.boxEnd[0]=c.boxStart[0]),b&&(c.boxEnd[1]=c.boxStart[1]);else{a=c.boxEnd[0]-c.boxStart[0],s=c.boxEnd[1]-c.boxStart[1];var _=(l[3]-l[1])/(l[2]-l[0]);Math.abs(a*_)>Math.abs(s)?(c.boxEnd[1]=c.boxStart[1]+Math.abs(a)*_*(s>=0?1:-1),c.boxEnd[1]<l[1]?(c.boxEnd[1]=l[1],c.boxEnd[0]=c.boxStart[0]+(l[1]-c.boxStart[1])/Math.abs(_)):c.boxEnd[1]>l[3]&&(c.boxEnd[1]=l[3],c.boxEnd[0]=c.boxStart[0]+(l[3]-c.boxStart[1])/Math.abs(_))):(c.boxEnd[0]=c.boxStart[0]+Math.abs(s)/_*(a>=0?1:-1),c.boxEnd[0]<l[0]?(c.boxEnd[0]=l[0],c.boxEnd[1]=c.boxStart[1]+(l[0]-c.boxStart[0])*Math.abs(_)):c.boxEnd[0]>l[2]&&(c.boxEnd[0]=l[2],c.boxEnd[1]=c.boxStart[1]+(l[2]-c.boxStart[0])*Math.abs(_)))}}else c.boxEnabled?(a=c.boxStart[0]!==c.boxEnd[0],s=c.boxStart[1]!==c.boxEnd[1],a||s?(a&&(m(0,c.boxStart[0],c.boxEnd[0]),t.xaxis.autorange=!1),s&&(m(1,c.boxStart[1],c.boxEnd[1]),t.yaxis.autorange=!1),t.relayoutCallback()):t.glplot.setDirty(),c.boxEnabled=!1,c.boxInited=!1):c.boxInited&&(c.boxInited=!1);break;case\"pan\":c.boxEnabled=!1,c.boxInited=!1,e?(c.panning||(c.dragStart[0]=n,c.dragStart[1]=i),Math.abs(c.dragStart[0]-n)<d&&(n=c.dragStart[0]),Math.abs(c.dragStart[1]-i)<d&&(i=c.dragStart[1]),a=(h-n)*(l[2]-l[0])/(r.viewBox[2]-r.viewBox[0]),s=(p-i)*(l[3]-l[1])/(r.viewBox[3]-r.viewBox[1]),l[0]+=a,l[2]+=a,l[1]+=s,l[3]+=s,t.setRanges(l),c.panning=!0,c.lastInputTime=Date.now(),u(),t.cameraChanged(),t.handleAnnotations()):c.panning&&(c.panning=!1,t.relayoutCallback())}c.lastPos[0]=n,c.lastPos[1]=i}return c.mouseListener=n(e,f),e.addEventListener(\"touchstart\",(function(t){var r=a(t.changedTouches[0],e);f(0,r[0],r[1]),f(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener(\"touchmove\",(function(t){t.preventDefault();var r=a(t.changedTouches[0],e);f(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener(\"touchend\",(function(t){f(0,c.lastPos[0],c.lastPos[1]),t.preventDefault()}),!!s&&{passive:!1}),c.wheelListener=i(e,(function(e,n){if(!t.scrollZoom)return!1;var i=t.calcDataBox(),a=r.viewBox,o=c.lastPos[0],s=c.lastPos[1],l=Math.exp(5*n/(a[3]-a[1])),f=o/(a[2]-a[0])*(i[2]-i[0])+i[0],h=s/(a[3]-a[1])*(i[3]-i[1])+i[1];return i[0]=(i[0]-f)*l+f,i[2]=(i[2]-f)*l+f,i[1]=(i[1]-h)*l+h,i[3]=(i[3]-h)*l+h,t.setRanges(i),c.lastInputTime=Date.now(),u(),t.cameraChanged(),t.handleAnnotations(),t.relayoutCallback(),!0}),!0),c}},{\"../cartesian/constants\":861,\"has-passive-events\":444,\"mouse-change\":470,\"mouse-event-offset\":471,\"mouse-wheel\":473}],893:[function(t,e,r){\"use strict\";var n=t(\"../cartesian/axes\"),i=t(\"../../lib/str2rgbarray\");function a(t){this.scene=t,this.gl=t.gl,this.pixelRatio=t.pixelRatio,this.screenBox=[0,0,1,1],this.viewBox=[0,0,1,1],this.dataBox=[-1,-1,1,1],this.borderLineEnable=[!1,!1,!1,!1],this.borderLineWidth=[1,1,1,1],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.ticks=[[],[]],this.tickEnable=[!0,!0,!1,!1],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labels=[\"x\",\"y\"],this.labelEnable=[!0,!0,!1,!1],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelPad=[15,15,15,15],this.labelSize=[12,12],this.labelFont=[\"sans-serif\",\"sans-serif\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.title=\"\",this.titleEnable=!0,this.titleCenter=[0,0,0,0],this.titleAngle=0,this.titleColor=[0,0,0,1],this.titleFont=\"sans-serif\",this.titleSize=18,this.gridLineEnable=[!0,!0],this.gridLineColor=[[0,0,0,.5],[0,0,0,.5]],this.gridLineWidth=[1,1],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[1,1],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.static=this.scene.staticPlot}var o=a.prototype,s=[\"xaxis\",\"yaxis\"];o.merge=function(t){var e,r,n,a,o,l,c,u,f,h,p;for(this.titleEnable=!1,this.backgroundColor=i(t.plot_bgcolor),h=0;h<2;++h){var d=(e=s[h]).charAt(0);for(n=(r=t[this.scene[e]._name]).title.text===this.scene.fullLayout._dfltTitle[d]?\"\":r.title.text,p=0;p<=2;p+=2)this.labelEnable[h+p]=!1,this.labels[h+p]=n,this.labelColor[h+p]=i(r.title.font.color),this.labelFont[h+p]=r.title.font.family,this.labelSize[h+p]=r.title.font.size,this.labelPad[h+p]=this.getLabelPad(e,r),this.tickEnable[h+p]=!1,this.tickColor[h+p]=i((r.tickfont||{}).color),this.tickAngle[h+p]=\"auto\"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[h+p]=this.getTickPad(r),this.tickMarkLength[h+p]=0,this.tickMarkWidth[h+p]=r.tickwidth||0,this.tickMarkColor[h+p]=i(r.tickcolor),this.borderLineEnable[h+p]=!1,this.borderLineColor[h+p]=i(r.linecolor),this.borderLineWidth[h+p]=r.linewidth||0;c=this.hasSharedAxis(r),o=this.hasAxisInDfltPos(e,r)&&!c,l=this.hasAxisInAltrPos(e,r)&&!c,a=r.mirror||!1,u=c?-1!==String(a).indexOf(\"all\"):!!a,f=c?\"allticks\"===a:-1!==String(a).indexOf(\"ticks\"),o?this.labelEnable[h]=!0:l&&(this.labelEnable[h+2]=!0),o?this.tickEnable[h]=r.showticklabels:l&&(this.tickEnable[h+2]=r.showticklabels),(o||u)&&(this.borderLineEnable[h]=r.showline),(l||u)&&(this.borderLineEnable[h+2]=r.showline),(o||f)&&(this.tickMarkLength[h]=this.getTickMarkLength(r)),(l||f)&&(this.tickMarkLength[h+2]=this.getTickMarkLength(r)),this.gridLineEnable[h]=r.showgrid,this.gridLineColor[h]=i(r.gridcolor),this.gridLineWidth[h]=r.gridwidth,this.zeroLineEnable[h]=r.zeroline,this.zeroLineColor[h]=i(r.zerolinecolor),this.zeroLineWidth[h]=r.zerolinewidth}},o.hasSharedAxis=function(t){var e=this.scene,r=e.fullLayout._subplots.gl2d;return 0!==n.findSubplotsWithAxis(r,t).indexOf(e.id)},o.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},o.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},o.getLabelPad=function(t,e){var r=e.title.font.size,n=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?r*(1.5+(n?1:0))-10:r*(1.5+(n?.5:0))-10:\"yaxis\"===t?\"right\"===e.side?10+r*(1.5+(n?1:.5)):10+r*(1.5+(n?.5:0)):void 0},o.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},o.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},e.exports=function(t){return new a(t)}},{\"../../lib/str2rgbarray\":828,\"../cartesian/axes\":854}],894:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"./scene2d\"),a=t(\"../layout_attributes\"),o=t(\"../../constants/xmlns_namespaces\"),s=t(\"../cartesian/constants\"),l=t(\"../cartesian\"),c=t(\"../../components/fx/layout_attributes\"),u=t(\"../get_data\").getSubplotData;r.name=\"gl2d\",r.attr=[\"xaxis\",\"yaxis\"],r.idRoot=[\"x\",\"y\"],r.idRegex=s.idRegex,r.attrRegex=s.attrRegex,r.attributes=t(\"../cartesian/attributes\"),r.supplyLayoutDefaults=function(t,e,r){e._has(\"cartesian\")||l.supplyLayoutDefaults(t,e,r)},r.layoutAttrOverrides=n(l.layoutAttributes,\"plot\",\"from-root\"),r.baseLayoutAttrOverrides=n({plot_bgcolor:a.plot_bgcolor,hoverlabel:c.hoverlabel},\"plot\",\"nested\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,a=0;a<n.length;a++){var o=n[a],s=e._plots[o],l=u(r,\"gl2d\",o),c=s._scene2d;void 0===c&&(c=new i({id:o,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=c),c.plot(l,t.calcdata,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl2d||[],a=0;a<i.length;a++){var o=i[a],s=n._plots[o];if(s._scene2d){var c=u(t,\"gl2d\",o);0===c.length&&(s._scene2d.destroy(),delete n._plots[o])}}l.clean.apply(this,arguments)},r.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var i=e._plots[r[n]]._scene2d,a=i.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":a,x:0,y:0,width:\"100%\",height:\"100%\",preserveAspectRatio:\"none\"}),i.destroy()}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){e._plots[r[n]]._scene2d.updateFx(e.dragmode)}}},{\"../../components/fx/layout_attributes\":707,\"../../constants/xmlns_namespaces\":780,\"../../plot_api/edit_types\":836,\"../cartesian\":868,\"../cartesian/attributes\":852,\"../cartesian/constants\":861,\"../get_data\":891,\"../layout_attributes\":908,\"./scene2d\":895}],895:[function(t,e,r){\"use strict\";var n,i,a=t(\"../../registry\"),o=t(\"../../plots/cartesian/axes\"),s=t(\"../../components/fx\"),l=t(\"gl-plot2d\"),c=t(\"gl-spikes2d\"),u=t(\"gl-select-box\"),f=t(\"webgl-context\"),h=t(\"./convert\"),p=t(\"./camera\"),d=t(\"../../lib/show_no_webgl_msg\"),g=t(\"../cartesian/constraints\"),m=g.enforce,v=g.clean,y=t(\"../cartesian/autorange\").doAutoRange,x=t(\"../../components/dragelement/helpers\"),b=x.drawMode,_=x.selectMode,w=[\"xaxis\",\"yaxis\"],T=t(\"../cartesian/constants\").SUBPLOT_PATTERN;function k(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=h(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=c(this.glplot),this.selectBox=u(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}e.exports=k;var A=k.prototype;A.makeFramework=function(){if(this.staticPlot){if(!(i||(n=document.createElement(\"canvas\"),i=f({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=n,this.gl=i}else{var t=this.container.querySelector(\".gl-canvas-focus\"),e=f({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r);var a=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\";var o=this.mouseContainer=document.createElement(\"div\");o.style.position=\"absolute\",o.style[\"pointer-events\"]=\"auto\",this.pickCanvas=this.container.querySelector(\".gl-canvas-pick\");var s=this.container;s.appendChild(a),s.appendChild(o);var l=this;o.addEventListener(\"mouseout\",(function(){l.isMouseOver=!1,l.unhover()})),o.addEventListener(\"mouseover\",(function(){l.isMouseOver=!0}))},A.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a);for(var o=0,s=i-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var c=0;c<4;++c){var u=a[4*(r*o+l)+c];a[4*(r*o+l)+c]=a[4*(r*s+l)+c],a[4*(r*s+l)+c]=u}var f=document.createElement(\"canvas\");f.width=r,f.height=i;var h,p=f.getContext(\"2d\"),d=p.createImageData(r,i);switch(d.data.set(a),p.putImageData(d,0,0),t){case\"jpeg\":h=f.toDataURL(\"image/jpeg\");break;case\"webp\":h=f.toDataURL(\"image/webp\");break;default:h=f.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(n),h},A.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},A.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+\"\";return t},A.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(T),r=\"xaxis\"+e[1],n=\"yaxis\"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},A.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,i={},o=i[e._name+\".range\"]=e.range.slice(),s=i[r._name+\".range\"]=r.range.slice();i[e._name+\".autorange\"]=e.autorange,i[r._name+\".autorange\"]=r.autorange,a.call(\"_storeDirectGUIEdit\",t.layout,t._fullLayout._preGUI,i);var l=n[e._name];l.range=o,l.autorange=e.autorange;var c=n[r._name];c.range=s,c.autorange=r.autorange,i.lastInputTime=this.camera.lastInputTime,t.emit(\"plotly_relayout\",i)},A.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},A.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&a.getComponentMethod(\"annotations\",\"drawOne\")(t,r)}},A.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map((function(e){t[e].dispose(),delete t[e]})),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null}},A.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var s={_fullLayout:{_axisConstraintGroups:r._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis,_size:r._size}};v(s,this.xaxis),v(s,this.yaxis);var l,c,u=r._size,f=this.xaxis.domain,h=this.yaxis.domain;for(o.viewBox=[u.l+f[0]*u.w,u.b+h[0]*u.h,i-u.r-(1-f[1])*u.w,a-u.t-(1-h[1])*u.h],this.mouseContainer.style.width=u.w*(f[1]-f[0])+\"px\",this.mouseContainer.style.height=u.h*(h[1]-h[0])+\"px\",this.mouseContainer.height=u.h*(h[1]-h[0]),this.mouseContainer.style.left=u.l+f[0]*u.w+\"px\",this.mouseContainer.style.top=u.t+(1-h[1])*u.h+\"px\",c=0;c<2;++c)(l=this[w[c]])._length=o.viewBox[c+2]-o.viewBox[c],y(this.graphDiv,l),l.setScale();m(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},A.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,i=t.r2l,a=e.r2l;return[i(r[0]),a(n[0]),i(r[1]),a(n[1])]},A.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,i=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[i(t[1]),i(t[3])]},A.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if((i=t[n]).uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r];var l=e[r],c=this.traces[i.uid];c?c.update(i,l):(c=i._module.plot(this,i,l),this.traces[i.uid]=c)}this.glplot.objects.sort((function(t,e){return t._trace.index-e._trace.index}))},A.updateFx=function(t){_(t)||b(t)?(this.pickCanvas.style[\"pointer-events\"]=\"none\",this.mouseContainer.style[\"pointer-events\"]=\"none\"):(this.pickCanvas.style[\"pointer-events\"]=\"auto\",this.mouseContainer.style[\"pointer-events\"]=\"auto\"),this.mouseContainer.style.cursor=\"pan\"===t?\"move\":\"zoom\"===t?\"crosshair\":null},A.emitPointAction=function(t,e){for(var r,n=t.trace.uid,i=t.pointIndex,a=0;a<this.fullData.length;a++)this.fullData[a].uid===n&&(r=this.fullData[a]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:i,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,i),this.graphDiv.emit(e,{points:[o]})},A.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode){this.selectBox.enabled=!0;for(var c=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],u=0;u<2;u++)e.boxStart[u]===e.boxEnd[u]&&(c[u]=t.dataBox[u],c[u+2]=t.dataBox[u+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var f=i._size,h=this.xaxis.domain,p=this.yaxis.domain,d=(a=t.pick(o/t.pixelRatio+f.l+h[0]*f.w,l/t.pixelRatio-(f.t+(1-p[1])*f.h)))&&a.object._trace.handlePick(a);if(d&&n&&this.emitPointAction(d,\"plotly_click\"),a&&\"skip\"!==a.object._trace.hoverinfo&&i.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var g=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:a.dataCoord}),g.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(a.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(a.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,\"plotly_hover\");var m=this.fullData[g.trace.index]||{},v=g.pointIndex,y=s.castHoverinfo(m,i,v);if(y&&\"all\"!==y){var x=y.split(\"+\");-1===x.indexOf(\"x\")&&(g.traceCoord[0]=void 0),-1===x.indexOf(\"y\")&&(g.traceCoord[1]=void 0),-1===x.indexOf(\"z\")&&(g.traceCoord[2]=void 0),-1===x.indexOf(\"text\")&&(g.textLabel=void 0),-1===x.indexOf(\"name\")&&(g.name=void 0)}s.loneHover({x:g.screenCoord[0],y:g.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",g.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",g.traceCoord[1]),zLabel:g.traceCoord[2],text:g.textLabel,name:g.name,color:s.castHoverOption(m,v,\"bgcolor\")||g.color,borderColor:s.castHoverOption(m,v,\"bordercolor\"),fontFamily:s.castHoverOption(m,v,\"font.family\"),fontSize:s.castHoverOption(m,v,\"font.size\"),fontColor:s.castHoverOption(m,v,\"font.color\"),nameLength:s.castHoverOption(m,v,\"namelength\"),textAlign:s.castHoverOption(m,v,\"align\")},{container:this.svgContainer,gd:this.graphDiv})}}a||this.unhover(),t.draw()}},A.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),s.loneUnhover(this.svgContainer))},A.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../components/dragelement/helpers\":684,\"../../components/fx\":706,\"../../lib/show_no_webgl_msg\":825,\"../../plots/cartesian/axes\":854,\"../../registry\":931,\"../cartesian/autorange\":853,\"../cartesian/constants\":861,\"../cartesian/constraints\":862,\"./camera\":892,\"./convert\":893,\"gl-plot2d\":322,\"gl-select-box\":337,\"gl-spikes2d\":346,\"webgl-context\":629}],896:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"../../components/fx/layout_attributes\"),a=t(\"./scene\"),o=t(\"../get_data\").getSubplotData,s=t(\"../../lib\"),l=t(\"../../constants/xmlns_namespaces\");r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=r.attrRegex=s.counterRegex(\"scene\"),r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.baseLayoutAttrOverrides=n({hoverlabel:i.hoverlabel},\"plot\",\"nested\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl3d,i=0;i<n.length;i++){var s=n[i],l=o(r,\"gl3d\",s),c=e[s],u=c.camera,f=c._scene;f||(f=new a({id:s,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:u},e),c._scene=f),f.viewInitial||(f.viewInitial={up:{x:u.up.x,y:u.up.y,z:u.up.z},eye:{x:u.eye.x,y:u.eye.y,z:u.eye.z},center:{x:u.center.x,y:u.center.y,z:u.center.z}}),f.plot(l,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl3d||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(\".annotation-\"+o).remove())}},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=e._size,i=0;i<r.length;i++){var a=e[r[i]],o=a.domain,s=a._scene,c=s.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:l.svg,\"xlink:href\":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"}),s.destroy()}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=0;n<r.length;n++){e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}}},{\"../../components/fx/layout_attributes\":707,\"../../constants/xmlns_namespaces\":780,\"../../lib\":803,\"../../plot_api/edit_types\":836,\"../get_data\":891,\"./layout/attributes\":897,\"./layout/defaults\":901,\"./layout/layout_attributes\":902,\"./scene\":906}],897:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"subplotid\",dflt:\"scene\",editType:\"calc+clearAxisTypes\"}}},{}],898:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color\"),i=t(\"../../cartesian/layout_attributes\"),a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../plot_api/edit_types\").overrideAll;e.exports=o({visible:i.visible,showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:{text:i.title.text,font:i.title.font},type:a({},i.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autotypenumbers:i.autotypenumbers,autorange:i.autorange,rangemode:i.rangemode,range:a({},i.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],anim:!1}),tickmode:i.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,minexponent:i.minexponent,separatethousands:i.separatethousands,tickformat:i.tickformat,tickformatstops:i.tickformatstops,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth,_deprecated:{title:i._deprecated.title,titlefont:i._deprecated.titlefont}},\"plot\",\"from-root\")},{\"../../../components/color\":666,\"../../../lib/extend\":793,\"../../../plot_api/edit_types\":836,\"../../cartesian/layout_attributes\":869}],899:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"../../../plot_api/plot_template\"),o=t(\"./axis_attributes\"),s=t(\"../../cartesian/type_defaults\"),l=t(\"../../cartesian/axis_defaults\"),c=[\"xaxis\",\"yaxis\",\"zaxis\"];e.exports=function(t,e,r){var u,f;function h(t,e){return i.coerce(u,f,o,t,e)}for(var p=0;p<c.length;p++){var d=c[p];u=t[d]||{},(f=a.newContainer(e,d))._id=d[0]+r.scene,f._name=d,s(u,f,h,r),l(u,f,h,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noTickson:!0,noTicklabelmode:!0,noTicklabelposition:!0,noTicklabeloverflow:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),h(\"gridcolor\",n(f.color,r.bgColor,13600/187).toRgbString()),h(\"title.text\",d[0]),f.setScale=i.noop,h(\"showspikes\")&&(h(\"spikesides\"),h(\"spikethickness\"),h(\"spikecolor\",f.color)),h(\"showaxeslabels\"),h(\"showbackground\")&&h(\"backgroundcolor\")}}},{\"../../../lib\":803,\"../../../plot_api/plot_template\":843,\"../../cartesian/axis_defaults\":856,\"../../cartesian/type_defaults\":880,\"./axis_attributes\":898,tinycolor2:598}],900:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=0;r<3;++r){var o=e[a[r]];o.visible?(this.labels[r]=t._meta?i.templateString(o.title.text,t._meta):o.title.text,\"font\"in o.title&&(o.title.font.color&&(this.labelColor[r]=n(o.title.font.color)),o.title.font.family&&(this.labelFont[r]=o.title.font.family),o.title.font.size&&(this.labelSize[r]=o.title.font.size)),\"showline\"in o&&(this.lineEnable[r]=o.showline),\"linecolor\"in o&&(this.lineColor[r]=n(o.linecolor)),\"linewidth\"in o&&(this.lineWidth[r]=o.linewidth),\"showgrid\"in o&&(this.gridEnable[r]=o.showgrid),\"gridcolor\"in o&&(this.gridColor[r]=n(o.gridcolor)),\"gridwidth\"in o&&(this.gridWidth[r]=o.gridwidth),\"log\"===o.type?this.zeroEnable[r]=!1:\"zeroline\"in o&&(this.zeroEnable[r]=o.zeroline),\"zerolinecolor\"in o&&(this.zeroLineColor[r]=n(o.zerolinecolor)),\"zerolinewidth\"in o&&(this.zeroLineWidth[r]=o.zerolinewidth),\"ticks\"in o&&o.ticks?this.lineTickEnable[r]=!0:this.lineTickEnable[r]=!1,\"ticklen\"in o&&(this.lineTickLength[r]=this._defaultLineTickLength[r]=o.ticklen),\"tickcolor\"in o&&(this.lineTickColor[r]=n(o.tickcolor)),\"tickwidth\"in o&&(this.lineTickWidth[r]=o.tickwidth),\"tickangle\"in o&&(this.tickAngle[r]=\"auto\"===o.tickangle?-3600:Math.PI*-o.tickangle/180),\"showticklabels\"in o&&(this.tickEnable[r]=o.showticklabels),\"tickfont\"in o&&(o.tickfont.color&&(this.tickColor[r]=n(o.tickfont.color)),o.tickfont.family&&(this.tickFont[r]=o.tickfont.family),o.tickfont.size&&(this.tickSize[r]=o.tickfont.size)),\"mirror\"in o?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(o.mirror)?(this.lineTickMirror[r]=!0,this.lineMirror[r]=!0):!0===o.mirror?(this.lineTickMirror[r]=!1,this.lineMirror[r]=!0):(this.lineTickMirror[r]=!1,this.lineMirror[r]=!1):this.lineMirror[r]=!1,\"showbackground\"in o&&!1!==o.showbackground?(this.backgroundEnable[r]=!0,this.backgroundColor[r]=n(o.backgroundcolor)):this.backgroundEnable[r]=!1):(this.tickEnable[r]=!1,this.labelEnable[r]=!1,this.lineEnable[r]=!1,this.lineTickEnable[r]=!1,this.gridEnable[r]=!1,this.zeroEnable[r]=!1,this.backgroundEnable[r]=!1)}},e.exports=function(t,e){var r=new o;return r.merge(t,e),r}},{\"../../../lib\":803,\"../../../lib/str2rgbarray\":828}],901:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),i=t(\"../../../components/color\"),a=t(\"../../../registry\"),o=t(\"../../subplot_defaults\"),s=t(\"./axis_defaults\"),l=t(\"./layout_attributes\"),c=t(\"../../get_data\").getSubplotData;function u(t,e,r,n){for(var o=r(\"bgcolor\"),l=i.combine(o,n.paper_bgcolor),u=[\"up\",\"center\",\"eye\"],f=0;f<u.length;f++)r(\"camera.\"+u[f]+\".x\"),r(\"camera.\"+u[f]+\".y\"),r(\"camera.\"+u[f]+\".z\");r(\"camera.projection.type\");var h=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),p=r(\"aspectmode\",h?\"manual\":\"auto\");h||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===p&&(e.aspectmode=\"auto\"),t.aspectmode=e.aspectmode);var d=c(n.fullData,\"gl3d\",n.id);s(t,e,{font:n.font,scene:n.id,data:d,bgColor:l,calendar:n.calendar,autotypenumbersDflt:n.autotypenumbersDflt,fullLayout:n.fullLayout}),a.getComponentMethod(\"annotations3d\",\"handleDefaults\")(t,e,n);var g=n.getDfltFromLayout(\"dragmode\");if(!1!==g&&!g)if(g=\"orbit\",t.camera&&t.camera.up){var m=t.camera.up.x,v=t.camera.up.y,y=t.camera.up.z;0!==y&&(m&&v&&y?y/Math.sqrt(m*m+v*v+y*y)>.999&&(g=\"turntable\"):g=\"turntable\")}else g=\"turntable\";r(\"dragmode\",g),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}e.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:\"gl3d\",attributes:l,handleDefaults:u,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},autotypenumbersDflt:e.autotypenumbers,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},{\"../../../components/color\":666,\"../../../lib\":803,\"../../../registry\":931,\"../../get_data\":891,\"../../subplot_defaults\":925,\"./axis_defaults\":899,\"./layout_attributes\":902}],902:[function(t,e,r){\"use strict\";var n=t(\"./axis_attributes\"),i=t(\"../../domain\").attributes,a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../lib\").counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}e.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:i({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\",_deprecated:{cameraposition:{valType:\"info_array\",editType:\"camera\"}}}},{\"../../../lib\":803,\"../../../lib/extend\":793,\"../../domain\":882,\"./axis_attributes\":898}],903:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=[\"xaxis\",\"yaxis\",\"zaxis\"];function a(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}a.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},e.exports=function(t){var e=new a;return e.merge(t),e}},{\"../../../lib/str2rgbarray\":828}],904:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],c=0;c<3;++c){var u=s[a[c]];if(u._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(u._length)===1/0||isNaN(u._length))l[c]=[];else{u._input_range=u.range.slice(),u.range[0]=r[c].lo/t.dataScale[c],u.range[1]=r[c].hi/t.dataScale[c],u._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),u.range[0]===u.range[1]&&(u.range[0]-=1,u.range[1]+=1);var f=u.tickmode;if(\"auto\"===u.tickmode){u.tickmode=\"linear\";var h=u.nticks||i.constrain(u._length/40,4,9);n.autoTicks(u,Math.abs(u.range[1]-u.range[0])/h)}for(var p=n.calcTicks(u,{msUTC:!0}),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[c],\"date\"===u.type&&(p[d].text=p[d].text.replace(/\\<br\\>/g,\" \"));l[c]=p,u.tickmode=f}}e.ticks=l;for(c=0;c<3;++c){o[c]=.5*(t.glplot.bounds[0][c]+t.glplot.bounds[1][c]);for(d=0;d<2;++d)e.bounds[d][c]=t.glplot.bounds[d][c]}t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}(l)};var n=t(\"../../cartesian/axes\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"],o=[0,0,0]},{\"../../../lib\":803,\"../../cartesian/axes\":854}],905:[function(t,e,r){\"use strict\";function n(t,e){var r,n,i=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)i[n]+=t[4*r+n]*e[r];return i}e.exports=function(t,e){return n(t.projection,n(t.view,n(t.model,[e[0],e[1],e[2],1])))}},{}],906:[function(t,e,r){\"use strict\";var n,i,a=t(\"gl-plot3d\"),o=a.createCamera,s=a.createScene,l=t(\"webgl-context\"),c=t(\"has-passive-events\"),u=t(\"../../registry\"),f=t(\"../../lib\"),h=f.preserveDrawingBuffer(),p=t(\"../../plots/cartesian/axes\"),d=t(\"../../components/fx\"),g=t(\"../../lib/str2rgbarray\"),m=t(\"../../lib/show_no_webgl_msg\"),v=t(\"./project\"),y=t(\"./layout/convert\"),x=t(\"./layout/spikes\"),b=t(\"./layout/tick_marks\");function _(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var i=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");i.style.position=\"absolute\",i.style.top=i.style.left=\"0px\",i.style.width=i.style.height=\"100%\",i.style[\"z-index\"]=20,i.style[\"pointer-events\"]=\"none\",r.appendChild(i),this.svgContainer=i,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=y(e,e[this.id]),this.spikeOptions=x(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=u.getComponentMethod(\"annotations3d\",\"convert\"),this.drawAnnotations=u.getComponentMethod(\"annotations3d\",\"draw\"),this.initializeGLPlot()}var w=_.prototype;w.prepareOptions=function(){var t={canvas:this.canvas,gl:this.gl,glOptions:{preserveDrawingBuffer:h,premultipliedAlpha:!0,antialias:!0},container:this.container,axes:this.axesOptions,spikes:this.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:this.camera,pixelRatio:this.pixelRatio};if(this.staticMode){if(!(i||(n=document.createElement(\"canvas\"),i=l({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"error creating static canvas/context for image server\");t.gl=i,t.canvas=n}return t};var T=!0;w.tryCreatePlot=function(){var t=this.prepareOptions(),e=!0;try{this.glplot=s(t)}catch(r){if(this.staticMode||!T||h)e=!1;else{f.warn([\"webgl setup failed possibly due to\",\"false preserveDrawingBuffer config.\",\"The mobile/tablet device may not be detected by is-mobile module.\",\"Enabling preserveDrawingBuffer in second attempt to create webgl scene...\"].join(\" \"));try{h=t.glOptions.preserveDrawingBuffer=!0,this.glplot=s(t)}catch(r){h=t.glOptions.preserveDrawingBuffer=!1,e=!1}}}return T=!1,e},w.initializeGLCamera=function(){var t=this.fullSceneLayout.camera,e=\"orthographic\"===t.projection.type;this.camera=o(this.container,{center:[t.center.x,t.center.y,t.center.z],eye:[t.eye.x,t.eye.y,t.eye.z],up:[t.up.x,t.up.y,t.up.z],_ortho:e,zoomMin:.01,zoomMax:100,mode:\"orbit\"})},w.initializeGLPlot=function(){var t=this;if(t.initializeGLCamera(),!t.tryCreatePlot())return m(t);t.traces={},t.make4thDimension();var e=t.graphDiv,r=e.layout,n=function(){var e={};return t.isCameraChanged(r)&&(e[t.id+\".camera\"]=t.getCamera()),t.isAspectChanged(r)&&(e[t.id+\".aspectratio\"]=t.glplot.getAspectratio(),\"manual\"!==r[t.id].aspectmode&&(t.fullSceneLayout.aspectmode=r[t.id].aspectmode=e[t.id+\".aspectmode\"]=\"manual\")),e},i=function(t){if(!1!==t.fullSceneLayout.dragmode){var e=n();t.saveLayout(r),t.graphDiv.emit(\"plotly_relayout\",e)}};return t.glplot.canvas&&(t.glplot.canvas.addEventListener(\"mouseup\",(function(){i(t)})),t.glplot.canvas.addEventListener(\"wheel\",(function(r){if(e._context._scrollZoom.gl3d){if(t.camera._ortho){var n=r.deltaX>r.deltaY?1.1:1/1.1,a=t.glplot.getAspectratio();t.glplot.setAspectratio({x:n*a.x,y:n*a.y,z:n*a.z})}i(t)}}),!!c&&{passive:!1}),t.glplot.canvas.addEventListener(\"mousemove\",(function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e=n();t.graphDiv.emit(\"plotly_relayouting\",e)}})),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",(function(r){e&&e.emit&&e.emit(\"plotly_webglcontextlost\",{event:r,layer:t.id})}),!1)),t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(){t.render()},!0},w.render=function(){var t,e=this,r=e.graphDiv,n=e.svgContainer,i=e.container.getBoundingClientRect();r._fullLayout._calcInverseTransform(r);var a=r._fullLayout._invScaleX,o=r._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+s+\" \"+l),n.setAttributeNS(null,\"width\",s),n.setAttributeNS(null,\"height\",l),b(e),e.glplot.axes.update(e.axesOptions);for(var c,u=Object.keys(e.traces),h=null,g=e.glplot.selection,m=0;m<u.length;++m)\"skip\"!==(t=e.traces[u[m]]).data.hoverinfo&&t.handlePick(g)&&(h=t),t.setContourLevels&&t.setContourLevels();function y(t,r,n){var i=e.fullSceneLayout[t+\"axis\"];return\"log\"!==i.type&&(r=i.d2l(r)),p.hoverLabelText(i,r,n)}if(null!==h){var x=v(e.glplot.cameraParams,g.dataCoordinate);t=h.data;var _,w=r._fullData[t.index],T=g.index,k={xLabel:y(\"x\",g.traceCoordinate[0],t.xhoverformat),yLabel:y(\"y\",g.traceCoordinate[1],t.yhoverformat),zLabel:y(\"z\",g.traceCoordinate[2],t.zhoverformat)},A=d.castHoverinfo(w,e.fullLayout,T),M=(A||\"\").split(\"+\"),S=A&&\"all\"===A;w.hovertemplate||S||(-1===M.indexOf(\"x\")&&(k.xLabel=void 0),-1===M.indexOf(\"y\")&&(k.yLabel=void 0),-1===M.indexOf(\"z\")&&(k.zLabel=void 0),-1===M.indexOf(\"text\")&&(g.textLabel=void 0),-1===M.indexOf(\"name\")&&(h.name=void 0));var E=[];\"cone\"===t.type||\"streamtube\"===t.type?(k.uLabel=y(\"x\",g.traceCoordinate[3],t.uhoverformat),(S||-1!==M.indexOf(\"u\"))&&E.push(\"u: \"+k.uLabel),k.vLabel=y(\"y\",g.traceCoordinate[4],t.vhoverformat),(S||-1!==M.indexOf(\"v\"))&&E.push(\"v: \"+k.vLabel),k.wLabel=y(\"z\",g.traceCoordinate[5],t.whoverformat),(S||-1!==M.indexOf(\"w\"))&&E.push(\"w: \"+k.wLabel),k.normLabel=g.traceCoordinate[6].toPrecision(3),(S||-1!==M.indexOf(\"norm\"))&&E.push(\"norm: \"+k.normLabel),\"streamtube\"===t.type&&(k.divergenceLabel=g.traceCoordinate[7].toPrecision(3),(S||-1!==M.indexOf(\"divergence\"))&&E.push(\"divergence: \"+k.divergenceLabel)),g.textLabel&&E.push(g.textLabel),_=E.join(\"<br>\")):\"isosurface\"===t.type||\"volume\"===t.type?(k.valueLabel=p.hoverLabelText(e._mockAxis,e._mockAxis.d2l(g.traceCoordinate[3]),t.valuehoverformat),E.push(\"value: \"+k.valueLabel),g.textLabel&&E.push(g.textLabel),_=E.join(\"<br>\")):_=g.textLabel;var L={x:g.traceCoordinate[0],y:g.traceCoordinate[1],z:g.traceCoordinate[2],data:w._input,fullData:w,curveNumber:w.index,pointNumber:T};d.appendArrayPointValue(L,w,T),t._module.eventData&&(L=w._module.eventData(L,g,w,{},T));var C={points:[L]};if(e.fullSceneLayout.hovermode){var P=[];d.loneHover({trace:w,x:(.5+.5*x[0]/x[3])*s,y:(.5-.5*x[1]/x[3])*l,xLabel:k.xLabel,yLabel:k.yLabel,zLabel:k.zLabel,text:_,name:h.name,color:d.castHoverOption(w,T,\"bgcolor\")||h.color,borderColor:d.castHoverOption(w,T,\"bordercolor\"),fontFamily:d.castHoverOption(w,T,\"font.family\"),fontSize:d.castHoverOption(w,T,\"font.size\"),fontColor:d.castHoverOption(w,T,\"font.color\"),nameLength:d.castHoverOption(w,T,\"namelength\"),textAlign:d.castHoverOption(w,T,\"align\"),hovertemplate:f.castOption(w,T,\"hovertemplate\"),hovertemplateLabels:f.extendFlat({},L,k),eventData:[L]},{container:n,gd:r,inOut_bbox:P}),L.bbox=P[0]}g.buttons&&g.distance<5?r.emit(\"plotly_click\",C):r.emit(\"plotly_hover\",C),c=C}else d.loneUnhover(n),r.emit(\"plotly_unhover\",c);e.drawAnnotations(e)},w.recoverContext=function(){var t=this;t.glplot.dispose();var e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):f.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\")};requestAnimationFrame(e)};var k=[\"xaxis\",\"yaxis\",\"zaxis\"];function A(t,e,r){for(var n=t.fullSceneLayout,i=0;i<3;i++){var a=k[i],o=a.charAt(0),s=n[a],l=e[o],c=e[o+\"calendar\"],u=e[\"_\"+o+\"length\"];if(f.isArrayOrTypedArray(l))for(var h,p=0;p<(u||l.length);p++)if(f.isArrayOrTypedArray(l[p]))for(var d=0;d<l[p].length;++d)h=s.d2l(l[p][d],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else h=s.d2l(l[p],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else r[0][i]=Math.min(r[0][i],0),r[1][i]=Math.max(r[1][i],u-1)}}w.plot=function(t,e,r){if(this.plotArgs=[t,e,r],!this.glplot.contextLost){var n,i,a,o,s,l,c=e[this.id],u=r[this.id];this.fullLayout=e,this.fullSceneLayout=c,this.axesOptions.merge(e,c),this.spikeOptions.merge(c),this.setViewport(c),this.updateFx(c.dragmode,c.hovermode),this.camera.enableWheel=this.graphDiv._context._scrollZoom.gl3d,this.glplot.setClearColor(g(c.bgcolor)),this.setConvert(s),t?Array.isArray(t)||(t=[t]):t=[];var f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&A(this,n,f);!function(t,e){for(var r=t.fullSceneLayout,n=r.annotations||[],i=0;i<3;i++)for(var a=k[i],o=a.charAt(0),s=r[a],l=0;l<n.length;l++){var c=n[l];if(c.visible){var u=s.r2l(c[o]);!isNaN(u)&&isFinite(u)&&(e[0][i]=Math.min(e[0][i],u),e[1][i]=Math.max(e[1][i],u))}}}(this,f);var h=[1,1,1];for(o=0;o<3;++o)f[1][o]===f[0][o]?h[o]=1:h[o]=1/(f[1][o]-f[0][o]);for(this.dataScale=h,this.convertAnnotations(this),a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&((i=this.traces[n.uid])?i.data.type===n.type?i.update(n):(i.dispose(),i=n._module.plot(this,n),this.traces[n.uid]=i):(i=n._module.plot(this,n),this.traces[n.uid]=i),i.name=n.name);var p=Object.keys(this.traces);t:for(a=0;a<p.length;++a){for(o=0;o<t.length;++o)if(t[o].uid===p[a]&&!0===t[o].visible&&0!==t[o]._length)continue t;(i=this.traces[p[a]]).dispose(),delete this.traces[p[a]]}this.glplot.objects.sort((function(t,e){return t._trace.data.index-e._trace.data.index}));var d,m=[[0,0,0],[0,0,0]],v=[],y={};for(a=0;a<3;++a){if((l=(s=c[k[a]]).type)in y?(y[l].acc*=h[a],y[l].count+=1):y[l]={acc:h[a],count:1},s.autorange){m[0][a]=1/0,m[1][a]=-1/0;var x=this.glplot.objects,b=this.fullSceneLayout.annotations||[],_=s._name.charAt(0);for(o=0;o<x.length;o++){var w=x[o],T=w.bounds,M=w._trace.data._pad||0;\"ErrorBars\"===w.constructor.name&&s._lowerLogErrorBound?m[0][a]=Math.min(m[0][a],s._lowerLogErrorBound):m[0][a]=Math.min(m[0][a],T[0][a]/h[a]-M),m[1][a]=Math.max(m[1][a],T[1][a]/h[a]+M)}for(o=0;o<b.length;o++){var S=b[o];if(S.visible){var E=s.r2l(S[_]);m[0][a]=Math.min(m[0][a],E),m[1][a]=Math.max(m[1][a],E)}}if(\"rangemode\"in s&&\"tozero\"===s.rangemode&&(m[0][a]=Math.min(m[0][a],0),m[1][a]=Math.max(m[1][a],0)),m[0][a]>m[1][a])m[0][a]=-1,m[1][a]=1;else{var L=m[1][a]-m[0][a];m[0][a]-=L/32,m[1][a]+=L/32}if(\"reversed\"===s.autorange){var C=m[0][a];m[0][a]=m[1][a],m[1][a]=C}}else{var P=s.range;m[0][a]=s.r2l(P[0]),m[1][a]=s.r2l(P[1])}m[0][a]===m[1][a]&&(m[0][a]-=1,m[1][a]+=1),v[a]=m[1][a]-m[0][a],this.glplot.setBounds(a,{min:m[0][a]*h[a],max:m[1][a]*h[a]})}var I=c.aspectmode;if(\"cube\"===I)d=[1,1,1];else if(\"manual\"===I){var O=c.aspectratio;d=[O.x,O.y,O.z]}else{if(\"auto\"!==I&&\"data\"!==I)throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");var z=[1,1,1];for(a=0;a<3;++a){var D=y[l=(s=c[k[a]]).type];z[a]=Math.pow(D.acc,1/D.count)/h[a]}d=\"data\"===I||Math.max.apply(null,z)/Math.min.apply(null,z)<=4?z:[1,1,1]}c.aspectratio.x=u.aspectratio.x=d[0],c.aspectratio.y=u.aspectratio.y=d[1],c.aspectratio.z=u.aspectratio.z=d[2],this.glplot.setAspectratio(c.aspectratio),this.viewInitial.aspectratio||(this.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z}),this.viewInitial.aspectmode||(this.viewInitial.aspectmode=c.aspectmode);var R=c.domain||null,F=e._size||null;if(R&&F){var B=this.container.style;B.position=\"absolute\",B.left=F.l+R.x[0]*F.w+\"px\",B.top=F.t+(1-R.y[1])*F.h+\"px\",B.width=F.w*(R.x[1]-R.x[0])+\"px\",B.height=F.h*(R.y[1]-R.y[0])+\"px\"}this.glplot.redraw()}},w.destroy=function(){this.glplot&&(this.camera.mouseListener.enabled=!1,this.container.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null,this.glplot.dispose(),this.container.parentNode.removeChild(this.container),this.glplot=null)},w.getCamera=function(){var t;return this.camera.view.recalcMatrix(this.camera.view.lastT()),{up:{x:(t=this.camera).up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?\"orthographic\":\"perspective\"}}},w.setViewport=function(t){var e,r=t.camera;this.camera.lookAt.apply(this,[[(e=r).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),this.glplot.setAspectratio(t.aspectratio),\"orthographic\"===r.projection.type!==this.camera._ortho&&(this.glplot.redraw(),this.glplot.clearRGBA(),this.glplot.dispose(),this.initializeGLPlot())},w.isCameraChanged=function(t){var e=this.getCamera(),r=f.nestedProperty(t,this.id+\".camera\").get();function n(t,e,r,n){var i=[\"up\",\"center\",\"eye\"],a=[\"x\",\"y\",\"z\"];return e[i[r]]&&t[i[r]][a[n]]===e[i[r]][a[n]]}var i=!1;if(void 0===r)i=!0;else{for(var a=0;a<3;a++)for(var o=0;o<3;o++)if(!n(e,r,a,o)){i=!0;break}(!r.projection||e.projection&&e.projection.type!==r.projection.type)&&(i=!0)}return i},w.isAspectChanged=function(t){var e=this.glplot.getAspectratio(),r=f.nestedProperty(t,this.id+\".aspectratio\").get();return void 0===r||r.x!==e.x||r.y!==e.y||r.z!==e.z},w.saveLayout=function(t){var e,r,n,i,a,o,s=this.fullLayout,l=this.isCameraChanged(t),c=this.isAspectChanged(t),h=l||c;if(h){var p={};if(l&&(e=this.getCamera(),n=(r=f.nestedProperty(t,this.id+\".camera\")).get(),p[this.id+\".camera\"]=n),c&&(i=this.glplot.getAspectratio(),o=(a=f.nestedProperty(t,this.id+\".aspectratio\")).get(),p[this.id+\".aspectratio\"]=o),u.call(\"_storeDirectGUIEdit\",t,s._preGUI,p),l)r.set(e),f.nestedProperty(s,this.id+\".camera\").set(e);if(c)a.set(i),f.nestedProperty(s,this.id+\".aspectratio\").set(i),this.glplot.redraw()}return h},w.updateFx=function(t,e){var r=this.camera;if(r)if(\"orbit\"===t)r.mode=\"orbit\",r.keyBindingMode=\"rotate\";else if(\"turntable\"===t){r.up=[0,0,1],r.mode=\"turntable\",r.keyBindingMode=\"rotate\";var n=this.graphDiv,i=n._fullLayout,a=this.fullSceneLayout.camera,o=a.up.x,s=a.up.y,l=a.up.z;if(l/Math.sqrt(o*o+s*s+l*l)<.999){var c=this.id+\".camera.up\",h={x:0,y:0,z:1},p={};p[c]=h;var d=n.layout;u.call(\"_storeDirectGUIEdit\",d,i._preGUI,p),a.up=h,f.nestedProperty(d,c).set(h)}}else r.keyBindingMode=t;this.fullSceneLayout.hovermode=e},w.toImage=function(t){t||(t=\"png\"),this.staticMode&&this.container.appendChild(n),this.glplot.redraw();var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a),function(t,e,r){for(var n=0,i=r-1;n<i;++n,--i)for(var a=0;a<e;++a)for(var o=0;o<4;++o){var s=4*(e*n+a)+o,l=4*(e*i+a)+o,c=t[s];t[s]=t[l],t[l]=c}}(a,r,i),function(t,e,r){for(var n=0;n<r;++n)for(var i=0;i<e;++i){var a=4*(e*n+i),o=t[a+3];if(o>0)for(var s=255/o,l=0;l<3;++l)t[a+l]=Math.min(s*t[a+l],255)}}(a,r,i);var o=document.createElement(\"canvas\");o.width=r,o.height=i;var 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strict\";e.exports=function(t,e,r,n){n=n||t.length;for(var i=new Array(n),a=0;a<n;a++)i[a]=[t[a],e[a],r[a]];return i}},{}],908:[function(t,e,r){\"use strict\";var n=t(\"./font_attributes\"),i=t(\"./animation_attributes\"),a=t(\"../components/color/attributes\"),o=t(\"../components/shapes/draw_newshape/attributes\"),s=t(\"./pad_attributes\"),l=t(\"../lib/extend\").extendFlat,c=n({editType:\"calc\"});c.family.dflt='\"Open Sans\", verdana, arial, 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n=t(\"../../lib/sort_object_keys\"),i='\\xa9 <a target=\"_blank\" href=\"https://www.openstreetmap.org/copyright\">OpenStreetMap</a> contributors',a=['\\xa9 <a target=\"_blank\" href=\"https://carto.com/\">Carto</a>',i].join(\" \"),o=['Map tiles by <a target=\"_blank\" href=\"https://stamen.com\">Stamen Design</a>','under <a target=\"_blank\" href=\"https://creativecommons.org/licenses/by/3.0\">CC BY 3.0</a>',\"|\",'Data by <a target=\"_blank\" href=\"https://openstreetmap.org\">OpenStreetMap</a> contributors','under <a target=\"_blank\" href=\"https://www.openstreetmap.org/copyright\">ODbL</a>'].join(\" 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t&&(-1!==p.styleValuesMapbox.indexOf(t)||0===t.indexOf(\"mapbox://\"))}r.name=\"mapbox\",r.attr=\"subplot\",r.idRoot=\"mapbox\",r.idRegex=r.attrRegex=i.counterRegex(\"mapbox\"),r.attributes={subplot:{valType:\"subplotid\",dflt:\"mapbox\",editType:\"calc\"}},r.layoutAttributes=t(\"./layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout_defaults\"),r.plot=function(t){var e=t._fullLayout,r=t.calcdata,a=e._subplots.mapbox;if(n.version!==p.requiredVersion)throw new Error(p.wrongVersionErrorMsg);var o=function(t,e){var r=t._fullLayout;if(\"\"===t._context.mapboxAccessToken)return\"\";for(var n=[],a=[],o=!1,s=!1,l=0;l<e.length;l++){var c=r[e[l]],u=c.accesstoken;d(c.style)&&(u?i.pushUnique(n,u):(d(c._input.style)&&(i.error(\"Uses Mapbox map style, but did not set an access token.\"),o=!0),s=!0)),u&&i.pushUnique(a,u)}if(s){var f=o?p.noAccessTokenErrorMsg:p.missingStyleErrorMsg;throw i.error(f),new Error(f)}return 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g=c.select(s._subplot.div);if(!(null===g.select(\".mapboxgl-ctrl-logo\").node().offsetParent)){var m=e._glimages.append(\"g\");m.attr(\"transform\",a(n.l+n.w*h.x[0]+10,n.t+n.h*(1-h.y[0])-31)),m.append(\"path\").attr(\"d\",p.mapboxLogo.path0).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"}),m.append(\"path\").attr(\"d\",p.mapboxLogo.path1).style(\"opacity\",.35).style(\"enable-background\",\"new\"),m.append(\"path\").attr(\"d\",p.mapboxLogo.path2).style(\"opacity\",.35).style(\"enable-background\",\"new\"),m.append(\"polygon\").attr(\"points\",p.mapboxLogo.polygon).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"})}var v=g.select(\".mapboxgl-ctrl-attrib\").text().replace(\"Improve this map\",\"\"),y=e._glimages.append(\"g\"),x=y.append(\"text\");x.text(v).classed(\"static-attribution\",!0).attr({\"font-size\":12,\"font-family\":\"Arial\",color:\"rgba(0, 0, 0, 0.75)\",\"text-anchor\":\"end\",\"data-unformatted\":v});var 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n=t(\"../../lib\"),i=t(\"../../lib/svg_text_utils\").sanitizeHTML,a=t(\"./convert_text_opts\"),o=t(\"./constants\");function s(t,e){this.subplot=t,this.uid=t.uid+\"-\"+e,this.index=e,this.idSource=\"source-\"+this.uid,this.idLayer=o.layoutLayerPrefix+this.uid,this.sourceType=null,this.source=null,this.layerType=null,this.below=null,this.visible=!1}var l=s.prototype;function c(t){if(!t.visible)return!1;var e=t.source;if(Array.isArray(e)&&e.length>0){for(var r=0;r<e.length;r++)if(\"string\"!=typeof e[r]||0===e[r].length)return!1;return!0}return n.isPlainObject(e)||\"string\"==typeof e&&e.length>0}function u(t){var e={},r={};switch(t.type){case\"circle\":n.extendFlat(r,{\"circle-radius\":t.circle.radius,\"circle-color\":t.color,\"circle-opacity\":t.opacity});break;case\"line\":n.extendFlat(r,{\"line-width\":t.line.width,\"line-color\":t.color,\"line-opacity\":t.opacity,\"line-dasharray\":t.line.dash});break;case\"fill\":n.extendFlat(r,{\"fill-color\":t.color,\"fill-outline-color\":t.fill.outlinecolor,\"fill-opacity\":t.opacity});break;case\"symbol\":var i=t.symbol,o=a(i.textposition,i.iconsize);n.extendFlat(e,{\"icon-image\":i.icon+\"-15\",\"icon-size\":i.iconsize/10,\"text-field\":i.text,\"text-size\":i.textfont.size,\"text-anchor\":o.anchor,\"text-offset\":o.offset,\"symbol-placement\":i.placement}),n.extendFlat(r,{\"icon-color\":t.color,\"text-color\":i.textfont.color,\"text-opacity\":t.opacity});break;case\"raster\":n.extendFlat(r,{\"raster-fade-duration\":0,\"raster-opacity\":t.opacity})}return{layout:e,paint:r}}l.update=function(t){this.visible?this.needsNewImage(t)?this.updateImage(t):this.needsNewSource(t)?(this.removeLayer(),this.updateSource(t),this.updateLayer(t)):this.needsNewLayer(t)?this.updateLayer(t):this.updateStyle(t):(this.updateSource(t),this.updateLayer(t)),this.visible=c(t)},l.needsNewImage=function(t){return this.subplot.map.getSource(this.idSource)&&\"image\"===this.sourceType&&\"image\"===t.sourcetype&&(this.source!==t.source||JSON.stringify(this.coordinates)!==JSON.stringify(t.coordinates))},l.needsNewSource=function(t){return this.sourceType!==t.sourcetype||JSON.stringify(this.source)!==JSON.stringify(t.source)||this.layerType!==t.type},l.needsNewLayer=function(t){return this.layerType!==t.type||this.below!==this.subplot.belowLookup[\"layout-\"+this.index]},l.lookupBelow=function(){return this.subplot.belowLookup[\"layout-\"+this.index]},l.updateImage=function(t){this.subplot.map.getSource(this.idSource).updateImage({url:t.source,coordinates:t.coordinates});var e=this.findFollowingMapboxLayerId(this.lookupBelow());null!==e&&this.subplot.map.moveLayer(this.idLayer,e)},l.updateSource=function(t){var e=this.subplot.map;if(e.getSource(this.idSource)&&e.removeSource(this.idSource),this.sourceType=t.sourcetype,this.source=t.source,c(t)){var r=function(t){var e,r=t.sourcetype,n=t.source,a={type:r};\"geojson\"===r?e=\"data\":\"vector\"===r?e=\"string\"==typeof n?\"url\":\"tiles\":\"raster\"===r?(e=\"tiles\",a.tileSize=256):\"image\"===r&&(e=\"url\",a.coordinates=t.coordinates);a[e]=n,t.sourceattribution&&(a.attribution=i(t.sourceattribution));return a}(t);e.addSource(this.idSource,r)}},l.findFollowingMapboxLayerId=function(t){if(\"traces\"===t)for(var e=this.subplot.getMapLayers(),r=0;r<e.length;r++){var n=e[r].id;if(\"string\"==typeof n&&0===n.indexOf(o.traceLayerPrefix)){t=n;break}}return t},l.updateLayer=function(t){var e=this.subplot,r=u(t),n=this.lookupBelow(),i=this.findFollowingMapboxLayerId(n);this.removeLayer(),c(t)&&e.addLayer({id:this.idLayer,source:this.idSource,\"source-layer\":t.sourcelayer||\"\",type:t.type,minzoom:t.minzoom,maxzoom:t.maxzoom,layout:r.layout,paint:r.paint},i),this.layerType=t.type,this.below=n},l.updateStyle=function(t){if(c(t)){var 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strict\";var n=t(\"../../lib\"),i=t(\"../subplot_defaults\"),a=t(\"../array_container_defaults\"),o=t(\"./layout_attributes\");function s(t,e,r,n){r(\"accesstoken\",n.accessToken),r(\"style\"),r(\"center.lon\"),r(\"center.lat\"),r(\"zoom\"),r(\"bearing\"),r(\"pitch\"),a(t,e,{name:\"layers\",handleItemDefaults:l}),e._input=t}function l(t,e){function r(r,i){return n.coerce(t,e,o.layers,r,i)}if(r(\"visible\")){var i,a=r(\"sourcetype\"),s=\"raster\"===a||\"image\"===a;r(\"source\"),r(\"sourceattribution\"),\"vector\"===a&&r(\"sourcelayer\"),\"image\"===a&&r(\"coordinates\"),s&&(i=\"raster\");var l=r(\"type\",i);s&&\"raster\"!==l&&(l=e.type=\"raster\",n.log(\"Source types *raster* and *image* must drawn *raster* layer 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n=t(\"mapbox-gl/dist/mapbox-gl-unminified\"),i=t(\"../../lib\"),a=t(\"../../lib/geo_location_utils\"),o=t(\"../../registry\"),s=t(\"../cartesian/axes\"),l=t(\"../../components/dragelement\"),c=t(\"../../components/fx\"),u=t(\"../../components/dragelement/helpers\"),f=u.rectMode,h=u.drawMode,p=u.selectMode,d=t(\"../cartesian/select\").prepSelect,g=t(\"../cartesian/select\").clearSelect,m=t(\"../cartesian/select\").clearSelectionsCache,v=t(\"../cartesian/select\").selectOnClick,y=t(\"./constants\"),x=t(\"./layers\");function b(t,e){this.id=e,this.gd=t;var r=t._fullLayout,n=t._context;this.container=r._glcontainer.node(),this.isStatic=n.staticPlot,this.uid=r._uid+\"-\"+this.id,this.div=null,this.xaxis=null,this.yaxis=null,this.createFramework(r),this.map=null,this.accessToken=null,this.styleObj=null,this.traceHash={},this.layerList=[],this.belowLookup={},this.dragging=!1,this.wheeling=!1}var _=b.prototype;_.plot=function(t,e,r){var n,i=this,a=e[i.id];i.map&&a.accesstoken!==i.accessToken&&(i.map.remove(),i.map=null,i.styleObj=null,i.traceHash={},i.layerList=[]),n=i.map?new Promise((function(r,n){i.updateMap(t,e,r,n)})):new Promise((function(r,n){i.createMap(t,e,r,n)})),r.push(n)},_.createMap=function(t,e,r,i){var o=this,s=e[o.id],l=o.styleObj=T(s.style);o.accessToken=s.accesstoken;var c=o.map=new n.Map({container:o.div,style:l.style,center:A(s.center),zoom:s.zoom,bearing:s.bearing,pitch:s.pitch,interactive:!o.isStatic,preserveDrawingBuffer:o.isStatic,doubleClickZoom:!1,boxZoom:!1,attributionControl:!1}).addControl(new n.AttributionControl({compact:!0}));c._canvas.style.left=\"0px\",c._canvas.style.top=\"0px\",o.rejectOnError(i),o.isStatic||o.initFx(t,e);var u=[];u.push(new Promise((function(t){c.once(\"load\",t)}))),u=u.concat(a.fetchTraceGeoData(t)),Promise.all(u).then((function(){o.fillBelowLookup(t,e),o.updateData(t),o.updateLayout(e),o.resolveOnRender(r)})).catch(i)},_.updateMap=function(t,e,r,n){var i=this,o=i.map,s=e[this.id];i.rejectOnError(n);var l=[],c=T(s.style);JSON.stringify(i.styleObj)!==JSON.stringify(c)&&(i.styleObj=c,o.setStyle(c.style),i.traceHash={},l.push(new Promise((function(t){o.once(\"styledata\",t)})))),l=l.concat(a.fetchTraceGeoData(t)),Promise.all(l).then((function(){i.fillBelowLookup(t,e),i.updateData(t),i.updateLayout(e),i.resolveOnRender(r)})).catch(n)},_.fillBelowLookup=function(t,e){var r,n,i=e[this.id].layers,a=this.belowLookup={},o=!1;for(r=0;r<t.length;r++){var s=t[r][0].trace,l=s._module;\"string\"==typeof s.below?n=s.below:l.getBelow&&(n=l.getBelow(s,this)),\"\"===n&&(o=!0),a[\"trace-\"+s.uid]=n||\"\"}for(r=0;r<i.length;r++){var c=i[r];n=\"string\"==typeof c.below?c.below:o?\"traces\":\"\",a[\"layout-\"+r]=n}var u,f,h={};for(u in a)h[n=a[u]]?h[n].push(u):h[n]=[u];for(n in h){var p=h[n];if(p.length>1)for(r=0;r<p.length;r++)0===(u=p[r]).indexOf(\"trace-\")?(f=u.split(\"trace-\")[1],this.traceHash[f]&&(this.traceHash[f].below=null)):0===u.indexOf(\"layout-\")&&(f=u.split(\"layout-\")[1],this.layerList[f]&&(this.layerList[f].below=null))}};var w={choroplethmapbox:0,densitymapbox:1,scattermapbox:2};function T(t){var e={};return i.isPlainObject(t)?(e.id=t.id,e.style=t):\"string\"==typeof t?(e.id=t,-1!==y.styleValuesMapbox.indexOf(t)?e.style=k(t):y.stylesNonMapbox[t]?e.style=y.stylesNonMapbox[t]:e.style=t):(e.id=y.styleValueDflt,e.style=k(y.styleValueDflt)),e.transition={duration:0,delay:0},e}function k(t){return y.styleUrlPrefix+t+\"-\"+y.styleUrlSuffix}function A(t){return[t.lon,t.lat]}_.updateData=function(t){var e,r,n,i,a=this.traceHash,o=t.slice().sort((function(t,e){return w[t[0].trace.type]-w[e[0].trace.type]}));for(n=0;n<o.length;n++){var s=o[n],l=!1;(e=a[(r=s[0].trace).uid])&&(e.type===r.type?(e.update(s),l=!0):e.dispose()),!l&&r._module&&(a[r.uid]=r._module.plot(this,s))}var c=Object.keys(a);t:for(n=0;n<c.length;n++){var u=c[n];for(i=0;i<t.length;i++)if(u===(r=t[i][0].trace).uid)continue t;(e=a[u]).dispose(),delete a[u]}},_.updateLayout=function(t){var e=this.map,r=t[this.id];this.dragging||this.wheeling||(e.setCenter(A(r.center)),e.setZoom(r.zoom),e.setBearing(r.bearing),e.setPitch(r.pitch)),this.updateLayers(t),this.updateFramework(t),this.updateFx(t),this.map.resize(),this.gd._context._scrollZoom.mapbox?e.scrollZoom.enable():e.scrollZoom.disable()},_.resolveOnRender=function(t){var e=this.map;e.on(\"render\",(function r(){e.loaded()&&(e.off(\"render\",r),setTimeout(t,10))}))},_.rejectOnError=function(t){var e=this.map;function r(){t(new Error(y.mapOnErrorMsg))}e.once(\"error\",r),e.once(\"style.error\",r),e.once(\"source.error\",r),e.once(\"tile.error\",r),e.once(\"layer.error\",r)},_.createFramework=function(t){var e=this,r=e.div=document.createElement(\"div\");r.id=e.uid,r.style.position=\"absolute\",e.container.appendChild(r),e.xaxis={_id:\"x\",c2p:function(t){return e.project(t).x}},e.yaxis={_id:\"y\",c2p:function(t){return e.project(t).y}},e.updateFramework(t),e.mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},s.setConvert(e.mockAxis,t)},_.initFx=function(t,e){var r=this,n=r.gd,i=r.map;function a(){c.loneUnhover(e._hoverlayer)}function s(){var t=r.getView();n.emit(\"plotly_relayouting\",r.getViewEditsWithDerived(t))}i.on(\"moveend\",(function(t){if(r.map){var e=n._fullLayout;if(t.originalEvent||r.wheeling){var i=e[r.id];o.call(\"_storeDirectGUIEdit\",n.layout,e._preGUI,r.getViewEdits(i));var a=r.getView();i._input.center=i.center=a.center,i._input.zoom=i.zoom=a.zoom,i._input.bearing=i.bearing=a.bearing,i._input.pitch=i.pitch=a.pitch,n.emit(\"plotly_relayout\",r.getViewEditsWithDerived(a))}t.originalEvent&&\"mouseup\"===t.originalEvent.type?r.dragging=!1:r.wheeling&&(r.wheeling=!1),e._rehover&&e._rehover()}})),i.on(\"wheel\",(function(){r.wheeling=!0})),i.on(\"mousemove\",(function(t){var e=r.div.getBoundingClientRect(),a=[t.originalEvent.offsetX,t.originalEvent.offsetY];t.target.getBoundingClientRect=function(){return e},r.xaxis.p2c=function(){return i.unproject(a).lng},r.yaxis.p2c=function(){return 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\"+d,m=o(\"title.text\",g);e._hovertitle=m===g?m:d,a.coerceFont(o,\"title.font\",{family:r.font.family,size:a.bigFont(r.font.size),color:p}),o(\"min\"),c(t,e,o,\"linear\"),s(t,e,o,\"linear\",{}),l(t,e,o,{outerTicks:!0}),o(\"showticklabels\")&&(a.coerceFont(o,\"tickfont\",{family:r.font.family,size:r.font.size,color:p}),o(\"tickangle\"),o(\"tickformat\")),u(t,e,o,{dfltColor:h,bgColor:r.bgColor,blend:60,showLine:!0,showGrid:!0,noZeroLine:!0,attributes:i}),o(\"hoverformat\"),o(\"layer\")}e.exports=function(t,e,r){o(t,e,r,{type:\"ternary\",attributes:f,handleDefaults:p,font:e.font,paper_bgcolor:e.paper_bgcolor})}},{\"../../components/color\":666,\"../../lib\":803,\"../../plot_api/plot_template\":843,\"../cartesian/line_grid_defaults\":871,\"../cartesian/tick_label_defaults\":876,\"../cartesian/tick_mark_defaults\":877,\"../cartesian/tick_value_defaults\":878,\"../subplot_defaults\":925,\"./layout_attributes\":928}],930:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"tinycolor2\"),a=t(\"../../registry\"),o=t(\"../../lib\"),s=o.strTranslate,l=o._,c=t(\"../../components/color\"),u=t(\"../../components/drawing\"),f=t(\"../cartesian/set_convert\"),h=t(\"../../lib/extend\").extendFlat,p=t(\"../plots\"),d=t(\"../cartesian/axes\"),g=t(\"../../components/dragelement\"),m=t(\"../../components/fx\"),v=t(\"../../components/dragelement/helpers\"),y=v.freeMode,x=v.rectMode,b=t(\"../../components/titles\"),_=t(\"../cartesian/select\").prepSelect,w=t(\"../cartesian/select\").selectOnClick,T=t(\"../cartesian/select\").clearSelect,k=t(\"../cartesian/select\").clearSelectionsCache,A=t(\"../cartesian/constants\");function M(t,e){this.id=t.id,this.graphDiv=t.graphDiv,this.init(e),this.makeFramework(e),this.aTickLayout=null,this.bTickLayout=null,this.cTickLayout=null}e.exports=M;var S=M.prototype;S.init=function(t){this.container=t._ternarylayer,this.defs=t._defs,this.layoutId=t._uid,this.traceHash={},this.layers={}},S.plot=function(t,e){var r=e[this.id],n=e._size;this._hasClipOnAxisFalse=!1;for(var i=0;i<t.length;i++){if(!1===t[i][0].trace.cliponaxis){this._hasClipOnAxisFalse=!0;break}}this.updateLayers(r),this.adjustLayout(r,n),p.generalUpdatePerTraceModule(this.graphDiv,this,t,r),this.layers.plotbg.select(\"path\").call(c.fill,r.bgcolor)},S.makeFramework=function(t){var e=this.graphDiv,r=t[this.id],n=this.clipId=\"clip\"+this.layoutId+this.id,i=this.clipIdRelative=\"clip-relative\"+this.layoutId+this.id;this.clipDef=o.ensureSingleById(t._clips,\"clipPath\",n,(function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")})),this.clipDefRelative=o.ensureSingleById(t._clips,\"clipPath\",i,(function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")})),this.plotContainer=o.ensureSingle(this.container,\"g\",this.id),this.updateLayers(r),u.setClipUrl(this.layers.backplot,n,e),u.setClipUrl(this.layers.grids,n,e)},S.updateLayers=function(t){var e=this.layers,r=[\"draglayer\",\"plotbg\",\"backplot\",\"grids\"];\"below traces\"===t.aaxis.layer&&r.push(\"aaxis\",\"aline\"),\"below traces\"===t.baxis.layer&&r.push(\"baxis\",\"bline\"),\"below traces\"===t.caxis.layer&&r.push(\"caxis\",\"cline\"),r.push(\"frontplot\"),\"above traces\"===t.aaxis.layer&&r.push(\"aaxis\",\"aline\"),\"above traces\"===t.baxis.layer&&r.push(\"baxis\",\"bline\"),\"above traces\"===t.caxis.layer&&r.push(\"caxis\",\"cline\");var i=this.plotContainer.selectAll(\"g.toplevel\").data(r,String),a=[\"agrid\",\"bgrid\",\"cgrid\"];i.enter().append(\"g\").attr(\"class\",(function(t){return\"toplevel \"+t})).each((function(t){var r=n.select(this);e[t]=r,\"frontplot\"===t?r.append(\"g\").classed(\"scatterlayer\",!0):\"backplot\"===t?r.append(\"g\").classed(\"maplayer\",!0):\"plotbg\"===t?r.append(\"path\").attr(\"d\",\"M0,0Z\"):\"aline\"===t||\"bline\"===t||\"cline\"===t?r.append(\"path\"):\"grids\"===t&&a.forEach((function(t){e[t]=r.append(\"g\").classed(\"grid \"+t,!0)}))})),i.order()};var E=Math.sqrt(4/3);S.adjustLayout=function(t,e){var r,n,i,a,o,l,p=this,d=t.domain,g=(d.x[0]+d.x[1])/2,m=(d.y[0]+d.y[1])/2,v=d.x[1]-d.x[0],y=d.y[1]-d.y[0],x=v*e.w,b=y*e.h,_=t.sum,w=t.aaxis.min,T=t.baxis.min,k=t.caxis.min;x>E*b?i=(a=b)*E:a=(i=x)/E,o=v*i/x,l=y*a/b,r=e.l+e.w*g-i/2,n=e.t+e.h*(1-m)-a/2,p.x0=r,p.y0=n,p.w=i,p.h=a,p.sum=_,p.xaxis={type:\"linear\",range:[w+2*k-_,_-w-2*T],domain:[g-o/2,g+o/2],_id:\"x\"},f(p.xaxis,p.graphDiv._fullLayout),p.xaxis.setScale(),p.xaxis.isPtWithinRange=function(t){return t.a>=p.aaxis.range[0]&&t.a<=p.aaxis.range[1]&&t.b>=p.baxis.range[1]&&t.b<=p.baxis.range[0]&&t.c>=p.caxis.range[1]&&t.c<=p.caxis.range[0]},p.yaxis={type:\"linear\",range:[w,_-T-k],domain:[m-l/2,m+l/2],_id:\"y\"},f(p.yaxis,p.graphDiv._fullLayout),p.yaxis.setScale(),p.yaxis.isPtWithinRange=function(){return!0};var A=p.yaxis.domain[0],M=p.aaxis=h({},t.aaxis,{range:[w,_-T-k],side:\"left\",tickangle:(+t.aaxis.tickangle||0)-30,domain:[A,A+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(M,p.graphDiv._fullLayout),M.setScale();var S=p.baxis=h({},t.baxis,{range:[_-w-k,T],side:\"bottom\",domain:p.xaxis.domain,anchor:\"free\",position:0,_id:\"x\",_length:i});f(S,p.graphDiv._fullLayout),S.setScale();var L=p.caxis=h({},t.caxis,{range:[_-w-T,k],side:\"right\",tickangle:(+t.caxis.tickangle||0)+30,domain:[A,A+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(L,p.graphDiv._fullLayout),L.setScale();var C=\"M\"+r+\",\"+(n+a)+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDef.select(\"path\").attr(\"d\",C),p.layers.plotbg.select(\"path\").attr(\"d\",C);var P=\"M0,\"+a+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDefRelative.select(\"path\").attr(\"d\",P);var I=s(r,n);p.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",I),p.clipDefRelative.select(\"path\").attr(\"transform\",null);var O=s(r-S._offset,n+a);p.layers.baxis.attr(\"transform\",O),p.layers.bgrid.attr(\"transform\",O);var z=s(r+i/2,n)+\"rotate(30)\"+s(0,-M._offset);p.layers.aaxis.attr(\"transform\",z),p.layers.agrid.attr(\"transform\",z);var D=s(r+i/2,n)+\"rotate(-30)\"+s(0,-L._offset);p.layers.caxis.attr(\"transform\",D),p.layers.cgrid.attr(\"transform\",D),p.drawAxes(!0),p.layers.aline.select(\"path\").attr(\"d\",M.showline?\"M\"+r+\",\"+(n+a)+\"l\"+i/2+\",-\"+a:\"M0,0\").call(c.stroke,M.linecolor||\"#000\").style(\"stroke-width\",(M.linewidth||0)+\"px\"),p.layers.bline.select(\"path\").attr(\"d\",S.showline?\"M\"+r+\",\"+(n+a)+\"h\"+i:\"M0,0\").call(c.stroke,S.linecolor||\"#000\").style(\"stroke-width\",(S.linewidth||0)+\"px\"),p.layers.cline.select(\"path\").attr(\"d\",L.showline?\"M\"+(r+i/2)+\",\"+n+\"l\"+i/2+\",\"+a:\"M0,0\").call(c.stroke,L.linecolor||\"#000\").style(\"stroke-width\",(L.linewidth||0)+\"px\"),p.graphDiv._context.staticPlot||p.initInteractions(),u.setClipUrl(p.layers.frontplot,p._hasClipOnAxisFalse?null:p.clipId,p.graphDiv)},S.drawAxes=function(t){var e=this.graphDiv,r=this.id.substr(7)+\"title\",n=this.layers,i=this.aaxis,a=this.baxis,o=this.caxis;if(this.drawAx(i),this.drawAx(a),this.drawAx(o),t){var s=Math.max(i.showticklabels?i.tickfont.size/2:0,(o.showticklabels?.75*o.tickfont.size:0)+(\"outside\"===o.ticks?.87*o.ticklen:0)),c=(a.showticklabels?a.tickfont.size:0)+(\"outside\"===a.ticks?a.ticklen:0)+3;n[\"a-title\"]=b.draw(e,\"a\"+r,{propContainer:i,propName:this.id+\".aaxis.title\",placeholder:l(e,\"Click to enter Component A title\"),attributes:{x:this.x0+this.w/2,y:this.y0-i.title.font.size/3-s,\"text-anchor\":\"middle\"}}),n[\"b-title\"]=b.draw(e,\"b\"+r,{propContainer:a,propName:this.id+\".baxis.title\",placeholder:l(e,\"Click to enter Component B title\"),attributes:{x:this.x0-c,y:this.y0+this.h+.83*a.title.font.size+c,\"text-anchor\":\"middle\"}}),n[\"c-title\"]=b.draw(e,\"c\"+r,{propContainer:o,propName:this.id+\".caxis.title\",placeholder:l(e,\"Click to enter Component C title\"),attributes:{x:this.x0+this.w+c,y:this.y0+this.h+.83*o.title.font.size+c,\"text-anchor\":\"middle\"}})}},S.drawAx=function(t){var e,r=this.graphDiv,n=t._name,i=n.charAt(0),a=t._id,s=this.layers[n],l=i+\"tickLayout\",c=(e=t).ticks+String(e.ticklen)+String(e.showticklabels);this[l]!==c&&(s.selectAll(\".\"+a+\"tick\").remove(),this[l]=c),t.setScale();var u=d.calcTicks(t),f=d.clipEnds(t,u),h=d.makeTransTickFn(t),p=d.getTickSigns(t)[2],g=o.deg2rad(30),m=p*(t.linewidth||1)/2,v=p*t.ticklen,y=this.w,x=this.h,b=\"b\"===i?\"M0,\"+m+\"l\"+Math.sin(g)*v+\",\"+Math.cos(g)*v:\"M\"+m+\",0l\"+Math.cos(g)*v+\",\"+-Math.sin(g)*v,_={a:\"M0,0l\"+x+\",-\"+y/2,b:\"M0,0l-\"+y/2+\",-\"+x,c:\"M0,0l-\"+x+\",\"+y/2}[i];d.drawTicks(r,t,{vals:\"inside\"===t.ticks?f:u,layer:s,path:b,transFn:h,crisp:!1}),d.drawGrid(r,t,{vals:f,layer:this.layers[i+\"grid\"],path:_,transFn:h,crisp:!1}),d.drawLabels(r,t,{vals:u,layer:s,transFn:h,labelFns:d.makeLabelFns(t,0,30)})};var L=A.MINZOOM/2+.87,C=\"m-0.87,.5h\"+L+\"v3h-\"+(L+5.2)+\"l\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l2.6,1.5l-\"+L/2+\",\"+.87*L+\"Z\",P=\"m0.87,.5h-\"+L+\"v3h\"+(L+5.2)+\"l-\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l-2.6,1.5l\"+L/2+\",\"+.87*L+\"Z\",I=\"m0,1l\"+L/2+\",\"+.87*L+\"l2.6,-1.5l-\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l-\"+(L/2+2.6)+\",\"+(.87*L+4.5)+\"l2.6,1.5l\"+L/2+\",-\"+.87*L+\"Z\",O=!0;function z(t){n.select(t).selectAll(\".zoombox,.js-zoombox-backdrop,.js-zoombox-menu,.zoombox-corners\").remove()}S.clearSelect=function(){k(this.dragOptions),T(this.dragOptions.gd)},S.initInteractions=function(){var t,e,r,n,f,h,p,d,v,b,T,k,M=this,S=M.layers.plotbg.select(\"path\").node(),L=M.graphDiv,D=L._fullLayout._zoomlayer;function R(t){var e={};return e[M.id+\".aaxis.min\"]=t.a,e[M.id+\".baxis.min\"]=t.b,e[M.id+\".caxis.min\"]=t.c,e}function F(t,e){var r=L._fullLayout.clickmode;z(L),2===t&&(L.emit(\"plotly_doubleclick\",null),a.call(\"_guiRelayout\",L,R({a:0,b:0,c:0}))),r.indexOf(\"select\")>-1&&1===t&&w(e,L,[M.xaxis],[M.yaxis],M.id,M.dragOptions),r.indexOf(\"event\")>-1&&m.click(L,e,M.id)}function B(t,e){return 1-e/M.h}function N(t,e){return 1-(t+(M.h-e)/Math.sqrt(3))/M.w}function j(t,e){return(t-(M.h-e)/Math.sqrt(3))/M.w}function U(i,a){var o=r+i*t,s=n+a*e,l=Math.max(0,Math.min(1,B(0,n),B(0,s))),c=Math.max(0,Math.min(1,N(r,n),N(o,s))),u=Math.max(0,Math.min(1,j(r,n),j(o,s))),g=(l/2+u)*M.w,m=(1-l/2-c)*M.w,y=(g+m)/2,x=m-g,_=(1-l)*M.h,w=_-x/E;x<A.MINZOOM?(p=f,T.attr(\"d\",v),k.attr(\"d\",\"M0,0Z\")):(p={a:f.a+l*h,b:f.b+c*h,c:f.c+u*h},T.attr(\"d\",v+\"M\"+g+\",\"+_+\"H\"+m+\"L\"+y+\",\"+w+\"L\"+g+\",\"+_+\"Z\"),k.attr(\"d\",\"M\"+r+\",\"+n+\"m0.5,0.5h5v-2h-5v-5h-2v5h-5v2h5v5h2ZM\"+g+\",\"+_+C+\"M\"+m+\",\"+_+P+\"M\"+y+\",\"+w+I)),b||(T.transition().style(\"fill\",d>.2?\"rgba(0,0,0,0.4)\":\"rgba(255,255,255,0.3)\").duration(200),k.transition().style(\"opacity\",1).duration(200),b=!0),L.emit(\"plotly_relayouting\",R(p))}function V(){z(L),p!==f&&(a.call(\"_guiRelayout\",L,R(p)),O&&L.data&&L._context.showTips&&(o.notifier(l(L,\"Double-click to zoom back out\"),\"long\"),O=!1))}function q(t,e){var r=t/M.xaxis._m,n=e/M.yaxis._m,i=[(p={a:f.a-n,b:f.b+(r+n)/2,c:f.c-(r-n)/2}).a,p.b,p.c].sort(o.sorterAsc),a=i.indexOf(p.a),l=i.indexOf(p.b),c=i.indexOf(p.c);i[0]<0&&(i[1]+i[0]/2<0?(i[2]+=i[0]+i[1],i[0]=i[1]=0):(i[2]+=i[0]/2,i[1]+=i[0]/2,i[0]=0),p={a:i[a],b:i[l],c:i[c]},e=(f.a-p.a)*M.yaxis._m,t=(f.c-p.c-f.b+p.b)*M.xaxis._m);var h=s(M.x0+t,M.y0+e);M.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",h);var d=s(-t,-e);M.clipDefRelative.select(\"path\").attr(\"transform\",d),M.aaxis.range=[p.a,M.sum-p.b-p.c],M.baxis.range=[M.sum-p.a-p.c,p.b],M.caxis.range=[M.sum-p.a-p.b,p.c],M.drawAxes(!1),M._hasClipOnAxisFalse&&M.plotContainer.select(\".scatterlayer\").selectAll(\".trace\").call(u.hideOutsideRangePoints,M),L.emit(\"plotly_relayouting\",R(p))}function H(){a.call(\"_guiRelayout\",L,R(p))}this.dragOptions={element:S,gd:L,plotinfo:{id:M.id,domain:L._fullLayout[M.id].domain,xaxis:M.xaxis,yaxis:M.yaxis},subplot:M.id,prepFn:function(a,l,u){M.dragOptions.xaxes=[M.xaxis],M.dragOptions.yaxes=[M.yaxis],t=L._fullLayout._invScaleX,e=L._fullLayout._invScaleY;var g=M.dragOptions.dragmode=L._fullLayout.dragmode;y(g)?M.dragOptions.minDrag=1:M.dragOptions.minDrag=void 0,\"zoom\"===g?(M.dragOptions.moveFn=U,M.dragOptions.clickFn=F,M.dragOptions.doneFn=V,function(t,e,a){var l=S.getBoundingClientRect();r=e-l.left,n=a-l.top,L._fullLayout._calcInverseTransform(L);var u=L._fullLayout._invTransform,g=o.apply3DTransform(u)(r,n);r=g[0],n=g[1],f={a:M.aaxis.range[0],b:M.baxis.range[1],c:M.caxis.range[1]},p=f,h=M.aaxis.range[1]-f.a,d=i(M.graphDiv._fullLayout[M.id].bgcolor).getLuminance(),v=\"M0,\"+M.h+\"L\"+M.w/2+\", 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n=t(\"../../components/fx\"),i=t(\"../../lib\"),a=t(\"../bar/hover\").getTraceColor,o=i.fillText,s=t(\"../scatterpolar/hover\").makeHoverPointText,l=t(\"../../plots/polar/helpers\").isPtInsidePolygon;e.exports=function(t,e,r){var c=t.cd,u=c[0].trace,f=t.subplot,h=f.radialAxis,p=f.angularAxis,d=f.vangles,g=d?l:i.isPtInsideSector,m=t.maxHoverDistance,v=p._period||2*Math.PI,y=Math.abs(h.g2p(Math.sqrt(e*e+r*r))),x=Math.atan2(r,e);h.range[0]>h.range[1]&&(x+=Math.PI);if(n.getClosest(c,(function(t){return g(y,x,[t.rp0,t.rp1],[t.thetag0,t.thetag1],d)?m+Math.min(1,Math.abs(t.thetag1-t.thetag0)/v)-1+(t.rp1-y)/(t.rp1-t.rp0)-1:1/0}),t),!1!==t.index){var b=c[t.index];t.x0=t.x1=b.ct[0],t.y0=t.y1=b.ct[1];var _=i.extendFlat({},b,{r:b.s,theta:b.p});return o(b,u,t),s(_,u,f,t),t.hovertemplate=u.hovertemplate,t.color=a(u,b),t.xLabelVal=t.yLabelVal=void 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n=t(\"../scatter/attributes\"),i=t(\"../bar/attributes\"),a=t(\"../../components/color/attributes\"),o=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../lib/extend\").extendFlat,c=n.marker,u=c.line;e.exports={y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},x0:{valType:\"any\",editType:\"calc+clearAxisTypes\"},y0:{valType:\"any\",editType:\"calc+clearAxisTypes\"},dx:{valType:\"number\",editType:\"calc\"},dy:{valType:\"number\",editType:\"calc\"},xperiod:n.xperiod,yperiod:n.yperiod,xperiod0:n.xperiod0,yperiod0:n.yperiod0,xperiodalignment:n.xperiodalignment,yperiodalignment:n.yperiodalignment,xhoverformat:o(\"x\"),yhoverformat:o(\"y\"),name:{valType:\"string\",editType:\"calc+clearAxisTypes\"},q1:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},median:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},q3:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},lowerfence:{valType:\"data_array\",editType:\"calc\"},upperfence:{valType:\"data_array\",editType:\"calc\"},notched:{valType:\"boolean\",editType:\"calc\"},notchwidth:{valType:\"number\",min:0,max:.5,dflt:.25,editType:\"calc\"},notchspan:{valType:\"data_array\",editType:\"calc\"},boxpoints:{valType:\"enumerated\",values:[\"all\",\"outliers\",\"suspectedoutliers\",!1],editType:\"calc\"},jitter:{valType:\"number\",min:0,max:1,editType:\"calc\"},pointpos:{valType:\"number\",min:-2,max:2,editType:\"calc\"},boxmean:{valType:\"enumerated\",values:[!0,\"sd\",!1],editType:\"calc\"},mean:{valType:\"data_array\",editType:\"calc\"},sd:{valType:\"data_array\",editType:\"calc\"},orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],editType:\"calc+clearAxisTypes\"},quartilemethod:{valType:\"enumerated\",values:[\"linear\",\"exclusive\",\"inclusive\"],dflt:\"linear\",editType:\"calc\"},width:{valType:\"number\",min:0,dflt:0,editType:\"calc\"},marker:{outliercolor:{valType:\"color\",dflt:\"rgba(0, 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f={xaxis:0,yaxis:1,zaxis:2},h={tip:1,tail:0,cm:.25,center:.5},p={tip:1,tail:1,cm:.75,center:.5};function d(t,e){var r=t.fullSceneLayout,i=t.dataScale,c={};function u(t,e){var n=r[e],o=i[f[e]];return a(t,(function(t){return n.d2l(t)*o}))}c.vectors=l(u(e.u,\"xaxis\"),u(e.v,\"yaxis\"),u(e.w,\"zaxis\"),e._len),c.positions=l(u(e.x,\"xaxis\"),u(e.y,\"yaxis\"),u(e.z,\"zaxis\"),e._len);var d=s(e);c.colormap=o(e),c.vertexIntensityBounds=[d.min/e._normMax,d.max/e._normMax],c.coneOffset=h[e.anchor],\"scaled\"===e.sizemode?c.coneSize=e.sizeref||.5:c.coneSize=e.sizeref&&e._normMax?e.sizeref/e._normMax:.5;var g=n(c),m=e.lightposition;return g.lightPosition=[m.x,m.y,m.z],g.ambient=e.lighting.ambient,g.diffuse=e.lighting.diffuse,g.specular=e.lighting.specular,g.roughness=e.lighting.roughness,g.fresnel=e.lighting.fresnel,g.opacity=e.opacity,e._pad=p[e.anchor]*g.vectorScale*g.coneScale*e._normMax,g}u.update=function(t){this.data=t;var 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n=t(\"../heatmap/attributes\"),i=t(\"../scatter/attributes\"),a=t(\"../../plots/cartesian/axis_format_attributes\"),o=a.axisHoverFormat,s=a.descriptionOnlyNumbers,l=t(\"../../components/colorscale/attributes\"),c=t(\"../../components/drawing/attributes\").dash,u=t(\"../../plots/font_attributes\"),f=t(\"../../lib/extend\").extendFlat,h=t(\"../../constants/filter_ops\"),p=h.COMPARISON_OPS2,d=h.INTERVAL_OPS,g=i.line;e.exports=f({z:n.z,x:n.x,x0:n.x0,dx:n.dx,y:n.y,y0:n.y0,dy:n.dy,xperiod:n.xperiod,yperiod:n.yperiod,xperiod0:i.xperiod0,yperiod0:i.yperiod0,xperiodalignment:n.xperiodalignment,yperiodalignment:n.yperiodalignment,text:n.text,hovertext:n.hovertext,transpose:n.transpose,xtype:n.xtype,ytype:n.ytype,xhoverformat:o(\"x\"),yhoverformat:o(\"y\"),zhoverformat:o(\"z\",1),hovertemplate:n.hovertemplate,hoverongaps:n.hoverongaps,connectgaps:f({},n.connectgaps,{}),fillcolor:{valType:\"color\",editType:\"calc\"},autocontour:{valType:\"boolean\",dflt:!0,editType:\"calc\",impliedEdits:{\"contours.start\":void 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r=t.marker,i=e.mc||r.color,a=e.mlc||r.line.color,o=e.mlw||r.line.width;if(n(i))return i;if(n(a)&&o)return a}(u,h),[l]}}},{\"../../components/color\":666,\"../../lib\":803,\"../bar/hover\":948}],1071:[function(t,e,r){\"use 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s=r||n.select(t).selectAll(\"g.funnellayer\").selectAll(\"g.trace\");l(t,s,\"funnel\"),s.style(\"opacity\",(function(t){return t[0].trace.opacity})),s.each((function(e){var r=n.select(this),s=e[0].trace;r.selectAll(\".point > path\").each((function(t){if(!t.isBlank){var e=s.marker;n.select(this).call(a.fill,t.mc||e.color).call(a.stroke,t.mlc||e.line.color).call(i.dashLine,e.line.dash,t.mlw||e.line.width).style(\"opacity\",s.selectedpoints&&!t.selected?o:1)}})),c(r,s,t),r.selectAll(\".regions\").each((function(){n.select(this).selectAll(\"path\").style(\"stroke-width\",0).call(a.fill,s.connector.fillcolor)})),r.selectAll(\".lines\").each((function(){var t=s.connector.line;i.lineGroupStyle(n.select(this).selectAll(\"path\"),t.width,t.color,t.dash)}))}))}}},{\"../../components/color\":666,\"../../components/drawing\":688,\"../../constants/interactions\":778,\"../bar/style\":955,\"../bar/uniform_text\":957,\"@plotly/d3\":58}],1076:[function(t,e,r){\"use strict\";var n=t(\"../pie/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../plots/domain\").attributes,o=t(\"../../plots/template_attributes\").hovertemplateAttrs,s=t(\"../../plots/template_attributes\").texttemplateAttrs,l=t(\"../../lib/extend\").extendFlat;e.exports={labels:n.labels,label0:n.label0,dlabel:n.dlabel,values:n.values,marker:{colors:n.marker.colors,line:{color:l({},n.marker.line.color,{dflt:null}),width:l({},n.marker.line.width,{dflt:1}),editType:\"calc\"},editType:\"calc\"},text:n.text,hovertext:n.hovertext,scalegroup:l({},n.scalegroup,{}),textinfo:l({},n.textinfo,{flags:[\"label\",\"text\",\"value\",\"percent\"]}),texttemplate:s({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"text\",\"percent\"]}),hoverinfo:l({},i.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:o({},{keys:[\"label\",\"color\",\"value\",\"text\",\"percent\"]}),textposition:l({},n.textposition,{values:[\"inside\",\"none\"],dflt:\"inside\"}),textfont:n.textfont,insidetextfont:n.insidetextfont,title:{text:n.title.text,font:n.title.font,position:l({},n.title.position,{values:[\"top 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n=t(\"../../lib\"),i=t(\"./attributes\"),a=t(\"../../plots/domain\").defaults,o=t(\"../bar/defaults\").handleText,s=t(\"../pie/defaults\").handleLabelsAndValues;e.exports=function(t,e,r,l){function c(r,a){return n.coerce(t,e,i,r,a)}var u=c(\"labels\"),f=c(\"values\"),h=s(u,f),p=h.len;if(e._hasLabels=h.hasLabels,e._hasValues=h.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),p){e._length=p,c(\"marker.line.width\")&&c(\"marker.line.color\",l.paper_bgcolor),c(\"marker.colors\"),c(\"scalegroup\");var d,g=c(\"text\"),m=c(\"texttemplate\");if(m||(d=c(\"textinfo\",Array.isArray(g)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),m||d&&\"none\"!==d){var v=c(\"textposition\");o(t,e,l,c,v,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1})}a(e,l,c),c(\"title.text\")&&(c(\"title.position\"),n.coerceFont(c,\"title.font\",l.font)),c(\"aspectratio\"),c(\"baseratio\")}else e.visible=!1}},{\"../../lib\":803,\"../../plots/domain\":882,\"../bar/defaults\":945,\"../pie/defaults\":1195,\"./attributes\":1076}],1080:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"funnelarea\",basePlotModule:t(\"./base_plot\"),categories:[\"pie-like\",\"funnelarea\",\"showLegend\"],attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\"),supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\"),style:t(\"./style\"),styleOne:t(\"../pie/style_one\"),meta:{}}},{\"../pie/style_one\":1203,\"./attributes\":1076,\"./base_plot\":1077,\"./calc\":1078,\"./defaults\":1079,\"./layout_attributes\":1081,\"./layout_defaults\":1082,\"./plot\":1083,\"./style\":1084}],1081:[function(t,e,r){\"use strict\";var n=t(\"../pie/layout_attributes\").hiddenlabels;e.exports={hiddenlabels:n,funnelareacolorway:{valType:\"colorlist\",editType:\"calc\"},extendfunnelareacolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{\"../pie/layout_attributes\":1199}],1082:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"funnelareacolorway\",e.colorway),r(\"extendfunnelareacolors\")}},{\"../../lib\":803,\"./layout_attributes\":1081}],1083:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../components/drawing\"),a=t(\"../../lib\"),o=a.strScale,s=a.strTranslate,l=t(\"../../lib/svg_text_utils\"),c=t(\"../bar/plot\").toMoveInsideBar,u=t(\"../bar/uniform_text\"),f=u.recordMinTextSize,h=u.clearMinTextSize,p=t(\"../pie/helpers\"),d=t(\"../pie/plot\"),g=d.attachFxHandlers,m=d.determineInsideTextFont,v=d.layoutAreas,y=d.prerenderTitles,x=d.positionTitleOutside,b=d.formatSliceLabel;function _(t,e){return\"l\"+(e[0]-t[0])+\",\"+(e[1]-t[1])}e.exports=function(t,e){var r=t._fullLayout;h(\"funnelarea\",r),y(e,t),v(e,r._size),a.makeTraceGroups(r._funnelarealayer,e,\"trace\").each((function(e){var u=n.select(this),h=e[0],d=h.trace;!function(t){if(!t.length)return;var e=t[0],r=e.trace,n=r.aspectratio,i=r.baseratio;i>.999&&(i=.999);var a,o=Math.pow(i,2),s=e.vTotal,l=s,c=s*o/(1-o)/s;function u(){var t,e={x:t=Math.sqrt(c),y:-t};return[e.x,e.y]}var f,h,p=[];for(p.push(u()),f=t.length-1;f>-1;f--)if(!(h=t[f]).hidden){var d=h.v/l;c+=d,p.push(u())}var 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w=\"M\"+(u+o.TR[0])+\",\"+(v+o.TR[1])+_(o.TR,o.BR)+_(o.BR,o.BL)+_(o.BL,o.TL)+\"Z\";x.attr(\"d\",w),b(t,o,h);var T=p.castOption(d.textposition,o.pts),k=y.selectAll(\"g.slicetext\").data(o.text&&\"none\"!==T?[0]:[]);k.enter().append(\"g\").classed(\"slicetext\",!0),k.exit().remove(),k.each((function(){var h=a.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),p=a.ensureUniformFontSize(t,m(d,o,r.font));h.text(o.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(i.font,p).call(l.convertToTspans,t);var g,y,x,b=i.bBox(h.node()),_=Math.min(o.BL[1],o.BR[1])+v,w=Math.max(o.TL[1],o.TR[1])+v;y=Math.max(o.TL[0],o.BL[0])+u,x=Math.min(o.TR[0],o.BR[0])+u,(g=c(y,x,_,w,b,{isHorizontal:!0,constrained:!0,angle:0,anchor:\"middle\"})).fontSize=p.size,f(d.type,g,r),e[s].transform=g,h.attr(\"transform\",a.getTextTransform(g))}))}}));var 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0===e.delta.font.size&&(e.delta.font.size=(e._hasNumber?.5:1)*(m||l.defaultNumberFontSize),w[1]=!0),d(\"delta.reference\",e.value),d(\"delta.relative\"),d(\"delta.valueformat\",e.delta.relative?\"2%\":\"\"),d(\"delta.increasing.symbol\"),d(\"delta.increasing.color\"),d(\"delta.decreasing.symbol\"),d(\"delta.decreasing.color\"),d(\"delta.position\"),v=e.delta.font.size),e._scaleNumbers=(!e._hasNumber||w[0])&&(!e._hasDelta||w[1])||!1,d(\"title.font.color\",p.font.color),d(\"title.font.family\",p.font.family),d(\"title.font.size\",.25*(m||v||l.defaultNumberFontSize)),d(\"title.text\"),e._hasGauge){(y=t.gauge)||(y={}),x=o.newContainer(e,\"gauge\"),T(\"shape\"),(e._isBullet=\"bullet\"===e.gauge.shape)||d(\"title.align\",\"center\"),(e._isAngular=\"angular\"===e.gauge.shape)||d(\"align\",\"center\"),T(\"bgcolor\",p.paper_bgcolor),T(\"borderwidth\"),T(\"bordercolor\"),T(\"bar.color\"),T(\"bar.line.color\"),T(\"bar.line.width\"),T(\"bar.thickness\",l.valueThickness*(\"bullet\"===e.gauge.shape?.5:1)),s(y,x,{name:\"steps\",handleItemDefaults:h}),T(\"threshold.value\"),T(\"threshold.thickness\"),T(\"threshold.line.width\"),T(\"threshold.line.color\"),b={},y&&(b=y.axis||{}),_=o.newContainer(x,\"axis\"),k(\"visible\"),e._range=k(\"range\",e._range);var A={outerTicks:!0};c(b,_,k,\"linear\"),f(b,_,k,\"linear\",A),u(b,_,k,A)}else d(\"title.align\",\"center\"),d(\"align\",\"center\"),e._isAngular=e._isBullet=!1;e._length=null}}},{\"../../lib\":803,\"../../plot_api/plot_template\":843,\"../../plots/array_container_defaults\":849,\"../../plots/cartesian/tick_label_defaults\":876,\"../../plots/cartesian/tick_mark_defaults\":877,\"../../plots/cartesian/tick_value_defaults\":878,\"../../plots/domain\":882,\"./attributes\":1147,\"./constants.js\":1150}],1152:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"indicator\",basePlotModule:t(\"./base_plot\"),categories:[\"svg\",\"noOpacity\",\"noHover\"],animatable:!0,attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,calc:t(\"./calc\").calc,plot:t(\"./plot\"),meta:{}}},{\"./attributes\":1147,\"./base_plot\":1148,\"./calc\":1149,\"./defaults\":1151,\"./plot\":1153}],1153:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"d3-interpolate\").interpolate,a=t(\"d3-interpolate\").interpolateNumber,o=t(\"../../lib\"),s=o.strScale,l=o.strTranslate,c=o.rad2deg,u=t(\"../../constants/alignment\").MID_SHIFT,f=t(\"../../components/drawing\"),h=t(\"./constants\"),p=t(\"../../lib/svg_text_utils\"),d=t(\"../../plots/cartesian/axes\"),g=t(\"../../plots/cartesian/axis_defaults\"),m=t(\"../../plots/cartesian/position_defaults\"),v=t(\"../../plots/cartesian/layout_attributes\"),y=t(\"../../components/color\"),x={left:\"start\",center:\"middle\",right:\"end\"},b={left:0,center:.5,right:1},_=/[yzafpn\\xb5mkMGTPEZY]/;function w(t){return t&&t.duration>0}function T(t){t.each((function(t){y.stroke(n.select(this),t.line.color)})).each((function(t){y.fill(n.select(this),t.color)})).style(\"stroke-width\",(function(t){return t.line.width}))}function k(t,e,r){var n=t._fullLayout,i=o.extendFlat({type:\"linear\",ticks:\"outside\",range:r,showline:!0},e),a={type:\"linear\",_id:\"x\"+e._id},s={letter:\"x\",font:n.font,noHover:!0,noTickson:!0};function l(t,e){return o.coerce(i,a,v,t,e)}return g(i,a,l,s,n),m(i,a,l,s),a}function A(t,e,r){return[Math.min(e/t.width,r/t.height),t,e+\"x\"+r]}function M(t,e,r,i){var a=document.createElementNS(\"http://www.w3.org/2000/svg\",\"text\"),o=n.select(a);return o.text(t).attr(\"x\",0).attr(\"y\",0).attr(\"text-anchor\",r).attr(\"data-unformatted\",t).call(p.convertToTspans,i).call(f.font,e),f.bBox(o.node())}function S(t,e,r,n,i,a){var s=\"_cache\"+e;t[s]&&t[s].key===i||(t[s]={key:i,value:r});var l=o.aggNums(a,null,[t[s].value,n],2);return t[s].value=l,l}e.exports=function(t,e,r,g){var m,v=t._fullLayout;w(r)&&g&&(m=g()),o.makeTraceGroups(v._indicatorlayer,e,\"trace\").each((function(e){var g,E,L,C,P,I=e[0].trace,O=n.select(this),z=I._hasGauge,D=I._isAngular,R=I._isBullet,F=I.domain,B={w:v._size.w*(F.x[1]-F.x[0]),h:v._size.h*(F.y[1]-F.y[0]),l:v._size.l+v._size.w*F.x[0],r:v._size.r+v._size.w*(1-F.x[1]),t:v._size.t+v._size.h*(1-F.y[1]),b:v._size.b+v._size.h*F.y[0]},N=B.l+B.w/2,j=B.t+B.h/2,U=Math.min(B.w/2,B.h),V=h.innerRadius*U,q=I.align||\"center\";if(E=j,z){if(D&&(g=N,E=j+U/2,L=function(t){return function(t,e){var r=Math.sqrt(t.width/2*(t.width/2)+t.height*t.height);return[e/r,t,e]}(t,.9*V)}),R){var H=h.bulletPadding,G=1-h.bulletNumberDomainSize+H;g=B.l+(G+(1-G)*b[q])*B.w,L=function(t){return A(t,(h.bulletNumberDomainSize-H)*B.w,B.h)}}}else g=B.l+b[q]*B.w,L=function(t){return A(t,B.w,B.h)};!function(t,e,r,i){var c,u,h,g=r[0].trace,m=i.numbersX,v=i.numbersY,T=g.align||\"center\",A=x[T],E=i.transitionOpts,L=i.onComplete,C=o.ensureSingle(e,\"g\",\"numbers\"),P=[];g._hasNumber&&P.push(\"number\");g._hasDelta&&(P.push(\"delta\"),\"left\"===g.delta.position&&P.reverse());var I=C.selectAll(\"text\").data(P);function O(e,r,n,i){if(!e.match(\"s\")||n>=0==i>=0||r(n).slice(-1).match(_)||r(i).slice(-1).match(_))return r;var a=e.slice().replace(\"s\",\"f\").replace(/\\d+/,(function(t){return parseInt(t)-1})),o=k(t,{tickformat:a});return function(t){return Math.abs(t)<1?d.tickText(o,t).text:r(t)}}I.enter().append(\"text\"),I.attr(\"text-anchor\",(function(){return A})).attr(\"class\",(function(t){return t})).attr(\"x\",null).attr(\"y\",null).attr(\"dx\",null).attr(\"dy\",null),I.exit().remove();var z,D=g.mode+g.align;g._hasDelta&&(z=function(){var e=k(t,{tickformat:g.delta.valueformat},g._range);e.setScale(),d.prepTicks(e);var i=function(t){return d.tickText(e,t).text},o=function(t){return g.delta.relative?t.relativeDelta:t.delta},s=function(t,e){return 0===t||\"number\"!=typeof t||isNaN(t)?\"-\":(t>0?g.delta.increasing.symbol:g.delta.decreasing.symbol)+e(t)},l=function(t){return t.delta>=0?g.delta.increasing.color:g.delta.decreasing.color};void 0===g._deltaLastValue&&(g._deltaLastValue=o(r[0]));var c=C.select(\"text.delta\");function h(){c.text(s(o(r[0]),i)).call(y.fill,l(r[0])).call(p.convertToTspans,t)}return c.call(f.font,g.delta.font).call(y.fill,l({delta:g._deltaLastValue})),w(E)?c.transition().duration(E.duration).ease(E.easing).tween(\"text\",(function(){var t=n.select(this),e=o(r[0]),c=g._deltaLastValue,u=O(g.delta.valueformat,i,c,e),f=a(c,e);return g._deltaLastValue=e,function(e){t.text(s(f(e),u)),t.call(y.fill,l({delta:f(e)}))}})).each(\"end\",(function(){h(),L&&L()})).each(\"interrupt\",(function(){h(),L&&L()})):h(),u=M(s(o(r[0]),i),g.delta.font,A,t),c}(),D+=g.delta.position+g.delta.font.size+g.delta.font.family+g.delta.valueformat,D+=g.delta.increasing.symbol+g.delta.decreasing.symbol,h=u);g._hasNumber&&(!function(){var e=k(t,{tickformat:g.number.valueformat},g._range);e.setScale(),d.prepTicks(e);var i=function(t){return d.tickText(e,t).text},o=g.number.suffix,s=g.number.prefix,l=C.select(\"text.number\");function u(){var e=\"number\"==typeof r[0].y?s+i(r[0].y)+o:\"-\";l.text(e).call(f.font,g.number.font).call(p.convertToTspans,t)}w(E)?l.transition().duration(E.duration).ease(E.easing).each(\"end\",(function(){u(),L&&L()})).each(\"interrupt\",(function(){u(),L&&L()})).attrTween(\"text\",(function(){var t=n.select(this),e=a(r[0].lastY,r[0].y);g._lastValue=r[0].y;var l=O(g.number.valueformat,i,r[0].lastY,r[0].y);return function(r){t.text(s+l(e(r))+o)}})):u(),c=M(s+i(r[0].y)+o,g.number.font,A,t)}(),D+=g.number.font.size+g.number.font.family+g.number.valueformat+g.number.suffix+g.number.prefix,h=c);if(g._hasDelta&&g._hasNumber){var R,F,B=[(c.left+c.right)/2,(c.top+c.bottom)/2],N=[(u.left+u.right)/2,(u.top+u.bottom)/2],j=.75*g.delta.font.size;\"left\"===g.delta.position&&(R=S(g,\"deltaPos\",0,-1*(c.width*b[g.align]+u.width*(1-b[g.align])+j),D,Math.min),F=B[1]-N[1],h={width:c.width+u.width+j,height:Math.max(c.height,u.height),left:u.left+R,right:c.right,top:Math.min(c.top,u.top+F),bottom:Math.max(c.bottom,u.bottom+F)}),\"right\"===g.delta.position&&(R=S(g,\"deltaPos\",0,c.width*(1-b[g.align])+u.width*b[g.align]+j,D,Math.max),F=B[1]-N[1],h={width:c.width+u.width+j,height:Math.max(c.height,u.height),left:c.left,right:u.right+R,top:Math.min(c.top,u.top+F),bottom:Math.max(c.bottom,u.bottom+F)}),\"bottom\"===g.delta.position&&(R=null,F=u.height,h={width:Math.max(c.width,u.width),height:c.height+u.height,left:Math.min(c.left,u.left),right:Math.max(c.right,u.right),top:c.bottom-c.height,bottom:c.bottom+u.height}),\"top\"===g.delta.position&&(R=null,F=c.top,h={width:Math.max(c.width,u.width),height:c.height+u.height,left:Math.min(c.left,u.left),right:Math.max(c.right,u.right),top:c.bottom-c.height-u.height,bottom:c.bottom}),z.attr({dx:R,dy:F})}(g._hasNumber||g._hasDelta)&&C.attr(\"transform\",(function(){var t=i.numbersScaler(h);D+=t[2];var e,r=S(g,\"numbersScale\",1,t[0],D,Math.min);g._scaleNumbers||(r=1),e=g._isAngular?v-r*h.bottom:v-r*(h.top+h.bottom)/2,g._numbersTop=r*h.top+e;var n=h[T];\"center\"===T&&(n=(h.left+h.right)/2);var a=m-r*n;return a=S(g,\"numbersTranslate\",0,a,D,Math.max),l(a,e)+s(r)}))}(t,O,e,{numbersX:g,numbersY:E,numbersScaler:L,transitionOpts:r,onComplete:m}),z&&(C={range:I.gauge.axis.range,color:I.gauge.bgcolor,line:{color:I.gauge.bordercolor,width:0},thickness:1},P={range:I.gauge.axis.range,color:\"rgba(0, 0, 0, 0)\",line:{color:I.gauge.bordercolor,width:I.gauge.borderwidth},thickness:1});var Y=O.selectAll(\"g.angular\").data(D?e:[]);Y.exit().remove();var W=O.selectAll(\"g.angularaxis\").data(D?e:[]);W.exit().remove(),D&&function(t,e,r,a){var o,s,f,h,p=r[0].trace,g=a.size,m=a.radius,v=a.innerRadius,y=a.gaugeBg,x=a.gaugeOutline,b=[g.l+g.w/2,g.t+g.h/2+m/2],_=a.gauge,A=a.layer,M=a.transitionOpts,S=a.onComplete,E=Math.PI/2;function L(t){var e=p.gauge.axis.range[0],r=(t-e)/(p.gauge.axis.range[1]-e)*Math.PI-E;return r<-E?-E:r>E?E:r}function C(t){return n.svg.arc().innerRadius((v+m)/2-t/2*(m-v)).outerRadius((v+m)/2+t/2*(m-v)).startAngle(-E)}function P(t){t.attr(\"d\",(function(t){return C(t.thickness).startAngle(L(t.range[0])).endAngle(L(t.range[1]))()}))}_.enter().append(\"g\").classed(\"angular\",!0),_.attr(\"transform\",l(b[0],b[1])),A.enter().append(\"g\").classed(\"angularaxis\",!0).classed(\"crisp\",!0),A.selectAll(\"g.xangularaxistick,path,text\").remove(),(o=k(t,p.gauge.axis)).type=\"linear\",o.range=p.gauge.axis.range,o._id=\"xangularaxis\",o.ticklabeloverflow=\"allow\",o.setScale();var I=function(t){return(o.range[0]-t.x)/(o.range[1]-o.range[0])*Math.PI+Math.PI},O={},z=d.makeLabelFns(o,0).labelStandoff;O.xFn=function(t){var e=I(t);return Math.cos(e)*z},O.yFn=function(t){var e=I(t),r=Math.sin(e)>0?.2:1;return-Math.sin(e)*(z+t.fontSize*r)+Math.abs(Math.cos(e))*(t.fontSize*u)},O.anchorFn=function(t){var e=I(t),r=Math.cos(e);return Math.abs(r)<.1?\"middle\":r>0?\"start\":\"end\"},O.heightFn=function(t,e,r){var n=I(t);return-.5*(1+Math.sin(n))*r};var D=function(t){return l(b[0]+m*Math.cos(t),b[1]-m*Math.sin(t))};f=function(t){return D(I(t))};if(s=d.calcTicks(o),h=d.getTickSigns(o)[2],o.visible){h=\"inside\"===o.ticks?-1:1;var R=(o.linewidth||1)/2;d.drawTicks(t,o,{vals:s,layer:A,path:\"M\"+h*R+\",0h\"+h*o.ticklen,transFn:function(t){var e=I(t);return D(e)+\"rotate(\"+-c(e)+\")\"}}),d.drawLabels(t,o,{vals:s,layer:A,transFn:f,labelFns:O})}var F=[y].concat(p.gauge.steps),B=_.selectAll(\"g.bg-arc\").data(F);B.enter().append(\"g\").classed(\"bg-arc\",!0).append(\"path\"),B.select(\"path\").call(P).call(T),B.exit().remove();var N=C(p.gauge.bar.thickness),j=_.selectAll(\"g.value-arc\").data([p.gauge.bar]);j.enter().append(\"g\").classed(\"value-arc\",!0).append(\"path\");var U=j.select(\"path\");w(M)?(U.transition().duration(M.duration).ease(M.easing).each(\"end\",(function(){S&&S()})).each(\"interrupt\",(function(){S&&S()})).attrTween(\"d\",(V=N,q=L(r[0].lastY),H=L(r[0].y),function(){var t=i(q,H);return function(e){return V.endAngle(t(e))()}})),p._lastValue=r[0].y):U.attr(\"d\",\"number\"==typeof r[0].y?N.endAngle(L(r[0].y)):\"M0,0Z\");var V,q,H;U.call(T),j.exit().remove(),F=[];var G=p.gauge.threshold.value;(G||0===G)&&F.push({range:[G,G],color:p.gauge.threshold.color,line:{color:p.gauge.threshold.line.color,width:p.gauge.threshold.line.width},thickness:p.gauge.threshold.thickness});var Y=_.selectAll(\"g.threshold-arc\").data(F);Y.enter().append(\"g\").classed(\"threshold-arc\",!0).append(\"path\"),Y.select(\"path\").call(P).call(T),Y.exit().remove();var W=_.selectAll(\"g.gauge-outline\").data([x]);W.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"path\"),W.select(\"path\").call(P).call(T),W.exit().remove()}(t,0,e,{radius:U,innerRadius:V,gauge:Y,layer:W,size:B,gaugeBg:C,gaugeOutline:P,transitionOpts:r,onComplete:m});var X=O.selectAll(\"g.bullet\").data(R?e:[]);X.exit().remove();var Z=O.selectAll(\"g.bulletaxis\").data(R?e:[]);Z.exit().remove(),R&&function(t,e,r,n){var i,a,o,s,c,u=r[0].trace,f=n.gauge,p=n.layer,g=n.gaugeBg,m=n.gaugeOutline,v=n.size,x=u.domain,b=n.transitionOpts,_=n.onComplete;f.enter().append(\"g\").classed(\"bullet\",!0),f.attr(\"transform\",l(v.l,v.t)),p.enter().append(\"g\").classed(\"bulletaxis\",!0).classed(\"crisp\",!0),p.selectAll(\"g.xbulletaxistick,path,text\").remove();var A=v.h,M=u.gauge.bar.thickness*A,S=x.x[0],E=x.x[0]+(x.x[1]-x.x[0])*(u._hasNumber||u._hasDelta?1-h.bulletNumberDomainSize:1);(i=k(t,u.gauge.axis))._id=\"xbulletaxis\",i.domain=[S,E],i.setScale(),a=d.calcTicks(i),o=d.makeTransTickFn(i),s=d.getTickSigns(i)[2],c=v.t+v.h,i.visible&&(d.drawTicks(t,i,{vals:\"inside\"===i.ticks?d.clipEnds(i,a):a,layer:p,path:d.makeTickPath(i,c,s),transFn:o}),d.drawLabels(t,i,{vals:a,layer:p,transFn:o,labelFns:d.makeLabelFns(i,c)}));function L(t){t.attr(\"width\",(function(t){return Math.max(0,i.c2p(t.range[1])-i.c2p(t.range[0]))})).attr(\"x\",(function(t){return i.c2p(t.range[0])})).attr(\"y\",(function(t){return.5*(1-t.thickness)*A})).attr(\"height\",(function(t){return t.thickness*A}))}var C=[g].concat(u.gauge.steps),P=f.selectAll(\"g.bg-bullet\").data(C);P.enter().append(\"g\").classed(\"bg-bullet\",!0).append(\"rect\"),P.select(\"rect\").call(L).call(T),P.exit().remove();var I=f.selectAll(\"g.value-bullet\").data([u.gauge.bar]);I.enter().append(\"g\").classed(\"value-bullet\",!0).append(\"rect\"),I.select(\"rect\").attr(\"height\",M).attr(\"y\",(A-M)/2).call(T),w(b)?I.select(\"rect\").transition().duration(b.duration).ease(b.easing).each(\"end\",(function(){_&&_()})).each(\"interrupt\",(function(){_&&_()})).attr(\"width\",Math.max(0,i.c2p(Math.min(u.gauge.axis.range[1],r[0].y)))):I.select(\"rect\").attr(\"width\",\"number\"==typeof r[0].y?Math.max(0,i.c2p(Math.min(u.gauge.axis.range[1],r[0].y))):0);I.exit().remove();var O=r.filter((function(){return u.gauge.threshold.value||0===u.gauge.threshold.value})),z=f.selectAll(\"g.threshold-bullet\").data(O);z.enter().append(\"g\").classed(\"threshold-bullet\",!0).append(\"line\"),z.select(\"line\").attr(\"x1\",i.c2p(u.gauge.threshold.value)).attr(\"x2\",i.c2p(u.gauge.threshold.value)).attr(\"y1\",(1-u.gauge.threshold.thickness)/2*A).attr(\"y2\",(1-(1-u.gauge.threshold.thickness)/2)*A).call(y.stroke,u.gauge.threshold.line.color).style(\"stroke-width\",u.gauge.threshold.line.width),z.exit().remove();var D=f.selectAll(\"g.gauge-outline\").data([m]);D.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"rect\"),D.select(\"rect\").call(L).call(T),D.exit().remove()}(t,0,e,{gauge:X,layer:Z,size:B,gaugeBg:C,gaugeOutline:P,transitionOpts:r,onComplete:m});var J=O.selectAll(\"text.title\").data(e);J.exit().remove(),J.enter().append(\"text\").classed(\"title\",!0),J.attr(\"text-anchor\",(function(){return 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n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../mesh3d/attributes\"),s=t(\"../../plots/attributes\"),l=t(\"../../lib/extend\").extendFlat,c=t(\"../../plot_api/edit_types\").overrideAll;var 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n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../surface/attributes\"),s=t(\"../../plots/attributes\"),l=t(\"../../lib/extend\").extendFlat;e.exports=l({x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},i:{valType:\"data_array\",editType:\"calc\"},j:{valType:\"data_array\",editType:\"calc\"},k:{valType:\"data_array\",editType:\"calc\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:a({editType:\"calc\"}),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),delaunayaxis:{valType:\"enumerated\",values:[\"x\",\"y\",\"z\"],dflt:\"z\",editType:\"calc\"},alphahull:{valType:\"number\",dflt:-1,editType:\"calc\"},intensity:{valType:\"data_array\",editType:\"calc\"},intensitymode:{valType:\"enumerated\",values:[\"vertex\",\"cell\"],dflt:\"vertex\",editType:\"calc\"},color:{valType:\"color\",editType:\"calc\"},vertexcolor:{valType:\"data_array\",editType:\"calc\"},facecolor:{valType:\"data_array\",editType:\"calc\"},transforms:void 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n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){e.intensity&&n(t,e,{vals:e.intensity,containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":674}],1161:[function(t,e,r){\"use strict\";var n=t(\"gl-mesh3d\"),i=t(\"delaunay-triangulate\"),a=t(\"alpha-shape\"),o=t(\"convex-hull\"),s=t(\"../../lib/gl_format_color\").parseColorScale,l=t(\"../../lib/str2rgbarray\"),c=t(\"../../components/colorscale\").extractOpts,u=t(\"../../plots/gl3d/zip3\");function f(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name=\"\",this.color=\"#fff\",this.data=null,this.showContour=!1}var h=f.prototype;function p(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=l(t[n]);return e}function d(t,e,r,n){for(var i=[],a=e.length,o=0;o<a;o++)i[o]=t.d2l(e[o],0,n)*r;return i}function g(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=Math.round(t[n]);return e}function m(t,e){for(var r=t.length,n=0;n<r;n++)if(t[n]<=-.5||t[n]>=e-.5)return!1;return!0}h.handlePick=function(t){if(t.object===this.mesh){var e=t.index=t.data.index;t.data._cellCenter?t.traceCoordinate=t.data.dataCoordinate:t.traceCoordinate=[this.data.x[e],this.data.y[e],this.data.z[e]];var r=this.data.hovertext||this.data.text;return Array.isArray(r)&&void 0!==r[e]?t.textLabel=r[e]:r&&(t.textLabel=r),!0}},h.update=function(t){var e=this.scene,r=e.fullSceneLayout;this.data=t;var n,f=t.x.length,h=u(d(r.xaxis,t.x,e.dataScale[0],t.xcalendar),d(r.yaxis,t.y,e.dataScale[1],t.ycalendar),d(r.zaxis,t.z,e.dataScale[2],t.zcalendar));if(t.i&&t.j&&t.k){if(t.i.length!==t.j.length||t.j.length!==t.k.length||!m(t.i,f)||!m(t.j,f)||!m(t.k,f))return;n=u(g(t.i),g(t.j),g(t.k))}else n=0===t.alphahull?o(h):t.alphahull>0?a(t.alphahull,h):function(t,e){for(var r=[\"x\",\"y\",\"z\"].indexOf(t),n=[],a=e.length,o=0;o<a;o++)n[o]=[e[o][(r+1)%3],e[o][(r+2)%3]];return i(n)}(t.delaunayaxis,h);var v={positions:h,cells:n,lightPosition:[t.lightposition.x,t.lightposition.y,t.lightposition.z],ambient:t.lighting.ambient,diffuse:t.lighting.diffuse,specular:t.lighting.specular,roughness:t.lighting.roughness,fresnel:t.lighting.fresnel,vertexNormalsEpsilon:t.lighting.vertexnormalsepsilon,faceNormalsEpsilon:t.lighting.facenormalsepsilon,opacity:t.opacity,contourEnable:t.contour.show,contourColor:l(t.contour.color).slice(0,3),contourWidth:t.contour.width,useFacetNormals:t.flatshading};if(t.intensity){var y=c(t);this.color=\"#fff\";var x=t.intensitymode;v[x+\"Intensity\"]=t.intensity,v[x+\"IntensityBounds\"]=[y.min,y.max],v.colormap=s(t)}else t.vertexcolor?(this.color=t.vertexcolor[0],v.vertexColors=p(t.vertexcolor)):t.facecolor?(this.color=t.facecolor[0],v.cellColors=p(t.facecolor)):(this.color=t.color,v.meshColor=l(t.color));this.mesh.update(v)},h.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},e.exports=function(t,e){var r=t.glplot.gl,i=n({gl:r}),a=new f(t,i,e.uid);return i._trace=a,a.update(e),t.glplot.add(i),a}},{\"../../components/colorscale\":678,\"../../lib/gl_format_color\":799,\"../../lib/str2rgbarray\":828,\"../../plots/gl3d/zip3\":907,\"alpha-shape\":75,\"convex-hull\":141,\"delaunay-triangulate\":180,\"gl-mesh3d\":315}],1162:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../../components/colorscale/defaults\"),o=t(\"./attributes\");e.exports=function(t,e,r,s){function l(r,n){return i.coerce(t,e,o,r,n)}function c(t){var e=t.map((function(t){var e=l(t);return e&&i.isArrayOrTypedArray(e)?e:null}));return e.every((function(t){return 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n=t(\"../../lib\").extendFlat,i=t(\"../scatter/attributes\"),a=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,o=t(\"../../components/drawing/attributes\").dash,s=t(\"../../components/fx/attributes\"),l=t(\"../../constants/delta.js\"),c=l.INCREASING.COLOR,u=l.DECREASING.COLOR,f=i.line;function 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E=S.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);S.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})).attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"perpendicular\"===t.parcatsViewModel.arrangement?\"ns-resize\":\"move\"})),k(E),S.exit().remove(),M.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\");var z=e._fullLayout.paper_bgcolor;A.select(\"text.catlabel\").attr(\"text-anchor\",(function(t){return d(t)?\"start\":\"end\"})).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",f.makeTextShadow(z)).style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",(function(t){return d(t)?t.width+5:-5})).attr(\"y\",(function(t){return t.height/2})).text((function(t){return t.model.categoryLabel})).each((function(t){c.font(n.select(this),t.parcatsViewModel.categorylabelfont),f.convertToTspans(n.select(this),e)})),M.append(\"text\").attr(\"class\",\"dimlabel\"),A.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"})).attr(\"x\",(function(t){return t.width/2})).attr(\"y\",-5).text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})).each((function(t){c.font(n.select(this),t.parcatsViewModel.labelfont)})),A.selectAll(\"rect.bandrect\").on(\"mouseover\",L).on(\"mouseout\",C),A.exit().remove(),w.call(n.behavior.drag().origin((function(t){return{x:t.x,y:0}})).on(\"dragstart\",P).on(\"drag\",I).on(\"dragend\",O)),u.each((function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),t.dimensionSelection=n.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")})),u.exit().remove()}function p(t){return t.key}function d(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function g(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function m(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){s.raiseToTop(this),w(n.select(this));var e=y(t),r=x(t);if(t.parcatsViewModel.graphDiv.emit(\"plotly_hover\",{points:e,event:n.event,constraints:r}),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\")){var i,a,l,c=n.mouse(this)[0],f=t.parcatsViewModel.graphDiv,h=t.parcatsViewModel.trace,p=f._fullLayout,d=p._paperdiv.node().getBoundingClientRect(),g=t.parcatsViewModel.graphDiv.getBoundingClientRect();for(l=0;l<t.leftXs.length-1;l++)if(t.leftXs[l]+t.dimWidths[l]-2<=c&&c<=t.leftXs[l+1]+2){var m=t.parcatsViewModel.dimensions[l],v=t.parcatsViewModel.dimensions[l+1];i=(m.x+m.width+v.x)/2,a=(t.topYs[l]+t.topYs[l+1]+t.height)/2;break}var b=t.parcatsViewModel.x+i,_=t.parcatsViewModel.y+a,T=u.mostReadable(t.model.color,[\"black\",\"white\"]),k=t.model.count,A=k/t.parcatsViewModel.model.count,M={countLabel:k,probabilityLabel:A.toFixed(3)},S=[];-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&S.push([\"Count:\",M.countLabel].join(\" \")),-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&S.push([\"P:\",M.probabilityLabel].join(\" \"));var E=S.join(\"<br>\"),L=n.mouse(f)[0];o.loneHover({trace:h,x:b-d.left+g.left,y:_-d.top+g.top,text:E,color:t.model.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:10,fontColor:T,idealAlign:L<b?\"right\":\"left\",hovertemplate:(h.line||{}).hovertemplate,hovertemplateLabels:M,eventData:[{data:h._input,fullData:h,count:k,probability:A}]},{container:p._hoverlayer.node(),outerContainer:p._paper.node(),gd:f})}}}function v(t){if(!t.parcatsViewModel.dragDimension&&(_(n.select(this)),o.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),t.parcatsViewModel.pathSelection.sort(g),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\"))){var e=y(t),r=x(t);t.parcatsViewModel.graphDiv.emit(\"plotly_unhover\",{points:e,event:n.event,constraints:r})}}function y(t){for(var e=[],r=z(t.parcatsViewModel),n=0;n<t.model.valueInds.length;n++){var i=t.model.valueInds[n];e.push({curveNumber:r,pointNumber:i})}return e}function x(t){for(var e={},r=t.parcatsViewModel.model.dimensions,n=0;n<r.length;n++){var i=r[n],a=i.categories[t.model.categoryInds[n]];e[i.containerInd]=a.categoryValue}return void 0!==t.model.rawColor&&(e.color=t.model.rawColor),e}function b(t){if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){var e=y(t),r=x(t);t.parcatsViewModel.graphDiv.emit(\"plotly_click\",{points:e,event:n.event,constraints:r})}}function _(t){t.attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",.6).attr(\"stroke\",\"lightgray\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1)}function w(t){t.attr(\"fill-opacity\",.8).attr(\"stroke\",(function(t){return u.mostReadable(t.model.color,[\"black\",\"white\"])})).attr(\"stroke-width\",.3)}function T(t){t.select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",1).attr(\"stroke-opacity\",1)}function k(t){t.attr(\"stroke\",\"black\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1).attr(\"fill-opacity\",1)}function A(t){var e=t.parcatsViewModel.pathSelection,r=t.categoryViewModel.model.dimensionInd,n=t.categoryViewModel.model.categoryInd;return e.filter((function(e){return e.model.categoryInds[r]===n&&e.model.color===t.color}))}function M(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=n.select(t.parentNode).selectAll(\"rect.bandrect\"),l=[];s.each((function(t){A(t).each((function(t){Array.prototype.push.apply(l,y(t))}))}));var c={};c[a.dimensionInd]=a.categoryValue,o.emit(e,{points:l,event:r,constraints:c})}function S(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=A(i),l=[];s.each((function(t){Array.prototype.push.apply(l,y(t))}));var c={};c[a.dimensionInd]=a.categoryValue,void 0!==i.rawColor&&(c.color=i.rawColor),o.emit(e,{points:l,event:r,constraints:c})}function E(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=n.select(r.parentNode).select(\"rect.catrect\"),c=l.node().getBoundingClientRect(),u=l.datum(),f=u.parcatsViewModel,h=f.model.dimensions[u.model.dimensionInd],p=f.trace,d=c.top+c.height/2;f.dimensions.length>1&&h.displayInd===f.dimensions.length-1?(i=c.left,a=\"left\"):(i=c.left+c.width,a=\"right\");var g=u.model.count,m=u.model.categoryLabel,v=g/u.parcatsViewModel.model.count,y={countLabel:g,categoryLabel:m,probabilityLabel:v.toFixed(3)},x=[];-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&x.push([\"Count:\",y.countLabel].join(\" \")),-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&x.push([\"P(\"+y.categoryLabel+\"):\",y.probabilityLabel].join(\" \"));var b=x.join(\"<br>\");return{trace:p,x:o*(i-e.left),y:s*(d-e.top),text:b,color:\"lightgray\",borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:12,fontColor:\"black\",idealAlign:a,hovertemplate:p.hovertemplate,hovertemplateLabels:y,eventData:[{data:p._input,fullData:p,count:g,category:m,probability:v}]}}function L(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){if(n.mouse(this)[1]<-1)return;var e,r=t.parcatsViewModel.graphDiv,i=r._fullLayout,a=i._paperdiv.node().getBoundingClientRect(),l=t.parcatsViewModel.hoveron;if(\"color\"===l?(!function(t){var e=n.select(t).datum(),r=A(e);w(r),r.each((function(){s.raiseToTop(this)})),n.select(t.parentNode).selectAll(\"rect.bandrect\").filter((function(t){return t.color===e.color})).each((function(){s.raiseToTop(this),n.select(this).attr(\"stroke\",\"black\").attr(\"stroke-width\",1.5)}))}(this),S(this,\"plotly_hover\",n.event)):(!function(t){n.select(t.parentNode).selectAll(\"rect.bandrect\").each((function(t){var e=A(t);w(e),e.each((function(){s.raiseToTop(this)}))})),n.select(t.parentNode).select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",2.5)}(this),M(this,\"plotly_hover\",n.event)),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\"))\"category\"===l?e=E(r,a,this):\"color\"===l?e=function(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=r.getBoundingClientRect(),c=n.select(r).datum(),f=c.categoryViewModel,h=f.parcatsViewModel,p=h.model.dimensions[f.model.dimensionInd],d=h.trace,g=l.y+l.height/2;h.dimensions.length>1&&p.displayInd===h.dimensions.length-1?(i=l.left,a=\"left\"):(i=l.left+l.width,a=\"right\");var m=f.model.categoryLabel,v=c.parcatsViewModel.model.count,y=0;c.categoryViewModel.bands.forEach((function(t){t.color===c.color&&(y+=t.count)}));var x=f.model.count,b=0;h.pathSelection.each((function(t){t.model.color===c.color&&(b+=t.model.count)}));var _=y/v,w=y/b,T=y/x,k={countLabel:v,categoryLabel:m,probabilityLabel:_.toFixed(3)},A=[];-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&A.push([\"Count:\",k.countLabel].join(\" \")),-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&(A.push(\"P(color \\u2229 \"+m+\"): \"+k.probabilityLabel),A.push(\"P(\"+m+\" | color): \"+w.toFixed(3)),A.push(\"P(color | \"+m+\"): \"+T.toFixed(3)));var M=A.join(\"<br>\"),S=u.mostReadable(c.color,[\"black\",\"white\"]);return{trace:d,x:o*(i-e.left),y:s*(g-e.top),text:M,color:c.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontColor:S,fontSize:10,idealAlign:a,hovertemplate:d.hovertemplate,hovertemplateLabels:k,eventData:[{data:d._input,fullData:d,category:m,count:v,probability:_,categorycount:x,colorcount:b,bandcolorcount:y}]}}(r,a,this):\"dimension\"===l&&(e=function(t,e,r){var i=[];return n.select(r.parentNode.parentNode).selectAll(\"g.category\").select(\"rect.catrect\").each((function(){i.push(E(t,e,this))})),i}(r,a,this)),e&&o.loneHover(e,{container:i._hoverlayer.node(),outerContainer:i._paper.node(),gd:r})}}function C(t){var e=t.parcatsViewModel;if(!e.dragDimension&&(_(e.pathSelection),T(e.dimensionSelection.selectAll(\"g.category\")),k(e.dimensionSelection.selectAll(\"g.category\").selectAll(\"rect.bandrect\")),o.loneUnhover(e.graphDiv._fullLayout._hoverlayer.node()),e.pathSelection.sort(g),-1===e.hoverinfoItems.indexOf(\"skip\"))){\"color\"===t.parcatsViewModel.hoveron?S(this,\"plotly_unhover\",n.event):M(this,\"plotly_unhover\",n.event)}}function P(t){\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragDimensionDisplayInd=t.model.displayInd,t.initialDragDimensionDisplayInds=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),t.dragHasMoved=!1,t.dragCategoryDisplayInd=null,n.select(this).selectAll(\"g.category\").select(\"rect.catrect\").each((function(e){var r=n.mouse(this)[0],i=n.mouse(this)[1];-2<=r&&r<=e.width+2&&-2<=i&&i<=e.height+2&&(t.dragCategoryDisplayInd=e.model.displayInd,t.initialDragCategoryDisplayInds=t.model.categories.map((function(t){return t.displayInd})),e.model.dragY=e.y,s.raiseToTop(this.parentNode),n.select(this.parentNode).selectAll(\"rect.bandrect\").each((function(e){e.y<i&&i<=e.y+e.height&&(t.potentialClickBand=this)})))})),t.parcatsViewModel.dragDimension=t,o.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()))}function I(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragHasMoved=!0,null!==t.dragDimensionDisplayInd)){var e=t.dragDimensionDisplayInd,r=e-1,i=e+1,a=t.parcatsViewModel.dimensions[e];if(null!==t.dragCategoryDisplayInd){var o=a.categories[t.dragCategoryDisplayInd];o.model.dragY+=n.event.dy;var s=o.model.dragY,l=o.model.displayInd,c=a.categories,u=c[l-1],f=c[l+1];void 0!==u&&s<u.y+u.height/2&&(o.model.displayInd=u.model.displayInd,u.model.displayInd=l),void 0!==f&&s+o.height>f.y+f.height/2&&(o.model.displayInd=f.model.displayInd,f.model.displayInd=l),t.dragCategoryDisplayInd=o.model.displayInd}if(null===t.dragCategoryDisplayInd||\"freeform\"===t.parcatsViewModel.arrangement){a.model.dragX=n.event.x;var h=t.parcatsViewModel.dimensions[r],p=t.parcatsViewModel.dimensions[i];void 0!==h&&a.model.dragX<h.x+h.width&&(a.model.displayInd=h.model.displayInd,h.model.displayInd=e),void 0!==p&&a.model.dragX+a.width>p.x&&(a.model.displayInd=p.model.displayInd,p.model.displayInd=t.dragDimensionDisplayInd),t.dragDimensionDisplayInd=a.model.displayInd}j(t.parcatsViewModel),N(t.parcatsViewModel),R(t.parcatsViewModel),D(t.parcatsViewModel)}}function O(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&null!==t.dragDimensionDisplayInd){n.select(this).selectAll(\"text\").attr(\"font-weight\",\"normal\");var e={},r=z(t.parcatsViewModel),i=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),o=t.initialDragDimensionDisplayInds.some((function(t,e){return t!==i[e]}));o&&i.forEach((function(r,n){var i=t.parcatsViewModel.model.dimensions[n].containerInd;e[\"dimensions[\"+i+\"].displayindex\"]=r}));var s=!1;if(null!==t.dragCategoryDisplayInd){var l=t.model.categories.map((function(t){return t.displayInd}));if(s=t.initialDragCategoryDisplayInds.some((function(t,e){return t!==l[e]}))){var c=t.model.categories.slice().sort((function(t,e){return t.displayInd-e.displayInd})),u=c.map((function(t){return t.categoryValue})),f=c.map((function(t){return t.categoryLabel}));e[\"dimensions[\"+t.model.containerInd+\"].categoryarray\"]=[u],e[\"dimensions[\"+t.model.containerInd+\"].ticktext\"]=[f],e[\"dimensions[\"+t.model.containerInd+\"].categoryorder\"]=\"array\"}}if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")&&!t.dragHasMoved&&t.potentialClickBand&&(\"color\"===t.parcatsViewModel.hoveron?S(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent):M(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent)),t.model.dragX=null,null!==t.dragCategoryDisplayInd)t.parcatsViewModel.dimensions[t.dragDimensionDisplayInd].categories[t.dragCategoryDisplayInd].model.dragY=null,t.dragCategoryDisplayInd=null;t.dragDimensionDisplayInd=null,t.parcatsViewModel.dragDimension=null,t.dragHasMoved=null,t.potentialClickBand=null,j(t.parcatsViewModel),N(t.parcatsViewModel),n.transition().duration(300).ease(\"cubic-in-out\").each((function(){R(t.parcatsViewModel,!0),D(t.parcatsViewModel,!0)})).each(\"end\",(function(){(o||s)&&a.restyle(t.parcatsViewModel.graphDiv,e,[r])}))}}function z(t){for(var e,r=t.graphDiv._fullData,n=0;n<r.length;n++)if(t.key===r[n].uid){e=n;break}return e}function D(t,e){var r;void 0===e&&(e=!1),t.pathSelection.data((function(t){return t.paths}),p),(r=t.pathSelection,e?r.transition():r).attr(\"d\",(function(t){return t.svgD}))}function R(t,e){function r(t){return e?t.transition():t}void 0===e&&(e=!1),t.dimensionSelection.data((function(t){return t.dimensions}),p);var i=t.dimensionSelection.selectAll(\"g.category\").data((function(t){return t.categories}),p);r(t.dimensionSelection).attr(\"transform\",(function(t){return l(t.x,0)})),r(i).attr(\"transform\",(function(t){return l(0,t.y)})),i.select(\".dimlabel\").text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})),i.select(\".catlabel\").attr(\"text-anchor\",(function(t){return d(t)?\"start\":\"end\"})).attr(\"x\",(function(t){return d(t)?t.width+5:-5})).each((function(t){var e,r;d(t)?(e=t.width+5,r=\"start\"):(e=-5,r=\"end\"),n.select(this).selectAll(\"tspan\").attr(\"x\",e).attr(\"text-anchor\",r)}));var a=i.selectAll(\"rect.bandrect\").data((function(t){return t.bands}),p),o=a.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"cursor\",\"move\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);a.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})),k(o),a.each((function(){s.raiseToTop(this)})),a.exit().remove()}function F(t,e,r){var n,i=r[0],a=e.margin||{l:80,r:80,t:100,b:80},o=i.trace,s=o.domain,l=e.width,c=e.height,u=Math.floor(l*(s.x[1]-s.x[0])),f=Math.floor(c*(s.y[1]-s.y[0])),h=s.x[0]*l+a.l,p=e.height-s.y[1]*e.height+a.t,d=o.line.shape;n=\"all\"===o.hoverinfo?[\"count\",\"probability\"]:(o.hoverinfo||\"\").split(\"+\");var g={trace:o,key:o.uid,model:i,x:h,y:p,width:u,height:f,hoveron:o.hoveron,hoverinfoItems:n,arrangement:o.arrangement,bundlecolors:o.bundlecolors,sortpaths:o.sortpaths,labelfont:o.labelfont,categorylabelfont:o.tickfont,pathShape:d,dragDimension:null,margin:a,paths:[],dimensions:[],graphDiv:t,traceSelection:null,pathSelection:null,dimensionSelection:null};return i.dimensions&&(j(g),N(g)),g}function B(t,e,r,n,a){var o,s,l=[],c=[];for(s=0;s<r.length-1;s++)o=i(r[s]+t[s],t[s+1]),l.push(o(a)),c.push(o(1-a));var u=\"M \"+t[0]+\",\"+e[0];for(u+=\"l\"+r[0]+\",0 \",s=1;s<r.length;s++)u+=\"C\"+l[s-1]+\",\"+e[s-1]+\" \"+c[s-1]+\",\"+e[s]+\" \"+t[s]+\",\"+e[s],u+=\"l\"+r[s]+\",0 \";for(u+=\"l0,\"+n+\" \",u+=\"l -\"+r[r.length-1]+\",0 \",s=r.length-2;s>=0;s--)u+=\"C\"+c[s]+\",\"+(e[s+1]+n)+\" \"+l[s]+\",\"+(e[s]+n)+\" \"+(t[s]+r[s])+\",\"+(e[s]+n),u+=\"l-\"+r[s]+\",0 \";return u+=\"Z\"}function N(t){var e=t.dimensions,r=t.model,n=e.map((function(t){return t.categories.map((function(t){return t.y}))})),i=t.model.dimensions.map((function(t){return t.categories.map((function(t){return t.displayInd}))})),a=t.model.dimensions.map((function(t){return t.displayInd})),o=t.dimensions.map((function(t){return t.model.dimensionInd})),s=e.map((function(t){return t.x})),l=e.map((function(t){return t.width})),c=[];for(var u in r.paths)r.paths.hasOwnProperty(u)&&c.push(r.paths[u]);function f(t){var e=t.categoryInds.map((function(t,e){return i[e][t]}));return o.map((function(t){return e[t]}))}c.sort((function(e,r){var n=f(e),i=f(r);return\"backward\"===t.sortpaths&&(n.reverse(),i.reverse()),n.push(e.valueInds[0]),i.push(r.valueInds[0]),t.bundlecolors&&(n.unshift(e.rawColor),i.unshift(r.rawColor)),n<i?-1:n>i?1:0}));for(var h=new Array(c.length),p=e[0].model.count,d=e[0].categories.map((function(t){return t.height})).reduce((function(t,e){return t+e})),g=0;g<c.length;g++){var m,v=c[g];m=p>0?d*(v.count/p):0;for(var y,x=new Array(n.length),b=0;b<v.categoryInds.length;b++){var _=v.categoryInds[b],w=i[b][_],T=a[b];x[T]=n[T][w],n[T][w]+=m;var k=t.dimensions[T].categories[w],A=k.bands.length,M=k.bands[A-1];if(void 0===M||v.rawColor!==M.rawColor){var S=void 0===M?0:M.y+M.height;k.bands.push({key:S,color:v.color,rawColor:v.rawColor,height:m,width:k.width,count:v.count,y:S,categoryViewModel:k,parcatsViewModel:t})}else{var E=k.bands[A-1];E.height+=m,E.count+=v.count}}y=\"hspline\"===t.pathShape?B(s,x,l,m,.5):B(s,x,l,m,0),h[g]={key:v.valueInds[0],model:v,height:m,leftXs:s,topYs:x,dimWidths:l,svgD:y,parcatsViewModel:t}}t.paths=h}function j(t){var e=t.model.dimensions.map((function(t){return{displayInd:t.displayInd,dimensionInd:t.dimensionInd}}));e.sort((function(t,e){return t.displayInd-e.displayInd}));var r=[];for(var n in e){var i=e[n].dimensionInd,a=t.model.dimensions[i];r.push(U(t,a))}t.dimensions=r}function U(t,e){var r,n=t.model.dimensions.length,i=e.displayInd;r=40+(n>1?(t.width-80-16)/(n-1):0)*i;var a,o,s,l,c,u=[],f=t.model.maxCats,h=e.categories.length,p=e.count,d=t.height-8*(f-1),g=8*(f-h)/2,m=e.categories.map((function(t){return{displayInd:t.displayInd,categoryInd:t.categoryInd}}));for(m.sort((function(t,e){return t.displayInd-e.displayInd})),c=0;c<h;c++)l=m[c].categoryInd,o=e.categories[l],a=p>0?o.count/p*d:0,s={key:o.valueInds[0],model:o,width:16,height:a,y:null!==o.dragY?o.dragY:g,bands:[],parcatsViewModel:t},g=g+a+8,u.push(s);return{key:e.dimensionInd,x:null!==e.dragX?e.dragX:r,y:0,width:16,model:e,categories:u,parcatsViewModel:t,dragCategoryDisplayInd:null,dragDimensionDisplayInd:null,initialDragDimensionDisplayInds:null,initialDragCategoryDisplayInds:null,dragHasMoved:null,potentialClickBand:null}}e.exports=function(t,e,r,n){h(r,t,n,e)}},{\"../../components/drawing\":688,\"../../components/fx\":706,\"../../lib\":803,\"../../lib/svg_text_utils\":829,\"../../plot_api/plot_api\":840,\"@plotly/d3\":58,\"d3-interpolate\":171,tinycolor2:598}],1179:[function(t,e,r){\"use 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n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/layout_attributes\"),a=t(\"../../plots/font_attributes\"),o=t(\"../../plots/domain\").attributes,s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/plot_template\").templatedArray;e.exports={domain:o({name:\"parcoords\",trace:!0,editType:\"plot\"}),labelangle:{valType:\"angle\",dflt:0,editType:\"plot\"},labelside:{valType:\"enumerated\",values:[\"top\",\"bottom\"],dflt:\"top\",editType:\"plot\"},labelfont:a({editType:\"plot\"}),tickfont:a({editType:\"plot\"}),rangefont:a({editType:\"plot\"}),dimensions:l(\"dimension\",{label:{valType:\"string\",editType:\"plot\"},tickvals:s({},i.tickvals,{editType:\"plot\"}),ticktext:s({},i.ticktext,{editType:\"plot\"}),tickformat:s({},i.tickformat,{editType:\"plot\"}),visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},range:{valType:\"info_array\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},constraintrange:{valType:\"info_array\",freeLength:!0,dimensions:\"1-2\",items:[{valType:\"any\",editType:\"plot\"},{valType:\"any\",editType:\"plot\"}],editType:\"plot\"},multiselect:{valType:\"boolean\",dflt:!0,editType:\"plot\"},values:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"}),line:s({editType:\"calc\"},n(\"line\",{colorscaleDflt:\"Viridis\",autoColorDflt:!1,editTypeOverride:\"calc\"}))}},{\"../../components/colorscale/attributes\":673,\"../../lib/extend\":793,\"../../plot_api/plot_template\":843,\"../../plots/cartesian/layout_attributes\":869,\"../../plots/domain\":882,\"../../plots/font_attributes\":883}],1181:[function(t,e,r){\"use 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r=e.brush,n=r.filter,a=r.svgBrush;a._dragging||(T(t,e),w(t,e),e.brush.svgBrush.wasDragged=!1),a._dragging=!1,i.event.sourceEvent.stopPropagation();var o=a.grabbingBar;if(a.grabbingBar=!1,a.grabLocation=void 0,e.parent.inBrushDrag=!1,y(),!a.wasDragged)return a.wasDragged=void 0,a.clickableOrdinalRange?r.filterSpecified&&e.multiselect?a.extent.push(a.clickableOrdinalRange):(a.extent=[a.clickableOrdinalRange],r.filterSpecified=!0):o?(a.extent=a.stayingIntervals,0===a.extent.length&&M(r)):M(r),a.brushCallback(e),b(t.parentNode),void a.brushEndCallback(r.filterSpecified?n.getConsolidated():[]);var s=function(){n.set(n.getConsolidated())};if(e.ordinal){var l=e.unitTickvals;l[l.length-1]<l[0]&&l.reverse(),a.newExtent=[p(0,l,a.newExtent[0],a.stayingIntervals),p(1,l,a.newExtent[1],a.stayingIntervals)];var c=a.newExtent[1]>a.newExtent[0];a.extent=a.stayingIntervals.concat(c?[a.newExtent]:[]),a.extent.length||M(r),a.brushCallback(e),c?b(t.parentNode,s):(s(),b(t.parentNode))}else 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t.slice()}))}(e).slice();e.filter.set(r),o()}),brushEndCallback:a}}},ensureAxisBrush:function(t,e){var r=t.selectAll(\".\"+n.cn.axisBrush).data(o,a);r.enter().append(\"g\").classed(n.cn.axisBrush,!0),function(t,e){var r=t.selectAll(\".background\").data(o);r.enter().append(\"rect\").classed(\"background\",!0).call(d).call(g).style(\"pointer-events\",\"auto\").attr(\"transform\",l(0,n.verticalPadding)),r.call(k).attr(\"height\",(function(t){return t.height-n.verticalPadding}));var i=t.selectAll(\".highlight-shadow\").data(o);i.enter().append(\"line\").classed(\"highlight-shadow\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width+n.bar.strokeWidth).attr(\"stroke\",e).attr(\"opacity\",n.bar.strokeOpacity).attr(\"stroke-linecap\",\"butt\"),i.attr(\"y1\",(function(t){return t.height})).call(x);var a=t.selectAll(\".highlight\").data(o);a.enter().append(\"line\").classed(\"highlight\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width-n.bar.strokeWidth).attr(\"stroke\",n.bar.fillColor).attr(\"opacity\",n.bar.fillOpacity).attr(\"stroke-linecap\",\"butt\"),a.attr(\"y1\",(function(t){return t.height})).call(x)}(r,e)},cleanRanges:function(t,e){if(Array.isArray(t[0])?(t=t.map((function(t){return t.sort(s)})),t=e.multiselect?S(t.sort(A)):[t[0]]):t=[t.sort(s)],e.tickvals){var r=e.tickvals.slice().sort(s);if(!(t=t.map((function(t){var e=[p(0,r,t[0],[]),p(1,r,t[1],[])];if(e[1]>e[0])return e})).filter((function(t){return t}))).length)return}return t.length>1?t:t[0]}}},{\"../../lib\":803,\"../../lib/gup\":800,\"./constants\":1184,\"@plotly/d3\":58}],1182:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../plots/get_data\").getModuleCalcData,a=t(\"./plot\"),o=t(\"../../constants/xmlns_namespaces\");r.name=\"parcoords\",r.plot=function(t){var e=i(t.calcdata,\"parcoords\")[0];e.length&&a(t,e)},r.clean=function(t,e,r,n){var i=n._has&&n._has(\"parcoords\"),a=e._has&&e._has(\"parcoords\");i&&!a&&(n._paperdiv.selectAll(\".parcoords\").remove(),n._glimages.selectAll(\"*\").remove())},r.toSVG=function(t){var e=t._fullLayout._glimages,r=n.select(t).selectAll(\".svg-container\");r.filter((function(t,e){return e===r.size()-1})).selectAll(\".gl-canvas-context, .gl-canvas-focus\").each((function(){var t=this.toDataURL(\"image/png\");e.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":t,preserveAspectRatio:\"none\",x:0,y:0,width:this.style.width,height:this.style.height})})),window.setTimeout((function(){n.selectAll(\"#filterBarPattern\").attr(\"id\",\"filterBarPattern\")}),60)}},{\"../../constants/xmlns_namespaces\":780,\"../../plots/get_data\":891,\"./plot\":1191,\"@plotly/d3\":58}],1183:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isArrayOrTypedArray,i=t(\"../../components/colorscale\"),a=t(\"../../lib/gup\").wrap;e.exports=function(t,e){var r,o;return i.hasColorscale(e,\"line\")&&n(e.line.color)?(r=e.line.color,o=i.extractOpts(e.line).colorscale,i.calc(t,e,{vals:r,containerStr:\"line\",cLetter:\"c\"})):(r=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=.5;return e}(e._length),o=[[0,e.line.color],[1,e.line.color]]),a({lineColor:r,cscale:o})}},{\"../../components/colorscale\":678,\"../../lib\":803,\"../../lib/gup\":800}],1184:[function(t,e,r){\"use 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n=t(\"../../lib\").isTypedArray;r.convertTypedArray=function(t){return n(t)?Array.prototype.slice.call(t):t},r.isOrdinal=function(t){return!!t.tickvals},r.isVisible=function(t){return t.visible||!(\"visible\"in t)}},{\"../../lib\":803}],1187:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcoords\",basePlotModule:t(\"./base_plot\"),categories:[\"gl\",\"regl\",\"noOpacity\",\"noHover\"],meta:{}}},{\"./attributes\":1180,\"./base_plot\":1182,\"./calc\":1183,\"./defaults\":1185,\"./plot\":1191}],1188:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nattribute vec4 p01_04, p05_08, p09_12, p13_16,\\n               p17_20, p21_24, p25_28, p29_32,\\n               p33_36, p37_40, p41_44, p45_48,\\n               p49_52, p53_56, p57_60, colors;\\n\\nuniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,\\n             loA, hiA, loB, hiB, loC, hiC, loD, hiD;\\n\\nuniform vec2 resolution, viewBoxPos, viewBoxSize;\\nuniform float maskHeight;\\nuniform float drwLayer; // 0: context, 1: focus, 2: pick\\nuniform vec4 contextColor;\\nuniform sampler2D maskTexture, palette;\\n\\nbool isPick    = (drwLayer > 1.5);\\nbool isContext = (drwLayer < 0.5);\\n\\nconst vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);\\nconst vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);\\n\\nfloat val(mat4 p, mat4 v) {\\n    return dot(matrixCompMult(p, v) * UNITS, UNITS);\\n}\\n\\nfloat axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {\\n    float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);\\n    float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);\\n    return y1 * (1.0 - ratio) + y2 * ratio;\\n}\\n\\nint iMod(int a, int b) {\\n    return a - b * (a / b);\\n}\\n\\nbool fOutside(float p, float lo, float hi) {\\n    return (lo < hi) && (lo > p || p > hi);\\n}\\n\\nbool vOutside(vec4 p, vec4 lo, vec4 hi) {\\n    return (\\n        fOutside(p[0], lo[0], hi[0]) ||\\n        fOutside(p[1], lo[1], hi[1]) ||\\n        fOutside(p[2], lo[2], hi[2]) ||\\n        fOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool mOutside(mat4 p, mat4 lo, mat4 hi) {\\n    return (\\n        vOutside(p[0], lo[0], hi[0]) ||\\n        vOutside(p[1], lo[1], hi[1]) ||\\n        vOutside(p[2], lo[2], hi[2]) ||\\n        vOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    return mOutside(A, loA, hiA) ||\\n           mOutside(B, loB, hiB) ||\\n           mOutside(C, loC, hiC) ||\\n           mOutside(D, loD, hiD);\\n}\\n\\nbool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    mat4 pnts[4];\\n    pnts[0] = A;\\n    pnts[1] = B;\\n    pnts[2] = C;\\n    pnts[3] = D;\\n\\n    for(int i = 0; i < 4; ++i) {\\n        for(int j = 0; j < 4; ++j) {\\n            for(int k = 0; k < 4; ++k) {\\n                if(0 == iMod(\\n                    int(255.0 * texture2D(maskTexture,\\n                        vec2(\\n                            (float(i * 2 + j / 2) + 0.5) / 8.0,\\n                            (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight\\n                        ))[3]\\n                    ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),\\n                    2\\n                )) return true;\\n            }\\n        }\\n    }\\n    return false;\\n}\\n\\nvec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {\\n    float x = 0.5 * sign(v) + 0.5;\\n    float y = axisY(x, A, B, C, D);\\n    float z = 1.0 - abs(v);\\n\\n    z += isContext ? 0.0 : 2.0 * float(\\n        outsideBoundingBox(A, B, C, D) ||\\n        outsideRasterMask(A, B, C, D)\\n    );\\n\\n    return vec4(\\n        2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\\n        z,\\n        1.0\\n    );\\n}\\n\\nvoid main() {\\n    mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\\n    mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\\n    mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\\n    mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\\n\\n    float v = colors[3];\\n\\n    gl_Position = position(isContext, v, A, B, C, D);\\n\\n    fragColor =\\n        isContext ? vec4(contextColor) :\\n        isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\\n}\\n\"]),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n    gl_FragColor = fragColor;\\n}\\n\"]),o=t(\"./constants\").maxDimensionCount,s=t(\"../../lib\"),l=new Uint8Array(4),c=new Uint8Array(4),u={shape:[256,1],format:\"rgba\",type:\"uint8\",mag:\"nearest\",min:\"nearest\"};function f(t,e,r,n,i){var a=t._gl;a.enable(a.SCISSOR_TEST),a.scissor(e,r,n,i),t.clear({color:[0,0,0,0],depth:1})}function h(t,e,r,n,i,a){var o=a.key;r.drawCompleted||(!function(t){t.read({x:0,y:0,width:1,height:1,data:l})}(t),r.drawCompleted=!0),function s(l){var c=Math.min(n,i-l*n);0===l&&(window.cancelAnimationFrame(r.currentRafs[o]),delete r.currentRafs[o],f(t,a.scissorX,a.scissorY,a.scissorWidth,a.viewBoxSize[1])),r.clearOnly||(a.count=2*c,a.offset=2*l*n,e(a),l*n+c<i&&(r.currentRafs[o]=window.requestAnimationFrame((function(){s(l+1)}))),r.drawCompleted=!1)}(0)}function p(t,e){for(var r=new Array(256),n=0;n<256;n++)r[n]=t(n/255).concat(e);return r}function d(t,e){return(t>>>8*e)%256/255}function g(t,e,r){for(var n=new Array(8*e),i=0,a=0;a<e;a++)for(var o=0;o<2;o++)for(var s=0;s<4;s++){var l=4*t+s,c=r[64*a+l];63===l&&0===o&&(c*=-1),n[i++]=c}return n}function m(t){var e=\"0\"+t;return e.substr(e.length-2)}function v(t){return t<o?\"p\"+m(t+1)+\"_\"+m(t+4):\"colors\"}function y(t,e,r,n,i,a,o,l,c,u,f,h,p,d){for(var g=[[],[]],m=0;m<64;m++)g[0][m]=m===i?1:0,g[1][m]=m===a?1:0;o*=d,l*=d,c*=d,u*=d;var v=t.lines.canvasOverdrag*d,y=t.domain,x=t.canvasWidth*d,b=t.canvasHeight*d,_=t.pad.l*d,w=t.pad.b*d,T=t.layoutHeight*d,k=t.layoutWidth*d,A=t.deselectedLines.color;return s.extendFlat({key:f,resolution:[x,b],viewBoxPos:[o+v,l],viewBoxSize:[c,u],i0:i,i1:a,dim0A:g[0].slice(0,16),dim0B:g[0].slice(16,32),dim0C:g[0].slice(32,48),dim0D:g[0].slice(48,64),dim1A:g[1].slice(0,16),dim1B:g[1].slice(16,32),dim1C:g[1].slice(32,48),dim1D:g[1].slice(48,64),drwLayer:h,contextColor:[A[0]/255,A[1]/255,A[2]/255,A[3]<1?A[3]:Math.max(1/255,Math.pow(1/t.lines.color.length,1/3))],scissorX:(n===e?0:o+v)+(_-v)+k*y.x[0],scissorWidth:(n===r?x-o+v:c+.5)+(n===e?o+v:0),scissorY:l+w+T*y.y[0],scissorHeight:u,viewportX:_-v+k*y.x[0],viewportY:w+T*y.y[0],viewportWidth:x,viewportHeight:b},p)}function x(t){var e=Math.max(0,Math.floor(2047*t[0]),0),r=Math.min(2047,Math.ceil(2047*t[1]),2047);return[Math.min(e,r),Math.max(e,r)]}e.exports=function(t,e){var r,n,l,m,b,_=e.context,w=e.pick,T=e.regl,k=T._gl,A=k.getParameter(k.ALIASED_LINE_WIDTH_RANGE),M=Math.max(A[0],Math.min(A[1],e.viewModel.plotGlPixelRatio)),S={currentRafs:{},drawCompleted:!0,clearOnly:!1},E=function(t){for(var e={},r=0;r<=o;r+=4)e[v(r)]=t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)});return e}(T),L=T.texture(u),C=[];I(e);var P=T({profile:!1,blend:{enable:_,func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:1,dstAlpha:1},equation:{rgb:\"add\",alpha:\"add\"},color:[0,0,0,0]},depth:{enable:!_,mask:!0,func:\"less\",range:[0,1]},cull:{enable:!0,face:\"back\"},scissor:{enable:!0,box:{x:T.prop(\"scissorX\"),y:T.prop(\"scissorY\"),width:T.prop(\"scissorWidth\"),height:T.prop(\"scissorHeight\")}},viewport:{x:T.prop(\"viewportX\"),y:T.prop(\"viewportY\"),width:T.prop(\"viewportWidth\"),height:T.prop(\"viewportHeight\")},dither:!1,vert:i,frag:a,primitive:\"lines\",lineWidth:M,attributes:E,uniforms:{resolution:T.prop(\"resolution\"),viewBoxPos:T.prop(\"viewBoxPos\"),viewBoxSize:T.prop(\"viewBoxSize\"),dim0A:T.prop(\"dim0A\"),dim1A:T.prop(\"dim1A\"),dim0B:T.prop(\"dim0B\"),dim1B:T.prop(\"dim1B\"),dim0C:T.prop(\"dim0C\"),dim1C:T.prop(\"dim1C\"),dim0D:T.prop(\"dim0D\"),dim1D:T.prop(\"dim1D\"),loA:T.prop(\"loA\"),hiA:T.prop(\"hiA\"),loB:T.prop(\"loB\"),hiB:T.prop(\"hiB\"),loC:T.prop(\"loC\"),hiC:T.prop(\"hiC\"),loD:T.prop(\"loD\"),hiD:T.prop(\"hiD\"),palette:L,contextColor:T.prop(\"contextColor\"),maskTexture:T.prop(\"maskTexture\"),drwLayer:T.prop(\"drwLayer\"),maskHeight:T.prop(\"maskHeight\")},offset:T.prop(\"offset\"),count:T.prop(\"count\")});function I(t){r=t.model,n=t.viewModel,l=n.dimensions.slice(),m=l[0]?l[0].values.length:0;var e=r.lines,i=w?e.color.map((function(t,r){return r/e.color.length})):e.color,a=function(t,e,r){for(var n,i=new Array(t*(o+4)),a=0,s=0;s<t;s++){for(var l=0;l<o;l++)i[a++]=l<e.length?e[l].paddedUnitValues[s]:.5;i[a++]=d(s,2),i[a++]=d(s,1),i[a++]=d(s,0),i[a++]=(n=r[s],Math.max(1e-6,Math.min(.999999,n)))}return i}(m,l,i);!function(t,e,r){for(var n=0;n<=o;n+=4)t[v(n)](g(n/4,e,r))}(E,m,a),_||w||(L=T.texture(s.extendFlat({data:p(r.unitToColor,255)},u)))}return{render:function(t,e,n){var i,a,o,s=t.length,c=1/0,u=-1/0;for(i=0;i<s;i++)t[i].dim0.canvasX<c&&(c=t[i].dim0.canvasX,a=i),t[i].dim1.canvasX>u&&(u=t[i].dim1.canvasX,o=i);0===s&&f(T,0,0,r.canvasWidth,r.canvasHeight);var p=function(t){var e,r,n,i=[[],[]];for(n=0;n<64;n++){var a=!t&&n<l.length?l[n].brush.filter.getBounds():[-1/0,1/0];i[0][n]=a[0],i[1][n]=a[1]}var o=new Array(16384);for(e=0;e<16384;e++)o[e]=255;if(!t)for(e=0;e<l.length;e++){var s=e%8,c=(e-s)/8,u=Math.pow(2,s),f=l[e].brush.filter.get();if(!(f.length<2)){var h=x(f[0])[1];for(r=1;r<f.length;r++){var p=x(f[r]);for(n=h+1;n<p[0];n++)o[8*n+c]&=~u;h=Math.max(h,p[1])}}}var d={shape:[8,2048],format:\"alpha\",type:\"uint8\",mag:\"nearest\",min:\"nearest\",data:o};return b?b(d):b=T.texture(d),{maskTexture:b,maskHeight:2048,loA:i[0].slice(0,16),loB:i[0].slice(16,32),loC:i[0].slice(32,48),loD:i[0].slice(48,64),hiA:i[1].slice(0,16),hiB:i[1].slice(16,32),hiC:i[1].slice(32,48),hiD:i[1].slice(48,64)}}(_);for(i=0;i<s;i++){var d=t[i],g=d.dim0.crossfilterDimensionIndex,v=d.dim1.crossfilterDimensionIndex,k=d.canvasX,A=d.canvasY,M=k+d.panelSizeX,E=d.plotGlPixelRatio;if(e||!C[g]||C[g][0]!==k||C[g][1]!==M){C[g]=[k,M];var L=y(r,a,o,i,g,v,k,A,d.panelSizeX,d.panelSizeY,d.dim0.crossfilterDimensionIndex,_?0:w?2:1,p,E);S.clearOnly=n;var I=e?r.lines.blockLineCount:m;h(T,P,S,I,m,L)}}},readPixel:function(t,e){return T.read({x:t,y:e,width:1,height:1,data:c}),c},readPixels:function(t,e,r,n){var i=new Uint8Array(4*r*n);return T.read({x:t,y:e,width:r,height:n,data:i}),i},destroy:function(){for(var e in t.style[\"pointer-events\"]=\"none\",L.destroy(),b&&b.destroy(),E)E[e].destroy()},update:I}}},{\"../../lib\":803,\"./constants\":1184,glslify:442}],1189:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){var i,a;for(n||(n=1/0),i=0;i<e.length;i++)(a=e[i]).visible&&(n=Math.min(n,a[r].length));for(n===1/0&&(n=0),t._length=n,i=0;i<e.length;i++)(a=e[i]).visible&&(a._length=n);return n}},{}],1190:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../lib\"),a=i.numberFormat,o=t(\"color-rgba\"),s=t(\"../../plots/cartesian/axes\"),l=i.strRotate,c=i.strTranslate,u=t(\"../../lib/svg_text_utils\"),f=t(\"../../components/drawing\"),h=t(\"../../components/colorscale\"),p=t(\"../../lib/gup\"),d=p.keyFun,g=p.repeat,m=p.unwrap,v=t(\"./helpers\"),y=t(\"./constants\"),x=t(\"./axisbrush\"),b=t(\"./lines\");function _(t,e,r){return i.aggNums(t,null,e,r)}function w(t,e){return k(_(Math.min,t,e),_(Math.max,t,e))}function T(t){var e=t.range;return e?k(e[0],e[1]):w(t.values,t._length)}function k(t,e){return!isNaN(t)&&isFinite(t)||(t=0),!isNaN(e)&&isFinite(e)||(e=0),t===e&&(0===t?(t-=1,e+=1):(t*=.9,e*=1.1)),[t,e]}function A(t,e,r,i,o){var s,l,c=T(r);return i?n.scale.ordinal().domain(i.map((s=a(r.tickformat),l=o,l?function(t,e){var r=l[e];return null==r?s(t):r}:s))).range(i.map((function(r){var n=(r-c[0])/(c[1]-c[0]);return t-e+n*(2*e-t)}))):n.scale.linear().domain(c).range([t-e,e])}function M(t){if(t.tickvals){var e=T(t);return n.scale.ordinal().domain(t.tickvals).range(t.tickvals.map((function(t){return(t-e[0])/(e[1]-e[0])})))}}function S(t){var e=t.map((function(t){return t[0]})),r=t.map((function(t){var e=o(t[1]);return n.rgb(\"rgb(\"+e[0]+\",\"+e[1]+\",\"+e[2]+\")\")})),i=\"rgb\".split(\"\").map((function(t){return n.scale.linear().clamp(!0).domain(e).range(r.map((i=t,function(t){return t[i]})));var i}));return function(t){return i.map((function(e){return e(t)}))}}function E(t){return t.dimensions.some((function(t){return t.brush.filterSpecified}))}function L(t,e,r){var a=m(e),s=a.trace,l=v.convertTypedArray(a.lineColor),c=s.line,u={color:o(y.deselectedLineColor)},f=h.extractOpts(c),p=f.reversescale?h.flipScale(a.cscale):a.cscale,d=s.domain,g=s.dimensions,x=t.width,b=s.labelangle,_=s.labelside,w=s.labelfont,k=s.tickfont,A=s.rangefont,M=i.extendDeepNoArrays({},c,{color:l.map(n.scale.linear().domain(T({values:l,range:[f.min,f.max],_length:s._length}))),blockLineCount:y.blockLineCount,canvasOverdrag:y.overdrag*y.canvasPixelRatio}),E=Math.floor(x*(d.x[1]-d.x[0])),L=Math.floor(t.height*(d.y[1]-d.y[0])),C=t.margin||{l:80,r:80,t:100,b:80},P=E,I=L;return{key:r,colCount:g.filter(v.isVisible).length,dimensions:g,tickDistance:y.tickDistance,unitToColor:S(p),lines:M,deselectedLines:u,labelAngle:b,labelSide:_,labelFont:w,tickFont:k,rangeFont:A,layoutWidth:x,layoutHeight:t.height,domain:d,translateX:d.x[0]*x,translateY:t.height-d.y[1]*t.height,pad:C,canvasWidth:P*y.canvasPixelRatio+2*M.canvasOverdrag,canvasHeight:I*y.canvasPixelRatio,width:P,height:I,canvasPixelRatio:y.canvasPixelRatio}}function C(t,e,r){var o=r.width,s=r.height,l=r.dimensions,c=r.canvasPixelRatio,u=function(t){return o*t/Math.max(1,r.colCount-1)},f=y.verticalPadding/s,h=function(t,e){return n.scale.linear().range([e,t-e])}(s,y.verticalPadding),p={key:r.key,xScale:u,model:r,inBrushDrag:!1},d={};return p.dimensions=l.filter(v.isVisible).map((function(o,l){var g=function(t,e){return n.scale.linear().domain(T(t)).range([e,1-e])}(o,f),m=d[o.label];d[o.label]=(m||0)+1;var b=o.label+(m?\"__\"+m:\"\"),_=o.constraintrange,w=_&&_.length;w&&!Array.isArray(_[0])&&(_=[_]);var k=w?_.map((function(t){return t.map(g)})):[[-1/0,1/0]],S=o.values;S.length>o._length&&(S=S.slice(0,o._length));var L,C=o.tickvals;function P(t,e){return{val:t,text:L[e]}}function I(t,e){return t.val-e.val}if(Array.isArray(C)&&C.length){L=o.ticktext,Array.isArray(L)&&L.length?L.length>C.length?L=L.slice(0,C.length):C.length>L.length&&(C=C.slice(0,L.length)):L=C.map(a(o.tickformat));for(var O=1;O<C.length;O++)if(C[O]<C[O-1]){for(var z=C.map(P).sort(I),D=0;D<C.length;D++)C[D]=z[D].val,L[D]=z[D].text;break}}else C=void 0;return S=v.convertTypedArray(S),{key:b,label:o.label,tickFormat:o.tickformat,tickvals:C,ticktext:L,ordinal:v.isOrdinal(o),multiselect:o.multiselect,xIndex:l,crossfilterDimensionIndex:l,visibleIndex:o._index,height:s,values:S,paddedUnitValues:S.map(g),unitTickvals:C&&C.map(g),xScale:u,x:u(l),canvasX:u(l)*c,unitToPaddedPx:h,domainScale:A(s,y.verticalPadding,o,C,L),ordinalScale:M(o),parent:p,model:r,brush:x.makeBrush(t,w,k,(function(){t.linePickActive(!1)}),(function(){var e=p;e.focusLayer&&e.focusLayer.render(e.panels,!0);var r=E(e);!t.contextShown()&&r?(e.contextLayer&&e.contextLayer.render(e.panels,!0),t.contextShown(!0)):t.contextShown()&&!r&&(e.contextLayer&&e.contextLayer.render(e.panels,!0,!0),t.contextShown(!1))}),(function(r){if(p.focusLayer.render(p.panels,!0),p.pickLayer&&p.pickLayer.render(p.panels,!0),t.linePickActive(!0),e&&e.filterChanged){var n=g.invert,a=r.map((function(t){return t.map(n).sort(i.sorterAsc)})).sort((function(t,e){return t[0]-e[0]}));e.filterChanged(p.key,o._index,a)}}))}})),p}function P(t){t.classed(y.cn.axisExtentText,!0).attr(\"text-anchor\",\"middle\").style(\"cursor\",\"default\")}function I(t,e){var r=\"top\"===e?1:-1,n=t*Math.PI/180;return{dir:r,dx:Math.sin(n),dy:Math.cos(n),degrees:t}}function O(t,e,r){for(var n=e.panels||(e.panels=[]),i=t.data(),a=0;a<i.length-1;a++){var o=n[a]||(n[a]={}),s=i[a],l=i[a+1];o.dim0=s,o.dim1=l,o.canvasX=s.canvasX,o.panelSizeX=l.canvasX-s.canvasX,o.panelSizeY=e.model.canvasHeight,o.y=0,o.canvasY=0,o.plotGlPixelRatio=r}}function z(t,e){return s.tickText(t._ax,e,!1).text}function D(t,e){if(t.ordinal)return\"\";var r=t.domainScale.domain(),n=r[e?r.length-1:0];return z(t.model.dimensions[t.visibleIndex],n)}e.exports=function(t,e,r,a){var o=t._fullLayout,h=o._toppaper,p=o._glcontainer,_=t._context.plotGlPixelRatio,T=t._fullLayout.paper_bgcolor;!function(t){for(var e=0;e<t.length;e++)for(var 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n=t(\"../../plots/attributes\"),i=t(\"../../plots/domain\").attributes,a=t(\"../../plots/font_attributes\"),o=t(\"../../components/color/attributes\"),s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../plots/template_attributes\").texttemplateAttrs,c=t(\"../../lib/extend\").extendFlat,u=a({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});e.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:o.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:c({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:s({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),texttemplate:l({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:c({},u,{}),insidetextorientation:{valType:\"enumerated\",values:[\"horizontal\",\"radial\",\"tangential\",\"auto\"],dflt:\"auto\",editType:\"plot\"},insidetextfont:c({},u,{}),outsidetextfont:c({},u,{}),automargin:{valType:\"boolean\",dflt:!1,editType:\"plot\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:c({},u,{}),position:{valType:\"enumerated\",values:[\"top 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r,i,a=[],o=t._fullLayout,l=o.hiddenlabels||[],c=e.labels,u=e.marker.colors||[],f=e.values,h=e._length,p=e._hasValues&&h;if(e.dlabel)for(c=new Array(h),r=0;r<h;r++)c[r]=String(e.label0+r*e.dlabel);var d={},g=s(o[\"_\"+e.type+\"colormap\"]),m=0,v=!1;for(r=0;r<h;r++){var y,x,b;if(p){if(y=f[r],!n(y))continue;if((y=+y)<0)continue}else y=1;void 0!==(x=c[r])&&\"\"!==x||(x=r);var _=d[x=String(x)];void 0===_?(d[x]=a.length,(b=-1!==l.indexOf(x))||(m+=y),a.push({v:y,label:x,color:g(u[r],x),i:r,pts:[r],hidden:b})):(v=!0,(i=a[_]).v+=y,i.pts.push(r),i.hidden||(m+=y),!1===i.color&&u[r]&&(i.color=g(u[r],x)))}return(\"funnelarea\"===e.type?v:e.sort)&&a.sort((function(t,e){return e.v-t.v})),a[0]&&(a[0].vTotal=m),a},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r=\"pie\");var n=t._fullLayout,i=t.calcdata,a=n[r+\"colorway\"],s=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(a=l(a,o));for(var c=0,u=0;u<i.length;u++){var f=i[u];if(f[0].trace.type===r)for(var h=0;h<f.length;h++){var p=f[h];!1===p.color&&(s[p.label]?p.color=s[p.label]:(s[p.label]=p.color=a[c%a.length],c++))}}},makePullColorFn:s,generateExtendedColors:l}},{\"../../components/color\":666,\"fast-isnumeric\":249,tinycolor2:598}],1195:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"./attributes\"),o=t(\"../../plots/domain\").defaults,s=t(\"../bar/defaults\").handleText;function l(t,e){var r=Array.isArray(t),a=i.isArrayOrTypedArray(e),o=Math.min(r?t.length:1/0,a?e.length:1/0);if(isFinite(o)||(o=0),o&&a){for(var s,l=0;l<o;l++){var c=e[l];if(n(c)&&c>0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:a,len:o}}e.exports={handleLabelsAndValues:l,supplyDefaults:function(t,e,r,n){function c(r,n){return i.coerce(t,e,a,r,n)}var u=l(c(\"labels\"),c(\"values\")),f=u.len;if(e._hasLabels=u.hasLabels,e._hasValues=u.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),f){e._length=f,c(\"marker.line.width\")&&c(\"marker.line.color\"),c(\"marker.colors\"),c(\"scalegroup\");var h,p=c(\"text\"),d=c(\"texttemplate\");if(d||(h=c(\"textinfo\",Array.isArray(p)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),d||h&&\"none\"!==h){var g=c(\"textposition\");s(t,e,n,c,g,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(g)||\"auto\"===g||\"outside\"===g)&&c(\"automargin\"),(\"inside\"===g||\"auto\"===g||Array.isArray(g))&&c(\"insidetextorientation\")}o(e,n,c);var m=c(\"hole\");if(c(\"title.text\")){var v=c(\"title.position\",m?\"middle center\":\"top center\");m||\"middle center\"!==v||(e.title.position=\"top center\"),i.coerceFont(c,\"title.font\",n.font)}c(\"sort\"),c(\"direction\"),c(\"rotation\"),c(\"pull\")}else e.visible=!1}}},{\"../../lib\":803,\"../../plots/domain\":882,\"../bar/defaults\":945,\"./attributes\":1192,\"fast-isnumeric\":249}],1196:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx/helpers\").appendArrayMultiPointValues;e.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,bbox:t.bbox,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),\"funnelarea\"===e.type&&(delete r.v,delete r.i),r}},{\"../../components/fx/helpers\":702}],1197:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");function i(t){return-1!==t.indexOf(\"e\")?t.replace(/[.]?0+e/,\"e\"):-1!==t.indexOf(\".\")?t.replace(/[.]?0+$/,\"\"):t}r.formatPiePercent=function(t,e){var r=i((100*t).toPrecision(3));return n.numSeparate(r,e)+\"%\"},r.formatPieValue=function(t,e){var r=i(t.toPrecision(10));return n.numSeparate(r,e)},r.getFirstFilled=function(t,e){if(Array.isArray(t))for(var r=0;r<e.length;r++){var n=t[e[r]];if(n||0===n||\"\"===n)return n}},r.castOption=function(t,e){return Array.isArray(t)?r.getFirstFilled(t,e):t||void 0},r.getRotationAngle=function(t){return(\"auto\"===t?0:t)*Math.PI/180}},{\"../../lib\":803}],1198:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),layoutAttributes:t(\"./layout_attributes\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\").plot,style:t(\"./style\"),styleOne:t(\"./style_one\"),moduleType:\"trace\",name:\"pie\",basePlotModule:t(\"./base_plot\"),categories:[\"pie-like\",\"pie\",\"showLegend\"],meta:{}}},{\"./attributes\":1192,\"./base_plot\":1193,\"./calc\":1194,\"./defaults\":1195,\"./layout_attributes\":1199,\"./layout_defaults\":1200,\"./plot\":1201,\"./style\":1202,\"./style_one\":1203}],1199:[function(t,e,r){\"use strict\";e.exports={hiddenlabels:{valType:\"data_array\",editType:\"calc\"},piecolorway:{valType:\"colorlist\",editType:\"calc\"},extendpiecolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{}],1200:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"piecolorway\",e.colorway),r(\"extendpiecolors\")}},{\"../../lib\":803,\"./layout_attributes\":1199}],1201:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../plots/plots\"),a=t(\"../../components/fx\"),o=t(\"../../components/color\"),s=t(\"../../components/drawing\"),l=t(\"../../lib\"),c=l.strScale,u=l.strTranslate,f=t(\"../../lib/svg_text_utils\"),h=t(\"../bar/uniform_text\"),p=h.recordMinTextSize,d=h.clearMinTextSize,g=t(\"../bar/constants\").TEXTPAD,m=t(\"./helpers\"),v=t(\"./event_data\"),y=t(\"../../lib\").isValidTextValue;function x(t,e,r){var i=r[0],o=i.cx,s=i.cy,c=i.trace,u=\"funnelarea\"===c.type;\"_hasHoverLabel\"in c||(c._hasHoverLabel=!1),\"_hasHoverEvent\"in c||(c._hasHoverEvent=!1),t.on(\"mouseover\",(function(t){var r=e._fullLayout,f=e._fullData[c.index];if(!e._dragging&&!1!==r.hovermode){var h=f.hoverinfo;if(Array.isArray(h)&&(h=a.castHoverinfo({hoverinfo:[m.castOption(h,t.pts)],_module:c._module},r,0)),\"all\"===h&&(h=\"label+text+value+percent+name\"),f.hovertemplate||\"none\"!==h&&\"skip\"!==h&&h){var p=t.rInscribed||0,d=o+t.pxmid[0]*(1-p),g=s+t.pxmid[1]*(1-p),y=r.separators,x=[];if(h&&-1!==h.indexOf(\"label\")&&x.push(t.label),t.text=m.castOption(f.hovertext||f.text,t.pts),h&&-1!==h.indexOf(\"text\")){var b=t.text;l.isValidTextValue(b)&&x.push(b)}t.value=t.v,t.valueLabel=m.formatPieValue(t.v,y),h&&-1!==h.indexOf(\"value\")&&x.push(t.valueLabel),t.percent=t.v/i.vTotal,t.percentLabel=m.formatPiePercent(t.percent,y),h&&-1!==h.indexOf(\"percent\")&&x.push(t.percentLabel);var _=f.hoverlabel,w=_.font,T=[];a.loneHover({trace:c,x0:d-p*i.r,x1:d+p*i.r,y:g,_x0:u?o+t.TL[0]:d-p*i.r,_x1:u?o+t.TR[0]:d+p*i.r,_y0:u?s+t.TL[1]:g-p*i.r,_y1:u?s+t.BL[1]:g+p*i.r,text:x.join(\"<br>\"),name:f.hovertemplate||-1!==h.indexOf(\"name\")?f.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:m.castOption(_.bgcolor,t.pts)||t.color,borderColor:m.castOption(_.bordercolor,t.pts),fontFamily:m.castOption(w.family,t.pts),fontSize:m.castOption(w.size,t.pts),fontColor:m.castOption(w.color,t.pts),nameLength:m.castOption(_.namelength,t.pts),textAlign:m.castOption(_.align,t.pts),hovertemplate:m.castOption(f.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[v(t,f)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e,inOut_bbox:T}),t.bbox=T[0],c._hasHoverLabel=!0}c._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[v(t,f)],event:n.event})}})),t.on(\"mouseout\",(function(t){var r=e._fullLayout,i=e._fullData[c.index],o=n.select(this).datum();c._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[v(o,i)],event:n.event}),c._hasHoverEvent=!1),c._hasHoverLabel&&(a.loneUnhover(r._hoverlayer.node()),c._hasHoverLabel=!1)})),t.on(\"click\",(function(t){var r=e._fullLayout,i=e._fullData[c.index];e._dragging||!1===r.hovermode||(e._hoverdata=[v(t,i)],a.click(e,n.event))}))}function b(t,e,r){var n=m.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=m.castOption(t._input.textfont.color,e.pts));var i=m.castOption(t.insidetextfont.family,e.pts)||m.castOption(t.textfont.family,e.pts)||r.family,a=m.castOption(t.insidetextfont.size,e.pts)||m.castOption(t.textfont.size,e.pts)||r.size;return{color:n||o.contrast(e.color),family:i,size:a}}function _(t,e){for(var r,n,i=0;i<t.length;i++)if((n=(r=t[i][0]).trace).title.text){var a=n.title.text;n._meta&&(a=l.templateString(a,n._meta));var o=s.tester.append(\"text\").attr(\"data-notex\",1).text(a).call(s.font,n.title.font).call(f.convertToTspans,e),c=s.bBox(o.node(),!0);r.titleBox={width:c.width,height:c.height},o.remove()}}function w(t,e,r){var n=r.r||e.rpx1,i=e.rInscribed;if(e.startangle===e.stopangle)return{rCenter:1-i,scale:0,rotate:0,textPosAngle:0};var a,o=e.ring,s=1===o&&Math.abs(e.startangle-e.stopangle)===2*Math.PI,l=e.halfangle,c=e.midangle,u=r.trace.insidetextorientation,f=\"horizontal\"===u,h=\"tangential\"===u,p=\"radial\"===u,d=\"auto\"===u,g=[];if(!d){var m,v=function(r,i){if(function(t,e){var r=t.startangle,n=t.stopangle;return r>e&&e>n||r<e&&e<n}(e,r)){var s=Math.abs(r-e.startangle),l=Math.abs(r-e.stopangle),c=s<l?s:l;(a=\"tan\"===i?k(t,n,o,c,0):T(t,n,o,c,Math.PI/2)).textPosAngle=r,g.push(a)}};if(f||h){for(m=4;m>=-4;m-=2)v(Math.PI*m,\"tan\");for(m=4;m>=-4;m-=2)v(Math.PI*(m+1),\"tan\")}if(f||p){for(m=4;m>=-4;m-=2)v(Math.PI*(m+1.5),\"rad\");for(m=4;m>=-4;m-=2)v(Math.PI*(m+.5),\"rad\")}}if(s||d||f){var y=Math.sqrt(t.width*t.width+t.height*t.height);if((a={scale:i*n*2/y,rCenter:1-i,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,a.scale>=1)return a;g.push(a)}(d||p)&&((a=T(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,g.push(a)),(d||h)&&((a=k(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,g.push(a));for(var x=0,b=0,_=0;_<g.length;_++){var w=g[_].scale;if(b<w&&(b=w,x=_),!d&&b>=1)break}return g[x]}function T(t,e,r,n,i){e=Math.max(0,e-2*g);var a=t.width/t.height,o=S(a,n,e,r);return{scale:2*o/t.height,rCenter:A(a,o/e),rotate:M(i)}}function k(t,e,r,n,i){e=Math.max(0,e-2*g);var a=t.height/t.width,o=S(a,n,e,r);return{scale:2*o/t.width,rCenter:A(a,o/e),rotate:M(i+Math.PI/2)}}function A(t,e){return Math.cos(e)-t*e}function M(t){return(180/Math.PI*t+720)%180-90}function S(t,e,r,n){var i=t+1/(2*Math.tan(e));return r*Math.min(1/(Math.sqrt(i*i+.5)+i),n/(Math.sqrt(t*t+n/2)+t))}function E(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function L(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return r<0&&(i*=-1),n<0&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function C(t,e){var r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=I(a),-1!==a.title.position.indexOf(\"top\")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf(\"bottom\")&&(o.y+=(1+i)*t.r);var l,c,u=(l=t.r,c=t.trace.aspectratio,l/(void 0===c?1:c)),f=e.w*(a.domain.x[1]-a.domain.x[0])/2;return-1!==a.title.position.indexOf(\"left\")?(f+=u,o.x-=(1+i)*u,s.tx+=t.titleBox.width/2):-1!==a.title.position.indexOf(\"center\")?f*=2:-1!==a.title.position.indexOf(\"right\")&&(f+=u,o.x+=(1+i)*u,s.tx-=t.titleBox.width/2),r=f/t.titleBox.width,n=P(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function P(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function I(t){var e,r=t.pull;if(!r)return 0;if(Array.isArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function O(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n][0],a=i.trace,o=a.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);a.title.text&&\"middle center\"!==a.title.position&&(l-=P(i,e));var c=s/2,u=l/2;\"funnelarea\"!==a.type||a.scalegroup||(u/=a.aspectratio),i.r=Math.min(c,u)/(1+I(a)),i.cx=e.l+e.w*(a.domain.x[1]+a.domain.x[0])/2,i.cy=e.t+e.h*(1-a.domain.y[0])-l/2,a.title.text&&-1!==a.title.position.indexOf(\"bottom\")&&(i.cy-=P(i,e)),a.scalegroup&&-1===r.indexOf(a.scalegroup)&&r.push(a.scalegroup)}!function(t,e){for(var r,n,i,a=0;a<e.length;a++){var o=1/0,s=e[a];for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var l;if(\"pie\"===i.type)l=r.r*r.r;else if(\"funnelarea\"===i.type){var c,u;i.aspectratio>1?(c=r.r,u=c/i.aspectratio):(u=r.r,c=u*i.aspectratio),c*=(1+i.baseratio)/2,l=c*u}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var f=o*r.vTotal;\"funnelarea\"===i.type&&(f/=(1+i.baseratio)/2,f/=i.aspectratio),r.r=Math.sqrt(f)}}}(t,r)}function z(t,e){return[t*Math.sin(e),-t*Math.cos(e)]}function D(t,e,r){var n=t._fullLayout,i=r.trace,a=i.texttemplate,o=i.textinfo;if(!a&&o&&\"none\"!==o){var s,c=o.split(\"+\"),u=function(t){return-1!==c.indexOf(t)},f=u(\"label\"),h=u(\"text\"),p=u(\"value\"),d=u(\"percent\"),g=n.separators;if(s=f?[e.label]:[],h){var v=m.getFirstFilled(i.text,e.pts);y(v)&&s.push(v)}p&&s.push(m.formatPieValue(e.v,g)),d&&s.push(m.formatPiePercent(e.v/r.vTotal,g)),e.text=s.join(\"<br>\")}if(a){var x=l.castOption(i,e.i,\"texttemplate\");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:m.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:m.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(i,t.i,\"customdata\")}}(e),_=m.getFirstFilled(i.text,e.pts);(y(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,i._meta||{})}else e.text=\"\"}}function R(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}e.exports={plot:function(t,e){var r=t._fullLayout,a=r._size;d(\"pie\",r),_(e,t),O(e,a);var h=l.makeTraceGroups(r._pielayer,e,\"trace\").each((function(e){var h=n.select(this),d=e[0],g=d.trace;!function(t){var e,r,n,i=t[0],a=i.r,o=i.trace,s=m.getRotationAngle(o.rotation),l=2*Math.PI/i.vTotal,c=\"px0\",u=\"px1\";if(\"counterclockwise\"===o.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;s+=l*t[e].v,l*=-1,c=\"px1\",u=\"px0\"}for(n=z(a,s),e=0;e<t.length;e++)(r=t[e]).hidden||(r[c]=n,r.startangle=s,s+=l*r.v/2,r.pxmid=z(a,s),r.midangle=s,s+=l*r.v/2,n=z(a,s),r.stopangle=s,r[u]=n,r.largeArc=r.v>i.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/i.vTotal,.5),r.ring=1-o.hole,r.rInscribed=E(r,i))}(e),h.attr(\"stroke-linejoin\",\"round\"),h.each((function(){var v=n.select(this).selectAll(\"g.slice\").data(e);v.enter().append(\"g\").classed(\"slice\",!0),v.exit().remove();var y=[[[],[]],[[],[]]],_=!1;v.each((function(i,a){if(i.hidden)n.select(this).selectAll(\"path,g\").remove();else{i.pointNumber=i.i,i.curveNumber=g.index,y[i.pxmid[1]<0?0:1][i.pxmid[0]<0?0:1].push(i);var o=d.cx,c=d.cy,u=n.select(this),h=u.selectAll(\"path.surface\").data([i]);if(h.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),u.call(x,t,e),g.pull){var v=+m.castOption(g.pull,i.pts)||0;v>0&&(o+=v*i.pxmid[0],c+=v*i.pxmid[1])}i.cxFinal=o,i.cyFinal=c;var T=g.hole;if(i.v===d.vTotal){var k=\"M\"+(o+i.px0[0])+\",\"+(c+i.px0[1])+C(i.px0,i.pxmid,!0,1)+C(i.pxmid,i.px0,!0,1)+\"Z\";T?h.attr(\"d\",\"M\"+(o+T*i.px0[0])+\",\"+(c+T*i.px0[1])+C(i.px0,i.pxmid,!1,T)+C(i.pxmid,i.px0,!1,T)+\"Z\"+k):h.attr(\"d\",k)}else{var A=C(i.px0,i.px1,!0,1);if(T){var M=1-T;h.attr(\"d\",\"M\"+(o+T*i.px1[0])+\",\"+(c+T*i.px1[1])+C(i.px1,i.px0,!1,T)+\"l\"+M*i.px0[0]+\",\"+M*i.px0[1]+A+\"Z\")}else h.attr(\"d\",\"M\"+o+\",\"+c+\"l\"+i.px0[0]+\",\"+i.px0[1]+A+\"Z\")}D(t,i,d);var S=m.castOption(g.textposition,i.pts),E=u.selectAll(\"g.slicetext\").data(i.text&&\"none\"!==S?[0]:[]);E.enter().append(\"g\").classed(\"slicetext\",!0),E.exit().remove(),E.each((function(){var u=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),h=l.ensureUniformFontSize(t,\"outside\"===S?function(t,e,r){var n=m.castOption(t.outsidetextfont.color,e.pts)||m.castOption(t.textfont.color,e.pts)||r.color,i=m.castOption(t.outsidetextfont.family,e.pts)||m.castOption(t.textfont.family,e.pts)||r.family,a=m.castOption(t.outsidetextfont.size,e.pts)||m.castOption(t.textfont.size,e.pts)||r.size;return{color:n,family:i,size:a}}(g,i,r.font):b(g,i,r.font));u.text(i.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,h).call(f.convertToTspans,t);var v,y=s.bBox(u.node());if(\"outside\"===S)v=L(y,i);else if(v=w(y,i,d),\"auto\"===S&&v.scale<1){var x=l.ensureUniformFontSize(t,g.outsidetextfont);u.call(s.font,x),v=L(y=s.bBox(u.node()),i)}var T=v.textPosAngle,k=void 0===T?i.pxmid:z(d.r,T);if(v.targetX=o+k[0]*v.rCenter+(v.x||0),v.targetY=c+k[1]*v.rCenter+(v.y||0),R(v,y),v.outside){var A=v.targetY;i.yLabelMin=A-y.height/2,i.yLabelMid=A,i.yLabelMax=A+y.height/2,i.labelExtraX=0,i.labelExtraY=0,_=!0}v.fontSize=h.size,p(g.type,v,r),e[a].transform=v,u.attr(\"transform\",l.getTextTransform(v))}))}function C(t,e,r,n){var a=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return\"a\"+n*d.r+\",\"+n*d.r+\" 0 \"+i.largeArc+(r?\" 1 \":\" 0 \")+a+\",\"+o}}));var T=n.select(this).selectAll(\"g.titletext\").data(g.title.text?[0]:[]);if(T.enter().append(\"g\").classed(\"titletext\",!0),T.exit().remove(),T.each((function(){var e,r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),i=g.title.text;g._meta&&(i=l.templateString(i,g._meta)),r.text(i).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,g.title.font).call(f.convertToTspans,t),e=\"middle center\"===g.title.position?function(t){var 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i=n.datum().link.label;n.style(\"fill-opacity\",(function(t){if(!t.link.concentrationscale)return.4})),i&&h(e,t).selectAll(\".\"+c.sankeyLink).filter((function(t){return t.link.label===i})).style(\"fill-opacity\",(function(t){if(!t.link.concentrationscale)return.4})),r&&h(e,t).selectAll(\".\"+c.sankeyNode).filter(m(t)).call(v)}function b(t,e,r,n){var i=n.datum().link.label;n.style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})),i&&h(e,t).selectAll(\".\"+c.sankeyLink).filter((function(t){return t.link.label===i})).style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})),r&&h(e,t).selectAll(c.sankeyNode).filter(m(t)).call(y)}function _(t,e){var r=t.hoverlabel||{},n=i.nestedProperty(r,e).get();return!Array.isArray(n)&&n}e.exports=function(t,e){for(var r=t._fullLayout,i=r._paper,h=r._size,g=0;g<t._fullData.length;g++)if(t._fullData[g].visible&&t._fullData[g].type===c.sankey&&!t._fullData[g]._viewInitial){var m=t._fullData[g].node;t._fullData[g]._viewInitial={node:{groups:m.groups.slice(),x:m.x.slice(),y:m.y.slice()}}}var w=u(t,\"source:\")+\" \",T=u(t,\"target:\")+\" \",k=u(t,\"concentration:\")+\" \",A=u(t,\"incoming flow count:\")+\" \",M=u(t,\"outgoing flow count:\")+\" \";o(t,i,e,{width:h.w,height:h.h,margin:{t:h.t,r:h.r,b:h.b,l:h.l}},{linkEvents:{hover:function(e,r,i){!1!==t._fullLayout.hovermode&&(n.select(e).call(x.bind(0,r,i,!0)),\"skip\"!==r.link.trace.link.hoverinfo&&(r.link.fullData=r.link.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.link]})))},follow:function(e,i){if(!1!==t._fullLayout.hovermode){var o=i.link.trace.link;if(\"none\"!==o.hoverinfo&&\"skip\"!==o.hoverinfo){for(var c=[],u=0,h=0;h<i.flow.links.length;h++){var g=i.flow.links[h];if(\"closest\"!==t._fullLayout.hovermode||i.link.pointNumber===g.pointNumber){i.link.pointNumber===g.pointNumber&&(u=h),g.fullData=g.trace,o=i.link.trace.link;var m=y(g),v={valueLabel:a(i.valueFormat)(g.value)+i.valueSuffix};c.push({x:m[0],y:m[1],name:v.valueLabel,text:[g.label||\"\",w+g.source.label,T+g.target.label,g.concentrationscale?k+a(\"%0.2f\")(g.flow.labelConcentration):\"\"].filter(f).join(\"<br>\"),color:_(o,\"bgcolor\")||l.addOpacity(g.color,1),borderColor:_(o,\"bordercolor\"),fontFamily:_(o,\"font.family\"),fontSize:_(o,\"font.size\"),fontColor:_(o,\"font.color\"),nameLength:_(o,\"namelength\"),textAlign:_(o,\"align\"),idealAlign:n.event.x<m[0]?\"right\":\"left\",hovertemplate:o.hovertemplate,hovertemplateLabels:v,eventData:[g]})}}s.loneHover(c,{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t,anchorIndex:u}).each((function(){i.link.concentrationscale||p(this,.65),d(this)}))}}function y(t){var e,r;t.circular?(e=(t.circularPathData.leftInnerExtent+t.circularPathData.rightInnerExtent)/2,r=t.circularPathData.verticalFullExtent):(e=(t.source.x1+t.target.x0)/2,r=(t.y0+t.y1)/2);var n=[e,r];return\"v\"===t.trace.orientation&&n.reverse(),n[0]+=i.parent.translateX,n[1]+=i.parent.translateY,n}},unhover:function(e,i,a){!1!==t._fullLayout.hovermode&&(n.select(e).call(b.bind(0,i,a,!0)),\"skip\"!==i.link.trace.link.hoverinfo&&(i.link.fullData=i.link.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[i.link]})),s.loneUnhover(r._hoverlayer.node()))},select:function(e,r){var i=r.link;i.originalEvent=n.event,t._hoverdata=[i],s.click(t,{target:!0})}},nodeEvents:{hover:function(e,r,i){!1!==t._fullLayout.hovermode&&(n.select(e).call(v,r,i),\"skip\"!==r.node.trace.node.hoverinfo&&(r.node.fullData=r.node.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.node]})))},follow:function(e,i){if(!1!==t._fullLayout.hovermode){var o=i.node.trace.node;if(\"none\"!==o.hoverinfo&&\"skip\"!==o.hoverinfo){var l=n.select(e).select(\".\"+c.nodeRect),u=t._fullLayout._paperdiv.node().getBoundingClientRect(),h=l.node().getBoundingClientRect(),g=h.left-2-u.left,m=h.right+2-u.left,v=h.top+h.height/4-u.top,y={valueLabel:a(i.valueFormat)(i.node.value)+i.valueSuffix};i.node.fullData=i.node.trace,t._fullLayout._calcInverseTransform(t);var x=t._fullLayout._invScaleX,b=t._fullLayout._invScaleY,w=s.loneHover({x0:x*g,x1:x*m,y:b*v,name:a(i.valueFormat)(i.node.value)+i.valueSuffix,text:[i.node.label,A+i.node.targetLinks.length,M+i.node.sourceLinks.length].filter(f).join(\"<br>\"),color:_(o,\"bgcolor\")||i.tinyColorHue,borderColor:_(o,\"bordercolor\"),fontFamily:_(o,\"font.family\"),fontSize:_(o,\"font.size\"),fontColor:_(o,\"font.color\"),nameLength:_(o,\"namelength\"),textAlign:_(o,\"align\"),idealAlign:\"left\",hovertemplate:o.hovertemplate,hovertemplateLabels:y,eventData:[i.node]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t});p(w,.85),d(w)}}},unhover:function(e,i,a){!1!==t._fullLayout.hovermode&&(n.select(e).call(y,i,a),\"skip\"!==i.node.trace.node.hoverinfo&&(i.node.fullData=i.node.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[i.node]})),s.loneUnhover(r._hoverlayer.node()))},select:function(e,r,i){var 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n,i=y(e),a=i.trace,u=a.domain,f=\"h\"===a.orientation,p=a.node.pad,d=a.node.thickness,g=t.width*(u.x[1]-u.x[0]),m=t.height*(u.y[1]-u.y[0]),v=i._nodes,x=i._links,b=i.circular;(n=b?s.sankeyCircular().circularLinkGap(0):o.sankey()).iterations(l.sankeyIterations).size(f?[g,m]:[m,g]).nodeWidth(d).nodePadding(p).nodeId((function(t){return t.pointNumber})).nodes(v).links(x);var _,w,T,k=n();for(var A in n.nodePadding()<p&&h.warn(\"node.pad was reduced to \",n.nodePadding(),\" to fit within the figure.\"),i._groupLookup){var M,S=parseInt(i._groupLookup[A]);for(_=0;_<k.nodes.length;_++)if(k.nodes[_].pointNumber===S){M=k.nodes[_];break}if(M){var E={pointNumber:parseInt(A),x0:M.x0,x1:M.x1,y0:M.y0,y1:M.y1,partOfGroup:!0,sourceLinks:[],targetLinks:[]};k.nodes.unshift(E),M.childrenNodes.unshift(E)}}if(function(){for(_=0;_<k.nodes.length;_++){var t,e,r=k.nodes[_],n={};for(w=0;w<r.targetLinks.length;w++)t=(e=r.targetLinks[w]).source.pointNumber+\":\"+e.target.pointNumber,n.hasOwnProperty(t)||(n[t]=[]),n[t].push(e);var i=Object.keys(n);for(w=0;w<i.length;w++){var a=n[t=i[w]],o=0,s={};for(T=0;T<a.length;T++)s[(e=a[T]).label]||(s[e.label]=0),s[e.label]+=e.value,o+=e.value;for(T=0;T<a.length;T++)(e=a[T]).flow={value:o,labelConcentration:s[e.label]/o,concentration:e.value/o,links:a},e.concentrationscale&&(e.color=c(e.concentrationscale(e.flow.labelConcentration)))}var l=0;for(w=0;w<r.sourceLinks.length;w++)l+=r.sourceLinks[w].value;for(w=0;w<r.sourceLinks.length;w++)(e=r.sourceLinks[w]).concentrationOut=e.value/l;var u=0;for(w=0;w<r.targetLinks.length;w++)u+=r.targetLinks[w].value;for(w=0;w<r.targetLinks.length;w++)(e=r.targetLinks[w]).concenrationIn=e.value/u}}(),a.node.x.length&&a.node.y.length){for(_=0;_<Math.min(a.node.x.length,a.node.y.length,k.nodes.length);_++)if(a.node.x[_]&&a.node.y[_]){var L=[a.node.x[_]*g,a.node.y[_]*m];k.nodes[_].x0=L[0]-d/2,k.nodes[_].x1=L[0]+d/2;var C=k.nodes[_].y1-k.nodes[_].y0;k.nodes[_].y0=L[1]-C/2,k.nodes[_].y1=L[1]+C/2}if(\"snap\"===a.arrangement)!function(t){t.forEach((function(t){var e,r,n,i=0,a=t.length;for(t.sort((function(t,e){return t.y0-e.y0})),n=0;n<a;++n)(e=t[n]).y0>=i||(r=i-e.y0)>1e-6&&(e.y0+=r,e.y1+=r),i=e.y1+p}))}(function(t){var e,r,n=t.map((function(t,e){return{x0:t.x0,index:e}})).sort((function(t,e){return t.x0-e.x0})),i=[],a=-1,o=-1/0;for(_=0;_<n.length;_++){var s=t[n[_].index];s.x0>o+d&&(a+=1,e=s.x0),o=s.x0,i[a]||(i[a]=[]),i[a].push(s),r=e-s.x0,s.x0+=r,s.x1+=r}return 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e.trace=t.trace,e.curveNumber=t.trace.index,{circular:t.circular,key:i,traceId:t.key,pointNumber:e.pointNumber,link:e,tinyColorHue:u.tinyRGB(n),tinyColorAlpha:n.getAlpha(),linkPath:M,linkLineColor:t.linkLineColor,linkLineWidth:t.linkLineWidth,valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,parent:t,interactionState:t.interactionState,flow:e.flow}}function M(){return function(t){if(t.link.circular)return e=t.link,r=e.width/2,n=e.circularPathData,\"top\"===e.circularLinkType?\"M \"+n.targetX+\" \"+(n.targetY+r)+\" L\"+n.rightInnerExtent+\" \"+(n.targetY+r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 1 \"+(n.rightFullExtent-r)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 1 \"+n.rightInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 1 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 0 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"L\"+n.rightInnerExtent+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 0 \"+(n.rightFullExtent+r)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" 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\"+(n.sourceY+r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 1 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+n.rightInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 1 \"+(n.rightFullExtent+r)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 1 \"+n.rightInnerExtent+\" \"+(n.targetY+r)+\"L\"+n.targetX+\" \"+(n.targetY+r)+\"Z\";var e,r,n,a=t.link.source.x1,o=t.link.target.x0,s=i(a,o),l=s(.5),c=s(.5),u=t.link.y0-t.link.width/2,f=t.link.y0+t.link.width/2,h=t.link.y1-t.link.width/2,p=t.link.y1+t.link.width/2;return\"M\"+a+\",\"+u+\"C\"+l+\",\"+u+\" \"+c+\",\"+h+\" 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e.group&&(s=h.randstr()),e.trace=t.trace,e.curveNumber=t.trace.index,{index:e.pointNumber,key:s,partOfGroup:e.partOfGroup||!1,group:e.group,traceId:t.key,trace:t.trace,node:e,nodePad:t.nodePad,nodeLineColor:t.nodeLineColor,nodeLineWidth:t.nodeLineWidth,textFont:t.textFont,size:t.horizontal?t.height:t.width,visibleWidth:Math.ceil(a),visibleHeight:o,zoneX:-n,zoneY:-i,zoneWidth:a+2*n,zoneHeight:o+2*i,labelY:t.horizontal?e.dy/2+1:e.dx/2+1,left:1===e.originalLayer,sizeAcross:t.width,forceLayouts:t.forceLayouts,horizontal:t.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:u.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,graph:t.graph,arrangement:t.arrangement,uniqueNodeLabelPathId:[t.guid,t.key,s].join(\"_\"),interactionState:t.interactionState,figure:t}}function E(t){t.attr(\"transform\",(function(t){return p(t.node.x0.toFixed(3),t.node.y0.toFixed(3))}))}function L(t){t.call(E)}function 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n=t(\"../../components/colorscale/helpers\").hasColorscale,i=t(\"../../components/colorscale/calc\"),a=t(\"./subtypes\");e.exports=function(t,e){a.hasLines(e)&&n(e,\"line\")&&i(t,e,{vals:e.line.color,containerStr:\"line\",cLetter:\"c\"}),a.hasMarkers(e)&&(n(e,\"marker\")&&i(t,e,{vals:e.marker.color,containerStr:\"marker\",cLetter:\"c\"}),n(e,\"marker.line\")&&i(t,e,{vals:e.marker.line.color,containerStr:\"marker.line\",cLetter:\"c\"}))}},{\"../../components/colorscale/calc\":674,\"../../components/colorscale/helpers\":677,\"./subtypes\":1243}],1222:[function(t,e,r){\"use strict\";e.exports={PTS_LINESONLY:20,minTolerance:.2,toleranceGrowth:10,maxScreensAway:20,eventDataKeys:[]}},{}],1223:[function(t,e,r){\"use strict\";var n=t(\"./calc\");function i(t,e,r,n,i,a,o){i[n]=!0;var s={i:null,gap:!0,s:0};if(s[o]=r,t.splice(e,0,s),e&&r===t[e-1][o]){var l=t[e-1];s.s=l.s,s.i=l.i,s.gap=l.gap}else a&&(s.s=function(t,e,r,n){var i=t[e-1],a=t[e+1];return 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n=t(\"../../components/color\"),i=t(\"../../lib\").isArrayOrTypedArray;e.exports=function(t,e,r,a){var o=!1;if(e.marker){var s=e.marker.color,l=(e.marker.line||{}).color;s&&!i(s)?o=s:l&&!i(l)&&(o=l)}a(\"fillcolor\",n.addOpacity((e.line||{}).color||o||r,.5))}},{\"../../components/color\":666,\"../../lib\":803}],1227:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\");e.exports=function(t,e,r){var i={},a={_fullLayout:r},o=n.getFromTrace(a,e,\"x\"),s=n.getFromTrace(a,e,\"y\");return i.xLabel=n.tickText(o,o.c2l(t.x),!0).text,i.yLabel=n.tickText(s,s.c2l(t.y),!0).text,i}},{\"../../plots/cartesian/axes\":854}],1228:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),i=t(\"./subtypes\");e.exports=function(t,e){var r,a;if(\"lines\"===t.mode)return(r=t.line.color)&&n.opacity(r)?r:t.fillcolor;if(\"none\"===t.mode)return t.fill?t.fillcolor:\"\";var 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d=t.opacity;if(t.marker&&t.marker.opacity&&(d*=t.marker.opacity),r={gl:this.scene.glplot.gl,position:p.position,color:p.scatterColor,size:p.scatterSize,glyph:p.scatterMarker,opacity:d,orthographic:!0,lineWidth:p.scatterLineWidth,lineColor:p.scatterLineColor,project:p.project,projectScale:p.projectScale,projectOpacity:p.projectOpacity},-1!==this.mode.indexOf(\"markers\")?this.scatterPlot?this.scatterPlot.update(r):(this.scatterPlot=i(r),this.scatterPlot._trace=this,this.scatterPlot.highlightScale=1,this.scene.glplot.add(this.scatterPlot)):this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose(),this.scatterPlot=null),c={gl:this.scene.glplot.gl,position:p.position,glyph:p.text,color:p.textColor,size:p.textSize,angle:p.textAngle,alignment:p.textOffset,font:p.textFont,orthographic:!0,lineWidth:0,project:!1,opacity:t.opacity},this.textLabels=t.hovertext||t.text,-1!==this.mode.indexOf(\"text\")?this.textMarkers?this.textMarkers.update(c):(this.textMarkers=i(c),this.textMarkers._trace=this,this.textMarkers.highlightScale=1,this.scene.glplot.add(this.textMarkers)):this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose(),this.textMarkers=null),l={gl:this.scene.glplot.gl,position:p.position,color:p.errorColor,error:p.errorBounds,lineWidth:p.errorLineWidth,capSize:p.errorCapSize,opacity:t.opacity},this.errorBars?p.errorBounds?this.errorBars.update(l):(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose(),this.errorBars=null):p.errorBounds&&(this.errorBars=a(l),this.errorBars._trace=this,this.scene.glplot.add(this.errorBars)),p.delaunayAxis>=0){var g=function(t,e,r){var n,i=(r+1)%3,a=(r+2)%3,o=[],l=[];for(n=0;n<t.length;++n){var c=t[n];!isNaN(c[i])&&isFinite(c[i])&&!isNaN(c[a])&&isFinite(c[a])&&(o.push([c[i],c[a]]),l.push(n))}var u=s(o);for(n=0;n<u.length;++n)for(var f=u[n],h=0;h<f.length;++h)f[h]=l[f[h]];return{positions:t,cells:u,meshColor:e}}(p.position,p.delaunayColor,p.delaunayAxis);g.opacity=t.opacity,this.delaunayMesh?this.delaunayMesh.update(g):(g.gl=u,this.delaunayMesh=o(g),this.delaunayMesh._trace=this,this.scene.glplot.add(this.delaunayMesh))}else this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose(),this.delaunayMesh=null)},y.dispose=function(){this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose()),this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose()),this.errorBars&&(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose()),this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose()),this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose())},e.exports=function(t,e){var r=new v(t,e.uid);return r.update(e),r}},{\"../../components/fx/helpers\":702,\"../../constants/gl3d_dashes\":776,\"../../constants/gl3d_markers\":777,\"../../lib\":803,\"../../lib/gl_format_color\":799,\"../../lib/str2rgbarray\":828,\"../../plots/cartesian/axes\":854,\"../scatter/make_bubble_size_func\":1235,\"./calc_errors\":1248,\"delaunay-triangulate\":180,\"gl-error3d\":273,\"gl-line3d\":281,\"gl-mesh3d\":315,\"gl-scatter3d\":334}],1250:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function f(r,n){return i.coerce(t,e,c,r,n)}if(function(t,e,r,i){var a=0,o=r(\"x\"),s=r(\"y\"),l=r(\"z\");n.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\",\"z\"],i),o&&s&&l&&(a=Math.min(o.length,s.length,l.length),e._length=e._xlength=e._ylength=e._zlength=a);return 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strict\";e.exports={plot:t(\"./convert\"),attributes:t(\"./attributes\"),markerSymbols:t(\"../../constants/gl3d_markers\"),supplyDefaults:t(\"./defaults\"),colorbar:[{container:\"marker\",min:\"cmin\",max:\"cmax\"},{container:\"line\",min:\"cmin\",max:\"cmax\"}],calc:t(\"./calc\"),moduleType:\"trace\",name:\"scatter3d\",basePlotModule:t(\"../../plots/gl3d\"),categories:[\"gl3d\",\"symbols\",\"showLegend\",\"scatter-like\"],meta:{}}},{\"../../constants/gl3d_markers\":777,\"../../plots/gl3d\":896,\"./attributes\":1246,\"./calc\":1247,\"./convert\":1249,\"./defaults\":1250}],1252:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../../plots/template_attributes\").texttemplateAttrs,s=t(\"../../components/colorscale/attributes\"),l=t(\"../../lib/extend\").extendFlat,c=n.marker,u=n.line,f=c.line;e.exports={carpet:{valType:\"string\",editType:\"calc\"},a:{valType:\"data_array\",editType:\"calc\"},b:{valType:\"data_array\",editType:\"calc\"},mode:l({},n.mode,{dflt:\"markers\"}),text:l({},n.text,{}),texttemplate:o({editType:\"plot\"},{keys:[\"a\",\"b\",\"text\"]}),hovertext:l({},n.hovertext,{}),line:{color:u.color,width:u.width,dash:u.dash,shape:l({},u.shape,{values:[\"linear\",\"spline\"]}),smoothing:u.smoothing,editType:\"calc\"},connectgaps:n.connectgaps,fill:l({},n.fill,{values:[\"none\",\"toself\",\"tonext\"],dflt:\"none\"}),fillcolor:n.fillcolor,marker:l({symbol:c.symbol,opacity:c.opacity,maxdisplayed:c.maxdisplayed,size:c.size,sizeref:c.sizeref,sizemin:c.sizemin,sizemode:c.sizemode,line:l({width:f.width,editType:\"calc\"},s(\"marker.line\")),gradient:c.gradient,editType:\"calc\"},s(\"marker\")),textfont:n.textfont,textposition:n.textposition,selected:n.selected,unselected:n.unselected,hoverinfo:l({},i.hoverinfo,{flags:[\"a\",\"b\",\"text\",\"name\"]}),hoveron:n.hoveron,hovertemplate:a()}},{\"../../components/colorscale/attributes\":673,\"../../lib/extend\":793,\"../../plots/attributes\":850,\"../../plots/template_attributes\":926,\"../scatter/attributes\":1218}],1253:[function(t,e,r){\"use 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n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/line_shape_defaults\"),c=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),f=t(\"./attributes\");e.exports=function(t,e,r,h){function p(r,i){return n.coerce(t,e,f,r,i)}p(\"carpet\"),e.xaxis=\"x\",e.yaxis=\"y\";var d=p(\"a\"),g=p(\"b\"),m=Math.min(d.length,g.length);if(m){e._length=m,p(\"text\"),p(\"texttemplate\"),p(\"hovertext\"),p(\"mode\",m<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&(s(t,e,r,h,p),l(t,e,p),p(\"connectgaps\")),a.hasMarkers(e)&&o(t,e,r,h,p,{gradient:!0}),a.hasText(e)&&c(t,e,h,p);var v=[];(a.hasMarkers(e)||a.hasText(e))&&(p(\"marker.maxdisplayed\"),v.push(\"points\")),p(\"fill\"),\"none\"!==e.fill&&(u(t,e,r,p),a.hasLines(e)||l(t,e,p)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||v.push(\"fills\"),\"fills\"!==p(\"hoveron\",v.join(\"+\")||\"points\")&&p(\"hovertemplate\"),n.coerceSelectionMarkerOpacity(e,p)}else e.visible=!1}},{\"../../lib\":803,\"../scatter/constants\":1222,\"../scatter/fillcolor_defaults\":1226,\"../scatter/line_defaults\":1231,\"../scatter/line_shape_defaults\":1233,\"../scatter/marker_defaults\":1237,\"../scatter/subtypes\":1243,\"../scatter/text_defaults\":1244,\"./attributes\":1252}],1255:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,i){var a=n[i];return t.a=a.a,t.b=a.b,t.y=a.y,t}},{}],1256:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r={},n=e._carpet,i=n.ab2ij([t.a,t.b]),a=Math.floor(i[0]),o=i[0]-a,s=Math.floor(i[1]),l=i[1]-s,c=n.evalxy([],a,s,o,l);return r.yLabel=c[1].toFixed(3),r}},{}],1257:[function(t,e,r){\"use 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n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../scatter/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../components/colorscale/attributes\"),l=t(\"../../components/drawing/attributes\").dash,c=t(\"../../lib/extend\").extendFlat,u=t(\"../../plot_api/edit_types\").overrideAll,f=a.marker,h=a.line,p=f.line;e.exports=u({lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country 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n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/text_defaults\"),l=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function f(r,i){return n.coerce(t,e,c,r,i)}var h,p=f(\"locations\");if(p&&p.length){var d,g=f(\"geojson\");(\"string\"==typeof g&&\"\"!==g||n.isPlainObject(g))&&(d=\"geojson-id\"),\"geojson-id\"===f(\"locationmode\",d)&&f(\"featureidkey\"),h=p.length}else{var 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t.lonLabel=b.lonLabel,t.latLabel=b.latLabel,t.color=a(c,g),t.extraText=function(t,e,r,n){if(t.hovertemplate)return;var i=e.hi||t.hoverinfo,a=\"all\"===i?s.hoverinfo.flags:i.split(\"+\"),l=-1!==a.indexOf(\"location\")&&Array.isArray(t.locations),c=-1!==a.indexOf(\"lon\"),u=-1!==a.indexOf(\"lat\"),f=-1!==a.indexOf(\"text\"),h=[];function p(t){return t+\"\\xb0\"}l?h.push(e.loc):c&&u?h.push(\"(\"+p(r.latLabel)+\", \"+p(r.lonLabel)+\")\"):c?h.push(n.lon+p(r.lonLabel)):u&&h.push(n.lat+p(r.latLabel));f&&o(e,t,h);return h.join(\"<br>\")}(c,g,t,l[0].t.labels),t.hovertemplate=c.hovertemplate,[t]}}},{\"../../components/fx\":706,\"../../constants/numerical\":779,\"../../lib\":803,\"../scatter/get_trace_color\":1228,\"./attributes\":1260}],1266:[function(t,e,r){\"use 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n=t(\"@plotly/d3\"),i=t(\"../../lib\"),a=t(\"../../lib/topojson_utils\").getTopojsonFeatures,o=t(\"../../lib/geojson_utils\"),s=t(\"../../lib/geo_location_utils\"),l=t(\"../../plots/cartesian/autorange\").findExtremes,c=t(\"../../constants/numerical\").BADNUM,u=t(\"../scatter/calc\").calcMarkerSize,f=t(\"../scatter/subtypes\"),h=t(\"./style\");e.exports={calcGeoJSON:function(t,e){var r,n,i=t[0].trace,o=e[i.geo],f=o._subplot,h=i._length;if(Array.isArray(i.locations)){var p=i.locationmode,d=\"geojson-id\"===p?s.extractTraceFeature(t):a(i,f.topojson);for(r=0;r<h;r++){n=t[r];var g=\"geojson-id\"===p?n.fOut:s.locationToFeature(p,n.loc,d);n.lonlat=g?g.properties.ct:[c,c]}}var m,v,y={padded:!0};if(\"geojson\"===o.fitbounds&&\"geojson-id\"===i.locationmode){var x=s.computeBbox(s.getTraceGeojson(i));m=[x[0],x[2]],v=[x[1],x[3]]}else{for(m=new Array(h),v=new 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s=o.calcTraceToLineCoords(e),c=\"none\"!==a.fill?o.makePolygon(s):o.makeLine(s);r.selectAll(\"path.js-line\").data([{geojson:c,trace:a}]).enter().append(\"path\").classed(\"js-line\",!0).style(\"stroke-miterlimit\",2)}f.hasMarkers(a)&&r.selectAll(\"path.point\").data(i.identity).enter().append(\"path\").classed(\"point\",!0).each((function(t){l(t,this)})),f.hasText(a)&&r.selectAll(\"g\").data(i.identity).enter().append(\"g\").append(\"text\").each((function(t){l(t,this)})),h(t,e)}))}}},{\"../../constants/numerical\":779,\"../../lib\":803,\"../../lib/geo_location_utils\":796,\"../../lib/geojson_utils\":797,\"../../lib/topojson_utils\":832,\"../../plots/cartesian/autorange\":853,\"../scatter/calc\":1219,\"../scatter/subtypes\":1243,\"./style\":1269,\"@plotly/d3\":58}],1268:[function(t,e,r){\"use strict\";var n=t(\"../scatter/subtypes\"),i=t(\"../../constants/numerical\").BADNUM;e.exports=function(t,e){var 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e=n.select(this),r=t.trace,o=r.line||{};e.call(a.stroke,o.color).call(i.dashLine,o.dash||\"\",o.width||0),\"none\"!==r.fill&&e.call(a.fill,r.fillcolor)}))}(t,e)}},{\"../../components/color\":666,\"../../components/drawing\":688,\"../scatter/style\":1242,\"@plotly/d3\":58}],1270:[function(t,e,r){\"use strict\";var n=t(\"../../plots/attributes\"),i=t(\"../scatter/attributes\"),a=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,o=t(\"../../components/colorscale/attributes\"),s=t(\"../../lib/sort_object_keys\"),l=t(\"../../lib/extend\").extendFlat,c=t(\"../../plot_api/edit_types\").overrideAll,u=t(\"./constants\").DASHES,f=i.line,h=i.marker,p=h.line,d=e.exports=c({x:i.x,x0:i.x0,dx:i.dx,y:i.y,y0:i.y0,dy:i.dy,xperiod:i.xperiod,yperiod:i.yperiod,xperiod0:i.xperiod0,yperiod0:i.yperiod0,xperiodalignment:i.xperiodalignment,yperiodalignment:i.yperiodalignment,xhoverformat:a(\"x\"),yhoverformat:a(\"y\"),text:i.text,hovertext:i.hovertext,textposition:i.textposition,textfont:i.textfont,mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\",\"text\"],extras:[\"none\"]},line:{color:f.color,width:f.width,shape:{valType:\"enumerated\",values:[\"linear\",\"hv\",\"vh\",\"hvh\",\"vhv\"],dflt:\"linear\",editType:\"plot\"},dash:{valType:\"enumerated\",values:s(u),dflt:\"solid\"}},marker:l({},o(\"marker\"),{symbol:h.symbol,size:h.size,sizeref:h.sizeref,sizemin:h.sizemin,sizemode:h.sizemode,opacity:h.opacity,colorbar:h.colorbar,line:l({},o(\"marker.line\"),{width:p.width})}),connectgaps:i.connectgaps,fill:l({},i.fill,{dflt:\"none\"}),fillcolor:i.fillcolor,selected:{marker:i.selected.marker,textfont:i.selected.textfont},unselected:{marker:i.unselected.marker,textfont:i.unselected.textfont},opacity:n.opacity},\"calc\",\"nested\");d.x.editType=d.y.editType=d.x0.editType=d.y0.editType=\"calc+clearAxisTypes\",d.hovertemplate=i.hovertemplate,d.texttemplate=i.texttemplate},{\"../../components/colorscale/attributes\":673,\"../../lib/extend\":793,\"../../lib/sort_object_keys\":826,\"../../plot_api/edit_types\":836,\"../../plots/attributes\":850,\"../../plots/cartesian/axis_format_attributes\":857,\"../scatter/attributes\":1218,\"./constants\":1272}],1271:[function(t,e,r){\"use 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T=y-_,k=y+w;p[v+u[0]]=x-i.c2l(T),p[v+u[1]]=i.c2l(k)-x,p[v+u[2]]=0,p[v+u[3]]=0,d=Math.min(d,y-_),g=Math.max(g,y+w)}}}h[a]={positions:r,errors:p,_bnds:[d,g]}}}return p(i,l),p(a,u),h},textPosition:function(t,e,r,n){var i,a=e._length,o={};if(f.hasMarkers(e)){var s=r.font,l=r.align,c=r.baseline;for(o.offset=new Array(a),i=0;i<a;i++){var u=n.sizes?n.sizes[i]:n.size,h=Array.isArray(s)?s[i].size:s.size,p=Array.isArray(l)?l.length>1?l[i]:l[0]:l,d=Array.isArray(c)?c.length>1?c[i]:c[0]:c,g=m[p],v=m[d],y=u?u/.8+1:0,x=-v*y-.5*v;o.offset[i]=[g*y/h,x/h]}}return o}}},{\"../../components/drawing\":688,\"../../components/fx/helpers\":702,\"../../constants/interactions\":778,\"../../lib\":803,\"../../lib/gl_format_color\":799,\"../../plots/cartesian/axis_ids\":858,\"../../registry\":931,\"../scatter/make_bubble_size_func\":1235,\"../scatter/subtypes\":1243,\"./constants\":1272,\"./helpers\":1277,\"color-normalize\":131,\"fast-isnumeric\":249,\"svg-path-sdf\":595}],1274:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../registry\"),a=t(\"./helpers\"),o=t(\"./attributes\"),s=t(\"../scatter/constants\"),l=t(\"../scatter/subtypes\"),c=t(\"../scatter/xy_defaults\"),u=t(\"../scatter/period_defaults\"),f=t(\"../scatter/marker_defaults\"),h=t(\"../scatter/line_defaults\"),p=t(\"../scatter/fillcolor_defaults\"),d=t(\"../scatter/text_defaults\");e.exports=function(t,e,r,g){function m(r,i){return n.coerce(t,e,o,r,i)}var v=!!t.marker&&a.isOpenSymbol(t.marker.symbol),y=l.isBubble(t),x=c(t,e,g,m);if(x){u(t,e,g,m),m(\"xhoverformat\"),m(\"yhoverformat\");var b=x<s.PTS_LINESONLY?\"lines+markers\":\"lines\";m(\"text\"),m(\"hovertext\"),m(\"hovertemplate\"),m(\"mode\",b),l.hasLines(e)&&(m(\"connectgaps\"),h(t,e,r,g,m),m(\"line.shape\")),l.hasMarkers(e)&&(f(t,e,r,g,m),m(\"marker.line.width\",v||y?1:0)),l.hasText(e)&&(m(\"texttemplate\"),d(t,e,g,m));var _=(e.line||{}).color,w=(e.marker||{}).color;m(\"fill\"),\"none\"!==e.fill&&p(t,e,r,m);var T=i.getComponentMethod(\"errorbars\",\"supplyDefaults\");T(t,e,_||w||r,{axis:\"y\"}),T(t,e,_||w||r,{axis:\"x\",inherit:\"y\"}),n.coerceSelectionMarkerOpacity(e,m)}else e.visible=!1}},{\"../../lib\":803,\"../../registry\":931,\"../scatter/constants\":1222,\"../scatter/fillcolor_defaults\":1226,\"../scatter/line_defaults\":1231,\"../scatter/marker_defaults\":1237,\"../scatter/period_defaults\":1238,\"../scatter/subtypes\":1243,\"../scatter/text_defaults\":1244,\"../scatter/xy_defaults\":1245,\"./attributes\":1270,\"./helpers\":1277}],1275:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/color\"),a=t(\"../../constants/interactions\").DESELECTDIM;e.exports={styleTextSelection:function(t){var e,r,o=t[0],s=o.trace,l=o.t,c=l._scene,u=l.index,f=c.selectBatch[u],h=c.unselectBatch[u],p=c.textOptions[u],d=c.textSelectedOptions[u]||{},g=c.textUnselectedOptions[u]||{},m=n.extendFlat({},p);if(f.length||h.length){var v=d.color,y=g.color,x=p.color,b=Array.isArray(x);for(m.color=new Array(s._length),e=0;e<f.length;e++)r=f[e],m.color[r]=v||(b?x[r]:x);for(e=0;e<h.length;e++){r=h[e];var _=b?x[r]:x;m.color[r]=y||(v?_:i.addOpacity(_,a))}}c.glText[u].update(m)}}},{\"../../components/color\":666,\"../../constants/interactions\":778,\"../../lib\":803}],1276:[function(t,e,r){\"use strict\";var n=t(\"../scatter/format_labels\");e.exports=function(t,e,r){var i=t.i;return\"x\"in t||(t.x=e._x[i]),\"y\"in t||(t.y=e._y[i]),n(t,e,r)}},{\"../scatter/format_labels\":1227}],1277:[function(t,e,r){\"use strict\";var n=t(\"./constants\");r.isOpenSymbol=function(t){return\"string\"==typeof t?n.OPEN_RE.test(t):t%200>100},r.isDotSymbol=function(t){return\"string\"==typeof t?n.DOT_RE.test(t):t>200}},{\"./constants\":1272}],1278:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../scatter/get_trace_color\");function o(t,e,r,o){var s=t.xa,l=t.ya,c=t.distance,u=t.dxy,f=t.index,h={pointNumber:f,x:e[f],y:r[f]};h.tx=Array.isArray(o.text)?o.text[f]:o.text,h.htx=Array.isArray(o.hovertext)?o.hovertext[f]:o.hovertext,h.data=Array.isArray(o.customdata)?o.customdata[f]:o.customdata,h.tp=Array.isArray(o.textposition)?o.textposition[f]:o.textposition;var p=o.textfont;p&&(h.ts=i.isArrayOrTypedArray(p.size)?p.size[f]:p.size,h.tc=Array.isArray(p.color)?p.color[f]:p.color,h.tf=Array.isArray(p.family)?p.family[f]:p.family);var d=o.marker;d&&(h.ms=i.isArrayOrTypedArray(d.size)?d.size[f]:d.size,h.mo=i.isArrayOrTypedArray(d.opacity)?d.opacity[f]:d.opacity,h.mx=i.isArrayOrTypedArray(d.symbol)?d.symbol[f]:d.symbol,h.mc=i.isArrayOrTypedArray(d.color)?d.color[f]:d.color);var g=d&&d.line;g&&(h.mlc=Array.isArray(g.color)?g.color[f]:g.color,h.mlw=i.isArrayOrTypedArray(g.width)?g.width[f]:g.width);var m=d&&d.gradient;m&&\"none\"!==m.type&&(h.mgt=Array.isArray(m.type)?m.type[f]:m.type,h.mgc=Array.isArray(m.color)?m.color[f]:m.color);var v=s.c2p(h.x,!0),y=l.c2p(h.y,!0),x=h.mrc||1,b=o.hoverlabel;b&&(h.hbg=Array.isArray(b.bgcolor)?b.bgcolor[f]:b.bgcolor,h.hbc=Array.isArray(b.bordercolor)?b.bordercolor[f]:b.bordercolor,h.hts=i.isArrayOrTypedArray(b.font.size)?b.font.size[f]:b.font.size,h.htc=Array.isArray(b.font.color)?b.font.color[f]:b.font.color,h.htf=Array.isArray(b.font.family)?b.font.family[f]:b.font.family,h.hnl=i.isArrayOrTypedArray(b.namelength)?b.namelength[f]:b.namelength);var _=o.hoverinfo;_&&(h.hi=Array.isArray(_)?_[f]:_);var w=o.hovertemplate;w&&(h.ht=Array.isArray(w)?w[f]:w);var T={};T[t.index]=h;var k=o._origX,A=o._origY,M=i.extendFlat({},t,{color:a(o,h),x0:v-x,x1:v+x,xLabelVal:k?k[f]:h.x,y0:y-x,y1:y+x,yLabelVal:A?A[f]:h.y,cd:T,distance:c,spikeDistance:u,hovertemplate:h.ht});return h.htx?M.text=h.htx:h.tx?M.text=h.tx:o.text&&(M.text=o.text),i.fillText(h,o,M),n.getComponentMethod(\"errorbars\",\"hoverInfo\")(h,o,M),M}e.exports={hoverPoints:function(t,e,r,n){var i,a,s,l,c,u,f,h,p,d,g=t.cd,m=g[0].t,v=g[0].trace,y=t.xa,x=t.ya,b=m.x,_=m.y,w=y.c2p(e),T=x.c2p(r),k=t.distance;if(m.tree){var A=y.p2c(w-k),M=y.p2c(w+k),S=x.p2c(T-k),E=x.p2c(T+k);i=\"x\"===n?m.tree.range(Math.min(A,M),Math.min(x._rl[0],x._rl[1]),Math.max(A,M),Math.max(x._rl[0],x._rl[1])):m.tree.range(Math.min(A,M),Math.min(S,E),Math.max(A,M),Math.max(S,E))}else i=m.ids;var L=k;if(\"x\"===n){var C=!!v.xperiodalignment,P=!!v.yperiodalignment;for(u=0;u<i.length;u++){if(l=b[a=i[u]],f=Math.abs(y.c2p(l)-w),C){var I=y.c2p(v._xStarts[a]),O=y.c2p(v._xEnds[a]);f=w>=Math.min(I,O)&&w<=Math.max(I,O)?0:1/0}if(f<L){if(L=f,c=_[a],h=x.c2p(c)-T,P){var z=x.c2p(v._yStarts[a]),D=x.c2p(v._yEnds[a]);h=T>=Math.min(z,D)&&T<=Math.max(z,D)?0:1/0}d=Math.sqrt(f*f+h*h),s=i[u]}}}else for(u=i.length-1;u>-1;u--)l=b[a=i[u]],c=_[a],f=y.c2p(l)-w,h=x.c2p(c)-T,(p=Math.sqrt(f*f+h*h))<L&&(L=d=p,s=a);return t.index=s,t.distance=L,t.dxy=d,void 0===s?[t]:[o(t,b,_,v)]},calcHover:o}},{\"../../lib\":803,\"../../registry\":931,\"../scatter/get_trace_color\":1228}],1279:[function(t,e,r){\"use strict\";var n=t(\"./hover\");e.exports={moduleType:\"trace\",name:\"scattergl\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"gl\",\"regl\",\"cartesian\",\"symbols\",\"errorBarsOK\",\"showLegend\",\"scatter-like\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"../scatter/cross_trace_defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),formatLabels:t(\"./format_labels\"),calc:t(\"./calc\"),plot:t(\"./plot\"),hoverPoints:n.hoverPoints,selectPoints:t(\"./select\"),meta:{}}},{\"../../plots/cartesian\":868,\"../scatter/cross_trace_defaults\":1224,\"../scatter/marker_colorbar\":1236,\"./attributes\":1270,\"./calc\":1271,\"./defaults\":1274,\"./format_labels\":1276,\"./hover\":1278,\"./plot\":1280,\"./select\":1282}],1280:[function(t,e,r){\"use strict\";var n=t(\"regl-scatter2d\"),i=t(\"regl-line2d\"),a=t(\"regl-error2d\"),o=t(\"gl-text\"),s=t(\"../../lib\"),l=t(\"../../components/dragelement/helpers\").selectMode,c=t(\"../../lib/prepare_regl\"),u=t(\"../scatter/subtypes\"),f=t(\"../scatter/link_traces\"),h=t(\"./edit_style\").styleTextSelection;function p(t,e,r,n){var i=t._size,a=t.width*n,o=t.height*n,s=i.l*n,l=i.b*n,c=i.r*n,u=i.t*n,f=i.w*n,h=i.h*n;return[s+e.domain[0]*f,l+r.domain[0]*h,a-c-(1-e.domain[1])*f,o-u-(1-r.domain[1])*h]}e.exports=function(t,e,r){if(r.length){var d,g,m=t._fullLayout,v=e._scene,y=e.xaxis,x=e.yaxis;if(v)if(c(t,[\"ANGLE_instanced_arrays\",\"OES_element_index_uint\"])){var b=v.count,_=m._glcanvas.data()[0].regl;if(f(t,e,r),v.dirty){if(!0===v.error2d&&(v.error2d=a(_)),!0===v.line2d&&(v.line2d=i(_)),!0===v.scatter2d&&(v.scatter2d=n(_)),!0===v.fill2d&&(v.fill2d=i(_)),!0===v.glText)for(v.glText=new Array(b),d=0;d<b;d++)v.glText[d]=new o(_);if(v.glText){if(b>v.glText.length){var w=b-v.glText.length;for(d=0;d<w;d++)v.glText.push(new o(_))}else if(b<v.glText.length){var T=v.glText.length-b;v.glText.splice(b,T).forEach((function(t){t.destroy()}))}for(d=0;d<b;d++)v.glText[d].update(v.textOptions[d])}if(v.line2d&&(v.line2d.update(v.lineOptions),v.lineOptions=v.lineOptions.map((function(t){if(t&&t.positions){for(var e=t.positions,r=0;r<e.length&&(isNaN(e[r])||isNaN(e[r+1]));)r+=2;for(var n=e.length-2;n>r&&(isNaN(e[n])||isNaN(e[n+1]));)n-=2;t.positions=e.slice(r,n+2)}return t})),v.line2d.update(v.lineOptions)),v.error2d){var k=(v.errorXOptions||[]).concat(v.errorYOptions||[]);v.error2d.update(k)}v.scatter2d&&v.scatter2d.update(v.markerOptions),v.fillOrder=s.repeat(null,b),v.fill2d&&(v.fillOptions=v.fillOptions.map((function(t,e){var n=r[e];if(t&&n&&n[0]&&n[0].trace){var i,a,o=n[0],s=o.trace,l=o.t,c=v.lineOptions[e],u=[];s._ownfill&&u.push(e),s._nexttrace&&u.push(e+1),u.length&&(v.fillOrder[e]=u);var f,h,p=[],d=c&&c.positions||l.positions;if(\"tozeroy\"===s.fill){for(f=0;f<d.length&&isNaN(d[f+1]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h+1]);)h-=2;0!==d[f+1]&&(p=[d[f],0]),p=p.concat(d.slice(f,h+2)),0!==d[h+1]&&(p=p.concat([d[h],0]))}else if(\"tozerox\"===s.fill){for(f=0;f<d.length&&isNaN(d[f]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h]);)h-=2;0!==d[f]&&(p=[0,d[f+1]]),p=p.concat(d.slice(f,h+2)),0!==d[h]&&(p=p.concat([0,d[h+1]]))}else if(\"toself\"===s.fill||\"tonext\"===s.fill){for(p=[],i=0,t.splitNull=!0,a=0;a<d.length;a+=2)(isNaN(d[a])||isNaN(d[a+1]))&&((p=p.concat(d.slice(i,a))).push(d[i],d[i+1]),p.push(null,null),i=a+2);p=p.concat(d.slice(i)),i&&p.push(d[i],d[i+1])}else{var g=s._nexttrace;if(g){var m=v.lineOptions[e+1];if(m){var y=m.positions;if(\"tonexty\"===s.fill){for(p=d.slice(),e=Math.floor(y.length/2);e--;){var x=y[2*e],b=y[2*e+1];isNaN(x)||isNaN(b)||p.push(x,b)}t.fill=g.fillcolor}}}}if(s._prevtrace&&\"tonext\"===s._prevtrace.fill){var _=v.lineOptions[e-1].positions,w=p.length/2,T=[i=w];for(a=0;a<_.length;a+=2)(isNaN(_[a])||isNaN(_[a+1]))&&(T.push(a/2+w+1),i=a+2);p=p.concat(_),t.hole=T}return t.fillmode=s.fill,t.opacity=s.opacity,t.positions=p,t}})),v.fill2d.update(v.fillOptions))}var A=m.dragmode,M=l(A),S=m.clickmode.indexOf(\"select\")>-1;for(d=0;d<b;d++){var E=r[d][0],L=E.trace,C=E.t,P=C.index,I=L._length,O=C.x,z=C.y;if(L.selectedpoints||M||S){if(M||(M=!0),L.selectedpoints){var D=v.selectBatch[P]=s.selIndices2selPoints(L),R={};for(g=0;g<D.length;g++)R[D[g]]=1;var F=[];for(g=0;g<I;g++)R[g]||F.push(g);v.unselectBatch[P]=F}var B=C.xpx=new Array(I),N=C.ypx=new Array(I);for(g=0;g<I;g++)B[g]=y.c2p(O[g]),N[g]=x.c2p(z[g])}else C.xpx=C.ypx=null}if(M){if(v.select2d||(v.select2d=n(m._glcanvas.data()[1].regl)),v.scatter2d){var j=new Array(b);for(d=0;d<b;d++)j[d]=v.selectBatch[d].length||v.unselectBatch[d].length?v.markerUnselectedOptions[d]:{};v.scatter2d.update(j)}v.select2d&&(v.select2d.update(v.markerOptions),v.select2d.update(v.markerSelectedOptions)),v.glText&&r.forEach((function(t){var e=((t||[])[0]||{}).trace||{};u.hasText(e)&&h(t)}))}else v.scatter2d&&v.scatter2d.update(v.markerOptions);var U={viewport:p(m,y,x,t._context.plotGlPixelRatio),range:[(y._rl||y.range)[0],(x._rl||x.range)[0],(y._rl||y.range)[1],(x._rl||x.range)[1]]},V=s.repeat(U,v.count);v.fill2d&&v.fill2d.update(V),v.line2d&&v.line2d.update(V),v.error2d&&v.error2d.update(V.concat(V)),v.scatter2d&&v.scatter2d.update(V),v.select2d&&v.select2d.update(V),v.glText&&v.glText.forEach((function(t){t.update(U)}))}else v.init()}}},{\"../../components/dragelement/helpers\":684,\"../../lib\":803,\"../../lib/prepare_regl\":816,\"../scatter/link_traces\":1234,\"../scatter/subtypes\":1243,\"./edit_style\":1275,\"gl-text\":355,\"regl-error2d\":536,\"regl-line2d\":537,\"regl-scatter2d\":538}],1281:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){var r=e._scene,i={count:0,dirty:!0,lineOptions:[],fillOptions:[],markerOptions:[],markerSelectedOptions:[],markerUnselectedOptions:[],errorXOptions:[],errorYOptions:[],textOptions:[],textSelectedOptions:[],textUnselectedOptions:[],selectBatch:[],unselectBatch:[]},a={fill2d:!1,scatter2d:!1,error2d:!1,line2d:!1,glText:!1,select2d:!1};return e._scene||((r=e._scene={}).init=function(){n.extendFlat(r,a,i)},r.init(),r.update=function(t){var e=n.repeat(t,r.count);if(r.fill2d&&r.fill2d.update(e),r.scatter2d&&r.scatter2d.update(e),r.line2d&&r.line2d.update(e),r.error2d&&r.error2d.update(e.concat(e)),r.select2d&&r.select2d.update(e),r.glText)for(var i=0;i<r.count;i++)r.glText[i].update(t)},r.draw=function(){for(var t=r.count,e=r.fill2d,i=r.error2d,a=r.line2d,o=r.scatter2d,s=r.glText,l=r.select2d,c=r.selectBatch,u=r.unselectBatch,f=0;f<t;f++){if(e&&r.fillOrder[f]&&e.draw(r.fillOrder[f]),a&&r.lineOptions[f]&&a.draw(f),i&&(r.errorXOptions[f]&&i.draw(f),r.errorYOptions[f]&&i.draw(f+t)),o&&r.markerOptions[f])if(u[f].length){var h=n.repeat([],r.count);h[f]=u[f],o.draw(h)}else c[f].length||o.draw(f);s[f]&&r.textOptions[f]&&s[f].render()}l&&l.draw(c),r.dirty=!1},r.destroy=function(){r.fill2d&&r.fill2d.destroy&&r.fill2d.destroy(),r.scatter2d&&r.scatter2d.destroy&&r.scatter2d.destroy(),r.error2d&&r.error2d.destroy&&r.error2d.destroy(),r.line2d&&r.line2d.destroy&&r.line2d.destroy(),r.select2d&&r.select2d.destroy&&r.select2d.destroy(),r.glText&&r.glText.forEach((function(t){t.destroy&&t.destroy()})),r.lineOptions=null,r.fillOptions=null,r.markerOptions=null,r.markerSelectedOptions=null,r.markerUnselectedOptions=null,r.errorXOptions=null,r.errorYOptions=null,r.textOptions=null,r.textSelectedOptions=null,r.textUnselectedOptions=null,r.selectBatch=null,r.unselectBatch=null,e._scene=null}),r.dirty||n.extendFlat(r,i),r}},{\"../../lib\":803}],1282:[function(t,e,r){\"use strict\";var n=t(\"../scatter/subtypes\"),i=t(\"./edit_style\").styleTextSelection;e.exports=function(t,e){var r=t.cd,a=t.xaxis,o=t.yaxis,s=[],l=r[0].trace,c=r[0].t,u=l._length,f=c.x,h=c.y,p=c._scene,d=c.index;if(!p)return s;var g=n.hasText(l),m=n.hasMarkers(l),v=!m&&!g;if(!0!==l.visible||v)return s;var y=[],x=[];if(!1!==e&&!e.degenerate)for(var b=0;b<u;b++)e.contains([c.xpx[b],c.ypx[b]],!1,b,t)?(y.push(b),s.push({pointNumber:b,x:a.c2d(f[b]),y:o.c2d(h[b])})):x.push(b);if(m){var _=p.scatter2d;if(y.length||x.length){if(!p.selectBatch[d].length&&!p.unselectBatch[d].length){var w=new Array(p.count);w[d]=p.markerUnselectedOptions[d],_.update.apply(_,w)}}else{var T=new Array(p.count);T[d]=p.markerOptions[d],_.update.apply(_,T)}}return p.selectBatch[d]=y,p.unselectBatch[d]=x,g&&i(r),s}},{\"../scatter/subtypes\":1243,\"./edit_style\":1275}],1283:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../scattergeo/attributes\"),o=t(\"../scatter/attributes\"),s=t(\"../../plots/mapbox/layout_attributes\"),l=t(\"../../plots/attributes\"),c=t(\"../../components/colorscale/attributes\"),u=t(\"../../lib/extend\").extendFlat,f=t(\"../../plot_api/edit_types\").overrideAll,h=a.line,p=a.marker;e.exports=f({lon:a.lon,lat:a.lat,mode:u({},o.mode,{dflt:\"markers\"}),text:u({},o.text,{}),texttemplate:i({editType:\"plot\"},{keys:[\"lat\",\"lon\",\"text\"]}),hovertext:u({},o.hovertext,{}),line:{color:h.color,width:h.width},connectgaps:o.connectgaps,marker:u({symbol:{valType:\"string\",dflt:\"circle\",arrayOk:!0},angle:{valType:\"number\",dflt:\"auto\",arrayOk:!0},allowoverlap:{valType:\"boolean\",dflt:!1},opacity:p.opacity,size:p.size,sizeref:p.sizeref,sizemin:p.sizemin,sizemode:p.sizemode},c(\"marker\")),fill:a.fill,fillcolor:o.fillcolor,textfont:s.layers.symbol.textfont,textposition:s.layers.symbol.textposition,below:{valType:\"string\"},selected:{marker:o.selected.marker},unselected:{marker:o.unselected.marker},hoverinfo:u({},l.hoverinfo,{flags:[\"lon\",\"lat\",\"text\",\"name\"]}),hovertemplate:n()},\"calc\",\"nested\")},{\"../../components/colorscale/attributes\":673,\"../../lib/extend\":793,\"../../plot_api/edit_types\":836,\"../../plots/attributes\":850,\"../../plots/mapbox/layout_attributes\":913,\"../../plots/template_attributes\":926,\"../scatter/attributes\":1218,\"../scattergeo/attributes\":1260}],1284:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"../../constants/numerical\").BADNUM,o=t(\"../../lib/geojson_utils\"),s=t(\"../../components/colorscale\"),l=t(\"../../components/drawing\"),c=t(\"../scatter/make_bubble_size_func\"),u=t(\"../scatter/subtypes\"),f=t(\"../../plots/mapbox/convert_text_opts\"),h=t(\"../../components/fx/helpers\").appendArrayPointValue,p=t(\"../../lib/svg_text_utils\").NEWLINES,d=t(\"../../lib/svg_text_utils\").BR_TAG_ALL;function g(){return{geojson:o.makeBlank(),layout:{visibility:\"none\"},paint:{}}}function m(t,e){return i.isArrayOrTypedArray(t)?e?function(e){return n(t[e])?+t[e]:0}:function(e){return t[e]}:t?function(){return t}:v}function v(){return\"\"}function y(t){return t[0]===a}e.exports=function(t,e){var r,a=e[0].trace,x=!0===a.visible&&0!==a._length,b=\"none\"!==a.fill,_=u.hasLines(a),w=u.hasMarkers(a),T=u.hasText(a),k=w&&\"circle\"===a.marker.symbol,A=w&&\"circle\"!==a.marker.symbol,M=g(),S=g(),E=g(),L=g(),C={fill:M,line:S,circle:E,symbol:L};if(!x)return C;if((b||_)&&(r=o.calcTraceToLineCoords(e)),b&&(M.geojson=o.makePolygon(r),M.layout.visibility=\"visible\",i.extendFlat(M.paint,{\"fill-color\":a.fillcolor})),_&&(S.geojson=o.makeLine(r),S.layout.visibility=\"visible\",i.extendFlat(S.paint,{\"line-width\":a.line.width,\"line-color\":a.line.color,\"line-opacity\":a.opacity})),k){var P=function(t){var e,r,a,o,u=t[0].trace,f=u.marker,h=u.selectedpoints,p=i.isArrayOrTypedArray(f.color),d=i.isArrayOrTypedArray(f.size),g=i.isArrayOrTypedArray(f.opacity);function m(t){return u.opacity*t}p&&(r=s.hasColorscale(u,\"marker\")?s.makeColorScaleFuncFromTrace(f):i.identity);d&&(a=c(u));g&&(o=function(t){return m(n(t)?+i.constrain(t,0,1):0)});var v,x=[];for(e=0;e<t.length;e++){var b=t[e],_=b.lonlat;if(!y(_)){var w={};r&&(w.mcc=b.mcc=r(b.mc)),a&&(w.mrc=b.mrc=a(b.ms)),o&&(w.mo=o(b.mo)),h&&(w.selected=b.selected||0),x.push({type:\"Feature\",geometry:{type:\"Point\",coordinates:_},properties:w})}}if(h)for(v=l.makeSelectedPointStyleFns(u),e=0;e<x.length;e++){var T=x[e].properties;v.selectedOpacityFn&&(T.mo=m(v.selectedOpacityFn(T))),v.selectedColorFn&&(T.mcc=v.selectedColorFn(T)),v.selectedSizeFn&&(T.mrc=v.selectedSizeFn(T))}return{geojson:{type:\"FeatureCollection\",features:x},mcc:p||v&&v.selectedColorFn?{type:\"identity\",property:\"mcc\"}:f.color,mrc:d||v&&v.selectedSizeFn?{type:\"identity\",property:\"mrc\"}:(k=f.size,k/2),mo:g||v&&v.selectedOpacityFn?{type:\"identity\",property:\"mo\"}:m(f.opacity)};var k}(e);E.geojson=P.geojson,E.layout.visibility=\"visible\",i.extendFlat(E.paint,{\"circle-color\":P.mcc,\"circle-radius\":P.mrc,\"circle-opacity\":P.mo})}if((A||T)&&(L.geojson=function(t,e){for(var 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n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/line_shape_defaults\"),l=t(\"../scatter/text_defaults\"),c=t(\"../scatter/fillcolor_defaults\"),u=t(\"../scatter/constants\").PTS_LINESONLY,f=t(\"./attributes\");function h(t,e,r,n){var i,a=n(\"r\"),o=n(\"theta\");if(a)o?i=Math.min(a.length,o.length):(i=a.length,n(\"theta0\"),n(\"dtheta\"));else{if(!o)return 0;i=e.theta.length,n(\"r0\"),n(\"dr\")}return e._length=i,i}e.exports={handleRThetaDefaults:h,supplyDefaults:function(t,e,r,p){function d(r,i){return n.coerce(t,e,f,r,i)}var g=h(t,e,p,d);if(g){d(\"thetaunit\"),d(\"mode\",g<u?\"lines+markers\":\"lines\"),d(\"text\"),d(\"hovertext\"),\"fills\"!==e.hoveron&&d(\"hovertemplate\"),i.hasLines(e)&&(o(t,e,r,p,d),s(t,e,d),d(\"connectgaps\")),i.hasMarkers(e)&&a(t,e,r,p,d,{gradient:!0}),i.hasText(e)&&(d(\"texttemplate\"),l(t,e,p,d));var 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e,r,i,a,s,l,c,u,f,h,p,d,g=t._x,m=t._y,v=t._z,y=t._len,x=-1/0,b=1/0,_=-1/0,w=1/0,T=-1/0,k=1/0,A=\"\";for(y&&(c=g[0],f=m[0],p=v[0]),y>1&&(u=g[y-1],h=m[y-1],d=v[y-1]),e=0;e<y;e++)x=Math.max(x,g[e]),b=Math.min(b,g[e]),_=Math.max(_,m[e]),w=Math.min(w,m[e]),T=Math.max(T,v[e]),k=Math.min(k,v[e]),a||g[e]===c||(a=!0,A+=\"x\"),s||m[e]===f||(s=!0,A+=\"y\"),l||v[e]===p||(l=!0,A+=\"z\");a||(A+=\"x\"),s||(A+=\"y\"),l||(A+=\"z\");var M=o(t._x),S=o(t._y),E=o(t._z);A=(A=(A=A.replace(\"x\",(c>u?\"-\":\"+\")+\"x\")).replace(\"y\",(f>h?\"-\":\"+\")+\"y\")).replace(\"z\",(p>d?\"-\":\"+\")+\"z\");var L=function(){y=0,M=[],S=[],E=[]};(!y||y<M.length*S.length*E.length)&&L();var C=function(t){return\"x\"===t?g:\"y\"===t?m:v},P=function(t){return\"x\"===t?M:\"y\"===t?S:E},I=function(t){return t[y-1]<t[0]?-1:1},O=C(A[1]),z=C(A[3]),D=C(A[5]),R=P(A[1]).length,F=P(A[3]).length,B=P(A[5]).length,N=!1,j=function(t,e,r){return 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0},{\"../../components/color\":666,\"../../components/colorscale/attributes\":673,\"../../lib/extend\":793,\"../../plot_api/edit_types\":836,\"../../plots/attributes\":850,\"../../plots/cartesian/axis_format_attributes\":857,\"../../plots/template_attributes\":926}],1343:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":674}],1344:[function(t,e,r){\"use strict\";var n=t(\"gl-surface3d\"),i=t(\"ndarray\"),a=t(\"ndarray-linear-interpolate\").d2,o=t(\"../heatmap/interp2d\"),s=t(\"../heatmap/find_empties\"),l=t(\"../../lib\").isArrayOrTypedArray,c=t(\"../../lib/gl_format_color\").parseColorScale,u=t(\"../../lib/str2rgbarray\"),f=t(\"../../components/colorscale\").extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?i:n.d2l(i,0,r)},p.getZat=function(t,e,r,n){var i=this.data.z[e][t];return null===i&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[e][t]),void 0===r?i:n.d2l(i,0,r)},p.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,i],t.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],t.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){var o=t.dataCoordinate[a];null!=o&&(t.dataCoordinate[a]*=this.scene.dataScale[a])}var s=this.data.hovertext||this.data.text;return Array.isArray(s)&&s[i]&&void 0!==s[i][n]?t.textLabel=s[i][n]:t.textLabel=s||\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var 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g(t,e){if(t<e)return 0;for(var r=0;0===Math.floor(t%e);)t/=e,r++;return r}function m(t){for(var e=[],r=0;r<d.length;r++){var n=d[r];e.push(g(t,n))}return e}function v(t){for(var e=m(t),r=t,n=0;n<d.length;n++)if(e[n]>0){r=d[n];break}return r}function y(t,e){if(!(t<1||e<1)){for(var r=m(t),n=m(e),i=1,a=0;a<d.length;a++)i*=Math.pow(d[a],Math.max(r[a],n[a]));return i}}p.calcXnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getXat(e-1,0),i=this.getXat(e,0);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r},p.calcYnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getYat(0,e-1),i=this.getYat(0,e);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r};var x=[1,2,4,6,12,24,36,48,60,120,180,240,360,720,840,1260],b=x[9],_=x[13];function w(t,e,r){var n=r[8]+r[2]*e[0]+r[5]*e[1];return t[0]=(r[6]+r[0]*e[0]+r[3]*e[1])/n,t[1]=(r[7]+r[1]*e[0]+r[4]*e[1])/n,t}function T(t,e,r){return function(t,e,r,n){for(var i=[0,0],o=t.shape[0],s=t.shape[1],l=0;l<o;l++)for(var c=0;c<s;c++)r(i,[l,c],n),t.set(l,c,a(e,i[0],i[1]))}(t,e,w,r),t}function k(t,e){for(var r=!1,n=0;n<t.length;n++)if(e===t[n]){r=!0;break}!1===r&&t.push(e)}p.estimateScale=function(t,e){for(var r=1+function(t){if(0!==t.length){for(var e=1,r=0;r<t.length;r++)e=y(e,t[r]);return e}}(0===e?this.calcXnums(t):this.calcYnums(t));r<b;)r*=2;for(;r>_;)r--,r/=v(r),++r<b&&(r=_);var n=Math.round(r/t);return n>1?n:1},p.refineCoords=function(t){for(var e=this.dataScaleX,r=this.dataScaleY,n=t[0].shape[0],a=t[0].shape[1],o=0|Math.floor(t[0].shape[0]*e+1),s=0|Math.floor(t[0].shape[1]*r+1),l=1+n+1,c=1+a+1,u=i(new Float32Array(l*c),[l,c]),f=[1/e,0,0,0,1/r,0,0,0,1],h=0;h<t.length;++h){this.surface.padField(u,t[h]);var p=i(new Float32Array(o*s),[o,s]);T(p,u,f),t[h]=p}},p.setContourLevels=function(){var t,e,r,n=[[],[],[]],i=[!1,!1,!1],a=!1;for(t=0;t<3;++t)if(this.showContour[t]&&(a=!0,this.contourSize[t]>0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(i[t]=!0,e=this.contourStart[t];e<this.contourEnd[t];e+=this.contourSize[t])r=e*this.scene.dataScale[t],k(n[t],r);if(a){var o=[[],[],[]];for(t=0;t<3;++t)this.showContour[t]&&(o[t]=i[t]?n[t]:this.scene.contourLevels[t]);this.surface.update({levels:o})}},p.update=function(t){var e,r,n,a,l=this.scene,h=l.fullSceneLayout,p=this.surface,d=c(t),g=l.dataScale,m=t.z[0].length,v=t._ylength,y=l.contourLevels;this.data=t;var x=[];for(e=0;e<3;e++)for(x[e]=[],r=0;r<m;r++)x[e][r]=[];for(r=0;r<m;r++)for(n=0;n<v;n++)x[0][r][n]=this.getXat(r,n,t.xcalendar,h.xaxis),x[1][r][n]=this.getYat(r,n,t.ycalendar,h.yaxis),x[2][r][n]=this.getZat(r,n,t.zcalendar,h.zaxis);if(t.connectgaps)for(t._emptypoints=s(x[2]),o(x[2],t._emptypoints),t._interpolatedZ=[],r=0;r<m;r++)for(t._interpolatedZ[r]=[],n=0;n<v;n++)t._interpolatedZ[r][n]=x[2][r][n];for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)null==(a=x[e][r][n])?x[e][r][n]=NaN:a=x[e][r][n]*=g[e];for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(this.minValues[e]>a&&(this.minValues[e]=a),this.maxValues[e]<a&&(this.maxValues[e]=a));for(e=0;e<3;e++)this.objectOffset[e]=.5*(this.minValues[e]+this.maxValues[e]);for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(x[e][r][n]-=this.objectOffset[e]);var b=[i(new Float32Array(m*v),[m,v]),i(new Float32Array(m*v),[m,v]),i(new Float32Array(m*v),[m,v])];for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)b[e].set(r,n,x[e][r][n]);x=[];var w={colormap:d,levels:[[],[],[]],showContour:[!0,!0,!0],showSurface:!t.hidesurface,contourProject:[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],contourWidth:[1,1,1],contourColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],contourTint:[1,1,1],dynamicColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],dynamicWidth:[1,1,1],dynamicTint:[1,1,1],opacityscale:t.opacityscale,opacity:t.opacity},T=f(t);if(w.intensityBounds=[T.min,T.max],t.surfacecolor){var k=i(new Float32Array(m*v),[m,v]);for(r=0;r<m;r++)for(n=0;n<v;n++)k.set(r,n,t.surfacecolor[n][r]);b.push(k)}else w.intensityBounds[0]*=g[2],w.intensityBounds[1]*=g[2];(_<b[0].shape[0]||_<b[0].shape[1])&&(this.refineData=!1),!0===this.refineData&&(this.dataScaleX=this.estimateScale(b[0].shape[0],0),this.dataScaleY=this.estimateScale(b[0].shape[1],1),1===this.dataScaleX&&1===this.dataScaleY||this.refineCoords(b)),t.surfacecolor&&(w.intensity=b.pop());var A=[!0,!0,!0],M=[\"x\",\"y\",\"z\"];for(e=0;e<3;++e){var S=t.contours[M[e]];A[e]=S.highlight,w.showContour[e]=S.show||S.highlight,w.showContour[e]&&(w.contourProject[e]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[e]=!0,w.levels[e]=y[e],p.highlightColor[e]=w.contourColor[e]=u(S.color),S.usecolormap?p.highlightTint[e]=w.contourTint[e]=0:p.highlightTint[e]=w.contourTint[e]=1,w.contourWidth[e]=S.width,this.contourStart[e]=S.start,this.contourEnd[e]=S.end,this.contourSize[e]=S.size):(this.showContour[e]=!1,this.contourStart[e]=null,this.contourEnd[e]=null,this.contourSize[e]=0),S.highlight&&(w.dynamicColor[e]=u(S.highlightcolor),w.dynamicWidth[e]=S.highlightwidth))}(function(t){var e=t[0].rgb,r=t[t.length-1].rgb;return e[0]===r[0]&&e[1]===r[1]&&e[2]===r[2]&&e[3]===r[3]})(d)&&(w.vertexColor=!0),w.objectOffset=this.objectOffset,w.coords=b,p.update(w),p.visible=t.visible,p.enableDynamic=A,p.enableHighlight=A,p.snapToData=!0,\"lighting\"in 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i=n(\"opacityscale\");\"max\"===i?e.opacityscale=[[0,.1],[1,1]]:\"min\"===i?e.opacityscale=[[0,1],[1,.1]]:\"extremes\"===i?e.opacityscale=function(t,e){for(var r=[],n=0;n<32;n++){var i=n/31,a=e+(1-e)*(1-Math.pow(Math.sin(t*i*Math.PI),2));r.push([i,Math.max(0,Math.min(1,a))])}return r}(1,.1):function(t){var e=0;if(!Array.isArray(t)||t.length<2)return!1;if(!t[0]||!t[t.length-1])return!1;if(0!=+t[0][0]||1!=+t[t.length-1][0])return!1;for(var r=0;r<t.length;r++){var n=t[r];if(2!==n.length||+n[0]<e)return!1;e=+n[0]}return!0}(i)||(e.opacityscale=void 0)}function l(t,e,r){e in t&&!(r in t)&&(t[r]=t[e])}e.exports={supplyDefaults:function(t,e,r,c){var u,f;function h(r,n){return i.coerce(t,e,o,r,n)}var 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n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../../components/colorscale/attributes\"),o=t(\"../../plots/domain\").attributes,s=t(\"../pie/attributes\"),l=t(\"../sunburst/attributes\"),c=t(\"./constants\"),u=t(\"../../lib/extend\").extendFlat;e.exports={labels:l.labels,parents:l.parents,values:l.values,branchvalues:l.branchvalues,count:l.count,level:l.level,maxdepth:l.maxdepth,tiling:{packing:{valType:\"enumerated\",values:[\"squarify\",\"binary\",\"dice\",\"slice\",\"slice-dice\",\"dice-slice\"],dflt:\"squarify\",editType:\"plot\"},squarifyratio:{valType:\"number\",min:1,dflt:1,editType:\"plot\"},flip:{valType:\"flaglist\",flags:[\"x\",\"y\"],dflt:\"\",editType:\"plot\"},pad:{valType:\"number\",min:0,dflt:3,editType:\"plot\"},editType:\"calc\"},marker:u({pad:{t:{valType:\"number\",min:0,editType:\"plot\"},l:{valType:\"number\",min:0,editType:\"plot\"},r:{valType:\"number\",min:0,editType:\"plot\"},b:{valType:\"number\",min:0,editType:\"plot\"},editType:\"calc\"},colors:l.marker.colors,depthfade:{valType:\"enumerated\",values:[!0,!1,\"reversed\"],editType:\"style\"},line:l.marker.line,editType:\"calc\"},a(\"marker\",{colorAttr:\"colors\",anim:!1})),pathbar:{visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},side:{valType:\"enumerated\",values:[\"top\",\"bottom\"],dflt:\"top\",editType:\"plot\"},edgeshape:{valType:\"enumerated\",values:[\">\",\"<\",\"|\",\"/\",\"\\\\\"],dflt:\">\",editType:\"plot\"},thickness:{valType:\"number\",min:12,editType:\"plot\"},textfont:u({},s.textfont,{}),editType:\"calc\"},text:s.text,textinfo:l.textinfo,texttemplate:i({editType:\"plot\"},{keys:c.eventDataKeys.concat([\"label\",\"value\"])}),hovertext:s.hovertext,hoverinfo:l.hoverinfo,hovertemplate:n({},{keys:c.eventDataKeys}),textfont:s.textfont,insidetextfont:s.insidetextfont,outsidetextfont:u({},s.outsidetextfont,{}),textposition:{valType:\"enumerated\",values:[\"top 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h=n.select(this),p=i.ensureSingle(h,\"path\",\"surface\",(function(t){t.style(\"pointer-events\",\"all\")}));w?p.transition().attrTween(\"d\",(function(t){var e=k(t,!0,M,[g,m]);return function(t){return x(e(t))}})):p.attr(\"d\",x),h.call(f,r,t,e,{styleOne:l,eventDataKeys:c.eventDataKeys,transitionTime:c.CLICK_TRANSITION_TIME,transitionEasing:c.CLICK_TRANSITION_EASING}).call(u.setSliceCursor,t,{hideOnRoot:!1,hideOnLeaves:!1,isTransitioning:t._transitioning}),p.call(l,s,L,{hovered:!1}),s._text=(u.getPtLabel(s)||\"\").split(\"<br>\").join(\" \")||\"\";var d=i.ensureSingle(h,\"g\",\"slicetext\"),T=i.ensureSingle(d,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),E=i.ensureUniformFontSize(t,u.determineTextFont(L,s,S.font,{onPathbar:!0}));T.text(s._text||\" 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g=d.width,m=d.height,v=d.viewX,y=d.viewY,x=d.pathSlice,b=d.toMoveInsideSlice,_=d.strTransform,w=d.hasTransition,T=d.handleSlicesExit,k=d.makeUpdateSliceInterpolator,A=d.makeUpdateTextInterpolator,M=d.prevEntry,S=t._fullLayout,E=e[0].trace,L=-1!==E.textposition.indexOf(\"left\"),C=-1!==E.textposition.indexOf(\"right\"),P=-1!==E.textposition.indexOf(\"bottom\"),I=!P&&!E.marker.pad.t||P&&!E.marker.pad.b,O=s(r,[g,m],{packing:E.tiling.packing,squarifyratio:E.tiling.squarifyratio,flipX:E.tiling.flip.indexOf(\"x\")>-1,flipY:E.tiling.flip.indexOf(\"y\")>-1,pad:{inner:E.tiling.pad,top:E.marker.pad.t,left:E.marker.pad.l,right:E.marker.pad.r,bottom:E.marker.pad.b}}).descendants(),z=1/0,D=-1/0;O.forEach((function(t){var e=t.depth;e>=E._maxDepth?(t.x0=t.x1=(t.x0+t.x1)/2,t.y0=t.y1=(t.y0+t.y1)/2):(z=Math.min(z,e),D=Math.max(D,e))})),p=p.data(O,u.getPtId),E._maxVisibleLayers=isFinite(D)?D-z+1:0,p.enter().append(\"g\").classed(\"slice\",!0),T(p,!1,{},[g,m],x),p.order();var R=null;if(w&&M){var 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of individuals by Hours of work in the income category  \"},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"age\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Hours\"}}},                        {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('68caa452-b598-44c4-9cc4-bc09c5874e29');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data=df.groupby(['age','income']).apply(lambda x:x['hours.per.week'].count()).reset_index(name='Hours')\n",
+    "px.line(data,x='age',y='Hours',color='income',title='age of individuals by Hours of work in the income category  ')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "People earning <=50k tend to work for high no. of hours at a young age and the no. of hours decreases as the age increases but still they work for more no. of hours even at a later age as compared to people earning >50K"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:55.329131Z",
+     "iopub.status.busy": "2021-07-05T16:35:55.328782Z",
+     "iopub.status.idle": "2021-07-05T16:35:55.863048Z",
+     "shell.execute_reply": "2021-07-05T16:35:55.862084Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:55.329098Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Average age')"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(6,8))\n",
+    "sns.barplot(x='income',y='age',hue='sex',data=df)\n",
+    "plt.ylabel('Average age')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As the age increases  people are paid more but males are paid more than females."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:56.699110Z",
+     "iopub.status.busy": "2021-07-05T16:35:56.698698Z",
+     "iopub.status.idle": "2021-07-05T16:35:57.757925Z",
+     "shell.execute_reply": "2021-07-05T16:35:57.757022Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:56.699075Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([0, 1, 2, 3, 4, 5, 6, 7, 8]),\n",
+       " [Text(0, 0, '?'),\n",
+       "  Text(1, 0, 'Private'),\n",
+       "  Text(2, 0, 'State-gov'),\n",
+       "  Text(3, 0, 'Federal-gov'),\n",
+       "  Text(4, 0, 'Self-emp-not-inc'),\n",
+       "  Text(5, 0, 'Self-emp-inc'),\n",
+       "  Text(6, 0, 'Local-gov'),\n",
+       "  Text(7, 0, 'Without-pay'),\n",
+       "  Text(8, 0, 'Never-worked')])"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 431.75x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.factorplot(x='workclass',y='education.num',hue='income',data=df)\n",
+    "plt.xticks(rotation=90)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Some people belonging to a particular workclass might have less education and some workclass might require more education level, but no matter whatever workclass, people in the same workclass, if they have higher education level they earn more. It is also to be noticed that there is no person from without pay and never worked workclass category who earn more than 50k which is logical."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:57.759460Z",
+     "iopub.status.busy": "2021-07-05T16:35:57.759213Z",
+     "iopub.status.idle": "2021-07-05T16:35:58.453812Z",
+     "shell.execute_reply": "2021-07-05T16:35:58.452815Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:57.759436Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([0, 1]), [Text(0, 0, 'Female'), Text(1, 0, 'Male')])"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 431.75x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.factorplot(x='sex',y='education.num',hue='income',data=df)\n",
+    "plt.xticks(rotation=90)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Females with higher education level earn equal to men having less education level than them irrespective of any income category they fall."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:58.456052Z",
+     "iopub.status.busy": "2021-07-05T16:35:58.455657Z",
+     "iopub.status.idle": "2021-07-05T16:35:59.403398Z",
+     "shell.execute_reply": "2021-07-05T16:35:59.402704Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:58.456003Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([0, 1, 2, 3, 4]),\n",
+       " [Text(0, 0, 'White'),\n",
+       "  Text(1, 0, 'Black'),\n",
+       "  Text(2, 0, 'Asian-Pac-Islander'),\n",
+       "  Text(3, 0, 'Other'),\n",
+       "  Text(4, 0, 'Amer-Indian-Eskimo')])"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 431.75x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.factorplot(x='race',y='education.num',hue='income',data=df)\n",
+    "plt.xticks(rotation=90)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Asian pacific race have comparatively more education than the fellows who earn same as much as they do, belonging to other races. Indians and some other races earn >50k with lowest education level."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:59.405433Z",
+     "iopub.status.busy": "2021-07-05T16:35:59.404914Z",
+     "iopub.status.idle": "2021-07-05T16:36:00.894668Z",
+     "shell.execute_reply": "2021-07-05T16:36:00.893676Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:59.405390Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14]),\n",
+       " [Text(0, 0, '?'),\n",
+       "  Text(1, 0, 'Exec-managerial'),\n",
+       "  Text(2, 0, 'Machine-op-inspct'),\n",
+       "  Text(3, 0, 'Prof-specialty'),\n",
+       "  Text(4, 0, 'Other-service'),\n",
+       "  Text(5, 0, 'Adm-clerical'),\n",
+       "  Text(6, 0, 'Craft-repair'),\n",
+       "  Text(7, 0, 'Transport-moving'),\n",
+       "  Text(8, 0, 'Handlers-cleaners'),\n",
+       "  Text(9, 0, 'Sales'),\n",
+       "  Text(10, 0, 'Farming-fishing'),\n",
+       "  Text(11, 0, 'Tech-support'),\n",
+       "  Text(12, 0, 'Protective-serv'),\n",
+       "  Text(13, 0, 'Armed-Forces'),\n",
+       "  Text(14, 0, 'Priv-house-serv')])"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 431.75x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.factorplot(x='occupation',y='education.num',hue='income',data=df)\n",
+    "plt.xticks(rotation=90)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "People with highest education level belong to armed forces, but people with even education level quite low, who belong to handlers cleaners, transport moving  occupation earn as much as they do. Same is the case with prof speciality. occupation of private house service who earn >50k and <50k have the highest education level difference while prof speciality have the minimum difference."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:00.896444Z",
+     "iopub.status.busy": "2021-07-05T16:36:00.896098Z",
+     "iopub.status.idle": "2021-07-05T16:36:02.554348Z",
+     "shell.execute_reply": "2021-07-05T16:36:02.553448Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:00.896407Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='age', ylabel='hours.per.week'>"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,8))\n",
+    "sns.scatterplot(x='age',y='hours.per.week',hue='income',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From the scatterplot between age, hours.per.week and income, we observe that a person needs to be >30 to be earning more than 50K, else needs to work at least 60 hours.per.week to earn >50K."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:02.556715Z",
+     "iopub.status.busy": "2021-07-05T16:36:02.556370Z",
+     "iopub.status.idle": "2021-07-05T16:36:02.930266Z",
+     "shell.execute_reply": "2021-07-05T16:36:02.929319Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:02.556679Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:>"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10,10))\n",
+    "sns.heatmap(df.corr(),annot=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are only few features in the above heat map as most of them are of object type. From here we can see that the independent features don not have much correlation with each other i.e. no multicollinearity."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Feature Engineering"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "###### Encoding"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:05.819458Z",
+     "iopub.status.busy": "2021-07-05T16:36:05.818924Z",
+     "iopub.status.idle": "2021-07-05T16:36:05.950297Z",
+     "shell.execute_reply": "2021-07-05T16:36:05.949585Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:05.819423Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.preprocessing import LabelEncoder, OrdinalEncoder\n",
+    "l=LabelEncoder()\n",
+    "o=OrdinalEncoder()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:07.019232Z",
+     "iopub.status.busy": "2021-07-05T16:36:07.018688Z",
+     "iopub.status.idle": "2021-07-05T16:36:07.094492Z",
+     "shell.execute_reply": "2021-07-05T16:36:07.093829Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:07.019197Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#We use ordinal encoder to Encode Independent features\n",
+    "for i in df.columns:\n",
+    "    if df[i].dtypes=='O' and i!='income':\n",
+    "        df[i]=o.fit_transform(df[i].values.reshape(-1,1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:07.529008Z",
+     "iopub.status.busy": "2021-07-05T16:36:07.528484Z",
+     "iopub.status.idle": "2021-07-05T16:36:07.539388Z",
+     "shell.execute_reply": "2021-07-05T16:36:07.538415Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:07.528975Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#We use label encoder to encode label \n",
+    "df['income']=l.fit_transform(df['income'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Removing Outliers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:10.608324Z",
+     "iopub.status.busy": "2021-07-05T16:36:10.607889Z",
+     "iopub.status.idle": "2021-07-05T16:36:10.611663Z",
+     "shell.execute_reply": "2021-07-05T16:36:10.611024Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:10.608296Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from scipy.stats import zscore"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:10.970177Z",
+     "iopub.status.busy": "2021-07-05T16:36:10.969781Z",
+     "iopub.status.idle": "2021-07-05T16:36:10.975575Z",
+     "shell.execute_reply": "2021-07-05T16:36:10.974536Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:10.970144Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Method to find optimum threshold\n",
+    "def threshold():\n",
+    "    for i in np.arange(3,5,0.2):\n",
+    "        data=df.copy()\n",
+    "        data=data[(z<i).all(axis=1)]\n",
+    "        loss=(df.shape[0]-data.shape[0])/df.shape[0]*100\n",
+    "        print('With threshold {} data loss is {}%'.format(np.round(i,1),np.round(loss,2))) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:11.154090Z",
+     "iopub.status.busy": "2021-07-05T16:36:11.153708Z",
+     "iopub.status.idle": "2021-07-05T16:36:11.198230Z",
+     "shell.execute_reply": "2021-07-05T16:36:11.197146Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:11.154056Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "With threshold 3.0 data loss is 15.79%\n",
+      "With threshold 3.2 data loss is 12.17%\n",
+      "With threshold 3.4 data loss is 11.1%\n",
+      "With threshold 3.6 data loss is 10.2%\n",
+      "With threshold 3.8 data loss is 9.0%\n",
+      "With threshold 4.0 data loss is 8.44%\n",
+      "With threshold 4.2 data loss is 7.46%\n",
+      "With threshold 4.4 data loss is 6.08%\n",
+      "With threshold 4.6 data loss is 4.37%\n",
+      "With threshold 4.8 data loss is 1.55%\n"
+     ]
+    }
+   ],
+   "source": [
+    "z=np.abs(zscore(df))\n",
+    "threshold()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From above we choose threhold as 4.2 as data is precious and we cannot afford to lose more than 8% of data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:11.516415Z",
+     "iopub.status.busy": "2021-07-05T16:36:11.515856Z",
+     "iopub.status.idle": "2021-07-05T16:36:11.522605Z",
+     "shell.execute_reply": "2021-07-05T16:36:11.521832Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:11.516381Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df=df[(z<4.2).all(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "###### Removing Skewness"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:13.458162Z",
+     "iopub.status.busy": "2021-07-05T16:36:13.457779Z",
+     "iopub.status.idle": "2021-07-05T16:36:13.461994Z",
+     "shell.execute_reply": "2021-07-05T16:36:13.461064Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:13.458128Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#using Power transformer to remove skewness\n",
+    "from sklearn.preprocessing import PowerTransformer\n",
+    "pt=PowerTransformer()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:14.558068Z",
+     "iopub.status.busy": "2021-07-05T16:36:14.557717Z",
+     "iopub.status.idle": "2021-07-05T16:36:14.742224Z",
+     "shell.execute_reply": "2021-07-05T16:36:14.741301Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:14.558036Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "for i in cont:\n",
+    "    if np.abs(df[i].skew())>0.5:\n",
+    "        df[i]=pt.fit_transform(df[i].values.reshape(-1,1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:16.259259Z",
+     "iopub.status.busy": "2021-07-05T16:36:16.258779Z",
+     "iopub.status.idle": "2021-07-05T16:36:18.366263Z",
+     "shell.execute_reply": "2021-07-05T16:36:18.365179Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:16.259228Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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f/xKcOCbSebdhaGRnzXESYjwkxkbx8bPzT7sorLOnj5e3HyErKZYFhenBCTtKM/JSWL2thuqmDgrS7XwC4z5/F5T9UERSRSRGRF4XkVoRudXpcCaydHT38d9vlvHCpmqONHew72grX3lmM3/x87Vsqxr5qMefvraX+rZuPrGwICRWEo9kZq63gb1mr7UKTGjwd5L1VaraAnwMOABMB/7BqVAm8vT1K8+UHuJoSycrzp3EPVfN4uvXzOaBmxfR0tnDX/7PO6xcs5/+fj3pta/uPMpDa8opmZzBtJzQ78XMSYmjID3hxFkJxrjN30Iw0IV0LfCcqtpJ3CagHlpbzt6jrSw/u4AFhemICB4Rrl0wkZfvvojLZ+fxr6t3c9v/vs+uGu/5v339ygsbq/jSExuZX5DGX8yf6PLfwj8iwmWzc3m7rI7OHttuwrjP30LwexHZDSwGXheRHKDzdC8SkWUiskdEykTk3mGe/4KIbBORzSLytojMObP4Zjxo7ujhv98oY1ZeCudOOXlLiPTEWP7n1kX86yfns+lgI9f8fC2X/vhNPvKDP/H3z21hTn4aj31uKfEx4TMv/4o5ebR394XcOgcTmfzdhvpeEfkh0KyqfSLSBiwf6TUiEgU8AFwJVAEbRGSVqu4cdNmTqvqg7/rr8C5aWzaKv4cJY4+8XUFLZy9/df6pzw0QEW5eWsS18yfyxPsH2Xm4hb5+5Zsfy+fqENlh9EycNzWTpNgoXt111NXzlI0BPwuBz2y86wkGv+axEa5fApSpajmAiDyNt3icKAS+cYcBScDJHcBmXGvr6uXRtyu4Zt4E8v2YQZOWGMOXLpkehGTOiouO4uJZOby28yjfXT4PT5gVMjO++FUIRORxYBqwGRjo1FRGLgQFQOWg+1XA0mHe+2+BrwGxwGX+5DHjx+ptNbR29fLZj0xh39HWk54/1YEyNy8NjX2ExuKKs/JYve0IW6qaWFiU4XYcE8H8bRGUAHNUNeC/savqA8ADInIz8P+A24ZeIyJ3AncCFBWF/w8A8+cf8CvXlJOVFMveI8ddP1c42C4/K4+YKOEPW2usEBhX+VsItgMTgJozeO9qYNKg+4W+x07laeB/hntCVVcCKwFKSkqs+2icqG/t4kB9G1fNyYu4IjBQCKfnJPNsaSXF2Ul4fOMgxgSbv7OGsoGdIvKKiKwa+DrNazYAM0RkiojEAiuAD71GRGYMunstsM/f4Cb8fVDZhEBE/za8oDCdls5eDta3ux3FRDB/WwTfPtM3VtVeEbkLeAWIAh5V1R0icj9QqqqrgLtE5AqgB2hkmG4hM37tPNzC5KxE0hJi3I7imtkTU4iJErZWNTElO+n0LzDGAf5OH31LRCYDM1T1NRFJxPvD/XSvWw2sHvLYfYNu332Gec040dDWzZGWTq6ZN8HtKK6Ki45i9oRUtlc3h9T5yiay+LvX0OeB54Ff+B4qAF5yKJOJAAOrg+dMDM3tooNpQWEabd19lNedPGvKmGDwd4zgb4ELgRYAVd0H2CoYM2o7a1rITYkjKznO7Sium5mXQly0h62n2VjPGKf4Wwi6VLV74I5vUZnN3jGj0tzRw8H6Ns6y1gDgPaNgzsRUdhxupqvX9h4ywedvIXhLRP4Z7yH2VwLPAb9zLpYZz97bX0+/en8TNl4LCtPp7OnnzT22NbUJPn9nDd0LfA7YBvwN3gHgh50KZca3tftqiY32UJSZOOr3ONWK43A1PTeZlPhont1QydVzI3sA3QSfv7OG+kXkJeAlVbVfWcyYvF1Wx9TspLDbKM5JUR5hUVEGb+w5xtGWTvJS492OZCLIiF1D4vVtEakD9gB7fKeT3TfS64w5lcqGdg7WtzM9N/QPkAm2xZMz6Fd4fmOV21FMhDndGMFX8c4WOldVM1U1E+/GcReKyFcdT2fGnbX76gDv1grmw7KT41gyJZNnNlQOexKbMU45XSH4DHCTqlYMPODbVvpW4K+cDGbGp3f315GXGkdOik0bHc5nzpvMoYZ23rLzjE0Qna4QxKhq3dAHfeMEkbsvgBkVVWV9RQPnTc2KuE3m/LVs3gRyU+L45bsH3I5iIsjpCkH3KJ8z5iQVdW3UHu9i6ZQst6OErJgoD7csncxbe2spr7WVxiY4TlcIzhaRlmG+jgPzgxHQjB/rKxoAWDr15HOJzZ/dvLSI2GgPD79dcfqLjQmAEaePqmr4nAZuQtLg+f7PllaSHBfNuv311jU0gpyUOG5YXMjzpVV85fIZ5NpUUuMwf1cWGzMmqkpFXRtTspOsCIzgyfWHeHL9ISamxtPT1889z211O5KJAFYITFA0tHXT3NFje+77KSs5jvmFaayrqKe+tcvtOGacs0JggqKirg3ACsEZuHx2Hr19/Tzwxn63o5hxzgqBCYqKujYSY6PItfUDfstJiWNRUQa/XneQ6qYOt+OYccwKgQmKinobHxiNy2bnIgL/tnqX21HMOGaFwDiusb2bpnYbHxiN9MRYvnTJdH6/tYZ3yk5a22lMQFghMI6z8YGx+ZuLp1KUmcg3f7udzh47uMYEnhUC47iKujYSYqJsa+VRio+J4rufmEd5bRs/fXWv23HMOGSFwDiuvLaVKdlJeGx8YNQ+OjOHm5YUsXJtORsONLgdx4wzVgiMoxrbumls72FqjnULjdU3rj2LSRmJfPmpD2hos62+TOBYITCOKq/zbpw2zc4fGLPkuGj++5ZF1Ld1c/fTH9BnZxaYALFCYBy1v7aNpLhoWz8QIPMK0vj2x+eydl8d//WnMrfjmHHC38PrjTljqkp5bStTbf3AmAzeuA+8/64LJ6Xzs9f20tTRzYzclBPP3by0KNjxzDhgLQLjmIq6Nlo6e61bKMBEhOXnFJCbGsfT71faeIEZM0cLgYgsE5E9IlImIvcO8/zXRGSniGwVkddFZLKTeUxwvbu/HsAGih0QG+3h1qXeb5fH1x2gq9fWF5jRc6wQiEgU8ABwDTAHuElE5gy57AOgRFUXAM8DP3Qqjwm+9/bXk5YQQ1ZSrNtRxqWs5DhuWlLEsZYunt9YRb/a4LEZHSdbBEuAMlUtV9Vu4Glg+eALVPUNVW333V0HFDqYxwRRf7/yXnm9jQ84bHpuMtfMn8iOwy28ueeY23FMmHKyEBQAlYPuV/keO5XPAS8P94SI3CkipSJSWltbG8CIxil7jx2noa2bqTY+4LgLp2WxcFI6r+06xh93HHE7jglDITFYLCK3AiXAj4Z7XlVXqmqJqpbk5OQEN5wZlXfLbHwgWESETywsoDAjga8+s5m9R4+7HcmEGScLQTUwadD9Qt9jHyIiVwDfAK5TVTuKaZx4d38dRZmJZCTa+EAwxER5uGXpZBJio7nzsVKa23vcjmTCiJOFYAMwQ0SmiEgssAJYNfgCEVkI/AJvEbAOznGis6ePd8rquXimtd6CKS0hhl98ZhHVTR3c9dQmevv63Y5kwoRjhUBVe4G7gFeAXcCzqrpDRO4Xket8l/0ISAaeE5HNIrLqFG9nwsi68no6evq47Kxct6NEnMWTM/nO8nms3VfHD1/Z43YcEyYcXVmsqquB1UMeu2/Q7Suc/Hzjjjd2HyM+xsP5U7P4zaaTegONw1YsKWJnTQsr15RTnJVkq43NadkWEyagVJXXdx/jwmnZxMdEuR0n4gxsRzEjN4VZeSl848VtZCbFsmzeBJeTmVAWErOGzPix71grVY0d1i3ksiiPcNOSIiZlJvJ3T23iFZtWakZghcAE1OptNYjAFWfluR0l4sVGe7j9gmLmFaTxt09s4rnSytO/yEQk6xoyAaOq/H5rDUuKM+1YyhARHxPFY59dwhd/vYl/eH4r+461cs9Vs4iNHv53wKE7nYLtaBoJrEVgAmbv0VbKjrXysQUT3Y5iBkmJj+F///pcbj2viJVryrnhwXfZVtXsdiwTQqwQmID5/dbDeASWzbNCEEqeXH+I50qrmDMxjZuXFFF2rJWP/9fbfPWZzVQ3dbgdz4QA6xoyAdHfr7y0uZrzp2WRY6eRhax5BWlMz02mtrWLR9+u4A/bavjMeZP5wsXT7L9bBLNCYALinf11VDZ0cM9Vs9yOYk4jPiaKry+bza3nTeZnr+7ll+8e4In1B7nt/GJyU+JJiLVpv5HGCkEICeeBuqffryQjMYar59p89XBRkJ7Aj248my9dOp3/eH0fK9eWkxwXzSfOKeCsialuxzNBZGMEZszqWrv4484jXL+o0BaRhaEp2Un89NPnsOpvP0JSbDSPrzvI67uPonbQTcSwFoEZs8feO0hPn7JiSXi0XszwrU+AL10yjRc/qOb1Xcc43tnL8rPzg5zMuMEKgRmTtq5efvXuAa6ak8f0XDuEJtxFR3m4YXEhKfExrNlXS1yUh1vOs6PExzvrGjJj8tT7h2ju6OELl0xzO4oJEBHh6rl5nDc1k7VldTy7wVYkj3fWIjCj1tbVyy/WlHPe1EwWFWWcsrvBhB8R4dr5+dQd7+b/vbSd2RNTWFCY7nYs4xBrEZhRW7mmnNrjXfzjstluRzEOiPIInz53EtnJsXzlmc109vS5Hck4xAqBGZWjLZ2sXFPOtQsmsqgow+04xiFJcdH86MazKa9t40d20M24ZV1DZlQ++8sN9PT1c9aEVOsSGucunJ7NX50/mUffqeCqOXksnZrldiQTYNYiMGfs5W017DjcwuVn5ZGZZIfTR4J7r5lNUWYi9zy/hbauXrfjmACzQmDOyLGWTr752+3kp8XzkenZbscxQZIYG82PbzybqsYOvv/ybrfjmACzQhCimjt62FbdzO4jLSGzwrOvX/ny0x/Q1tXHjSWTiPKI25FMEJ1bnMlfXzCFx9cdZH15vdtxTADZGEGI6enr5/mNVWyr9u4X/9T7h8hNieOGxYUUZiQC7u0/9P2Xd7GuvIEf33g23b39rmQwwTd4DKgoM5HMpFi+9MQm3v76ZbZB3ThhLYIQ0tPXzy/fPcC26mYunpnDFy+exicXFtDV28+Db+1nnYu/hT2+7iAPra3gr86fzA2LC13LYdwVG+3hkwsLqG/r5qev7XU7jgkQKwQh5LWdR6moa+NTJYVcPXcCkzITObc4ky9fNoOZeSms2nKYV3ceCXpX0Qsbq7jvt9u5bHYu931sTlA/24SeaTnJnFucwcNry9lc2eR2HBMAVghCxAeHGnm7rI5zizM5Z9KH5+UnxEZxy9LJlEzO4I09tfzzi9vo7fOva+bJ9YdO+joTj687yD3Pb+HCadk8cPMioqPsfxkD18ybSG5KPF97djPt3TaLKNzZGEEIUFW+vWoHqQkxXDNv+P38ozzCJxcWkBwfzVPvV1LX2s1/3rTQsW2fO3v6+O4fdvLrdYeYlZfCFWfl8eIH1Y58lgk/8TFR/ORTZ3PLI+u5/3c7+f71C9yOZMbACkEIeGtvLVuqmvnkwoIRf7CLCFfNmcCls3L59u92cPND6/jhDWcHdNdPVeX1Xcf43updVNS1cdH0bK6eNwGP2Awh82EH6tv56Iwcnt5QiYgwvyAtbA5SMh/maCEQkWXAz4Eo4GFV/f6Q5z8K/AxYAKxQ1eedzBOKVJX/eH0fBekJLCxK9+s1t11QTHZyHPe+sJVlP1vDNfMncvHMHLZXN9PZ00djew8Nbd00tnXT2N5NR08fqhAX4yElLpq1+2qZkBbPhNR4JqTFk5MSR3O7d7rqKzuOsL+2jclZiTx5x1IO1Lc7+w9gwtoVZ+Wxv7aVFz+oYlJGgttxzCiJUwOPIhIF7AWuBKqADcBNqrpz0DXFQCpwD7DKn0JQUlKipaWljmR2w4YDDdz44Ht8Z/lcojz+9b8P/NZV19rFf76+j99vraG+rftD1yTGRpGZFEtGYiyJvil+Xb39HO/sAeBIcydt3R/eRMwjUJSZRElxBmcXpts6AeOX+tYu/uuNMnJT4nj1axfbKXUhSkQ2qmrJcM852SJYApSparkvxNPAcuBEIVDVA77nInZS+lPvHyI5LprrFxfy0geHz+i12clx/Mvyedz38blU1LXxXGklsdEeMhJjR/xmHCgkxzt7ONLcSe3xLtISY3i/vIE4+yY2Zygr2bvO5Yn1h/j6C1v52afPQawrMaw4WQgKgMEnWlQBS0fzRiJyJ3AnQFHR+OmDbO7oYfW2Gv5yUSGJsaP/TxHlEabnJjM5K+mMXpcSH0NKfAwz8lIA2FLZPOoMJrLNzU/jqjl5/HbzYWbkJnPXZTPcjmTOQFjMBVTVlapaoqolOTk5bscJmFVbDtPZ08+Kcye5HcWYMbt4Zg6fOCefH/9xLy9vq3E7jjkDTrYIqoHBP+EKfY9FvIG5/A++uZ+JafFsq2pme3WLy6mMGRsR4fvXL+BQQzt3P7OZtIQYLrCNCcOCk4VgAzBDRKbgLQArgJsd/Lywcripg+qmDj6+YGLQ+1Pt/ADjlPiYKB657VxWrFzHHY+V8sQdS1loBxeFPMe6hlS1F7gLeAXYBTyrqjtE5H4RuQ5ARM4VkSrgRuAXIrLDqTyhpvRgA9EeOWkVsTHhLiMplsc/t4SclDhu/98N7Kqx1m6oc3SMQFVXq+pMVZ2mqt/zPXafqq7y3d6gqoWqmqSqWao618k8oaKnr5/NlU3MzU+13RvNuJSbGs+vP7eUhJgoPvPIevYdPe52JDOCsBgsHm92HG6ms6efkuJMt6MY45hJmYk88fmleES46aF1VgxCmGMLypwyHhaUXfrjN2nu6OFrV860rRvMuFd7vIuH15bTD9zxkSnkpcYD7p2rEalGWlBmLYIgq6hro6KujZLJGVYETETISYnjjoum4gEeebuCoy2dbkcyQ1ghCLJnSyvxCCyymRQmggwUA8GKQSiyQhBEvb5jKGflpZCaEON2HGOCKicljs9dNOVEMSg7ZmMGocIKQRC9saeW2uNdNkhsIlZuSvyJYrBi5XorBiHCCkEQPbPBexD9TN/ePsZEohPFQKwYhAorBEFytKWTP+0+xg2LC217ZxPxclPieerz51kxCBFWCILkmQ2V9Ct8qsQ2mDMGYHpuMk99/jxgoBi0upwoclkhCIKevn6eWH+Qi2fmUJx9ZltFGzNePbn+EO9XNHDreUV09vTxiQfesUVnLrFCEAR/3HGUoy1d3HbBZLejGBNyclPiucM3gHzjL96j9ECD25EijhWCIPjVuwcoykzk4pm5bkcxJiTlpsTzNxdPIzMxllseXs//bT/idqSIYoXAYRsPNvL+gQZuu6DYBomNGUFmUizPf/EC5uSn8sUnNrJyzX7CbQuccGWFwGEPvrWf9MQYO4XMGD9kJsXy5B3ncfWcCfzr6t3c+fhGmtt73I417jl5ME3E23f0OK/uPMpls3P57eYzO5jemEg0cGjSRTOyifIIL2+v4ZIfv8HDt53L4sm2LYtTrEXgoJ+8upfYaA/nT81yO4oxYUVEuHB6Nnd+dBqqcMOD7/LNl7bT0mmtAydYIXDI5somXt5+hIumZ5MUZw0vY0ajKDORL18+g9vOL+aJ9Qe5/N/f4oWNVfT129hBIFkhcICq8v2Xd5GVFMtH7PBuY8YkPiaKmXkpfPHi6cRGefj757aw9F9f57ebq60gBIgVAge8tLmadeUNfOXKmcTF2FGUxgRCQUYCX7xkGjcvKSLaI9z99GYu+/c3eWhNOU3t3W7HC2t2QlmANbZ1c/lP3qIoM5EXvngBz2yodDuSMeNOvyo7Drfw7v46Dta3E+0R5hWkcdel07loZjZx0fYL2FAjnVBmndcBpKp846VtNHf08G9/Od/WDRjjEI8I8wvSmF+QxpHmTtZX1LO1qpk7HislJT6aq+ZM4GMLJnL+tCzirVV+WlYIAujxdQdZve0I/3TNbM6amOp2HGMiwoS0eJafU8C1CyYyKTORP2yt4ZUdR3hhUxUJMVFcOD2LS2blcsmsHAozEt2OG5KsEATI2n21fOf3O7l0Vg6fv2iq23GMiTjRHg81TZ0sKspgQUEa+2tb2X3kOBsPNvLarmMATMtJYsmUTEomZ7JocgZFmYnWcsfGCAJi48FGblq5jsykWD5/0VQSYq0pakyoUFVqW7vYe+Q4ZbWtHGpop7OnH4C4aA/Tc5OZkZvMjLwUpuUkUZydRHFW0rjrUrIxAge9suMIdz/9Acnx0dx+YbEVAWNCjIiQmxJPbko8H5mRQ78qx1q6KMiIZ9/RVvYea2V9RQMvDVn9n5YQQ1ZyLNlJcVw5J4/i7CSmZCcyKTNx3A1GW4tglNq6evnB/+3msfcOcs6kdP5i/kSSbeGYMWGrs6ePutYu6lu7qWvz/lnf2kVdazcdPX0nrvMI5KcnMMXXcijOTmJaThLTcpIpSE/AE6JdTa61CERkGfBzIAp4WFW/P+T5OOAxYDFQD3xaVQ84mWmsjrV08vymKh5eW0FjezefvXAK/7hsFr/ZVO12NGPMGMTHRFGYkTjsgHJ7d6+3QLR2Ud/m/bO8to0NBxpOdDMBRHvkRBfTtJxkpuUmMy0nianZySHdW+BYIRCRKOAB4EqgCtggIqtUdeegyz4HNKrqdBFZAfwA+LRTmYajqvSrd15yX7+iCn2qtHf30tjWQ0NbN9VNHew9epzSAw1srmyiX+GjM3P46hUzWFhkG2EZM94lxkaTmBnNpMwPFwlVpa27j9rjXdQd76K2tYuYKGFrVTN/2FbD4A6XgvQEpucm+wqEtzWRGh9DUlwUyXHRJMZFExftIUoEEW+XVrA42SJYApSpajmAiDwNLAcGF4LlwLd9t58H/ktERB3or3rk7Qr+/Y97Tvyw71elTxV/Pykmyjtv+a5Lp3PdOflMz00JdERjTJgREZLjokmOi2bKoGNor8R7RG19aze1rV1MTItnf20r+2tbeb+i4UNdTad+b4gSweMrDB4RvvXxOaxYUhTwv4eThaAAGLystgpYeqprVLVXRJqBLKBu8EUicidwp+9uq4jsOcMs2UPfczTKgBeBvx/rG52ZgGR3QbjmhvDNHq65IXyzBzX3Td+Fm0b/8lOelRsWo5uquhJYOdrXi0jpqQZJQl24Zg/X3BC+2cM1N4Rv9nDNPZSTm85VA4OP5Sr0PTbsNSISDaThHTQ2xhgTJE4Wgg3ADBGZIiKxwApg1ZBrVgG3+W7fAPzJifEBY4wxp+ZY15Cvz/8u4BW800cfVdUdInI/UKqqq4BHgMdFpAxowFssnDDqbqUQEK7ZwzU3hG/2cM0N4Zs9XHN/SNgtKDPGGBNYdjCNMcZEOCsExhgT4SKmEIjId0Rkq4hsFpE/iki+25n8ISI/EpHdvuwviki625n8JSI3isgOEekXkZCfYiciy0Rkj4iUici9bufxl4g8KiLHRGS721nOhIhMEpE3RGSn7/+Tu93O5C8RiReR90Vkiy/7v7idaSwiZoxARFJVtcV3+8vAHFX9gsuxTktErsI7m6pXRH4AoKpfdzmWX0TkLKAf+AVwj6q6v1vgKfi2RNnLoC1RgJuGbIkSkkTko0Ar8JiqznM7j79EZCIwUVU3iUgKsBH4RJj8mwuQpKqtIhIDvA3crarrXI42KhHTIhgoAj5JQFhUQFX9o6r2+u6uw7seIyyo6i5VPdNV4G45sSWKqnYDA1uihDxVXYN31l1YUdUaVd3ku30c2IV3t4GQp16tvrsxvq+w+JkynIgpBAAi8j0RqQRuAe5zO88ofBZ42e0Q49RwW6KExQ+l8UBEioGFwHqXo/hNRKJEZDNwDHhVVcMm+1DjqhCIyGsisn2Yr+UAqvoNVZ0EPAHc5W7aPztdbt813wB68WYPGf5kN2YkIpIMvAB8ZUjLPaSpap+qnoO3lb5ERMKmW26osNhryF+qeoWflz4BrAa+5WAcv50ut4jcDnwMuDzUVl6fwb95qPNnSxQTYL7+9ReAJ1T1N27nGQ1VbRKRN4BlQFgN2A8YVy2CkYjIjEF3lwO73cpyJnyH+/wjcJ2qtrudZxzzZ0sUE0C+AddHgF2q+hO385wJEckZmMEnIgl4JxmExc+U4UTSrKEXgFl4Z7EcBL6gqiH/G59v+404/rwZ37pwmO0EICKfBP4TyAGagM2qerWroUYgIn8B/Iw/b4nyPXcT+UdEngIuwbsl8lHgW6r6iKuh/CAiHwHWAtvwfl8C/LOqrnYvlX9EZAHwK7z/r3iAZ1X1fndTjV7EFAJjjDHDi5iuIWOMMcOzQmCMMRHOCoExxkQ4KwTGGBPhrBAYY0yEs0JgzBAi8mUR2SUip1zFLSKtp3ruDD7n9nDZBdeMb+NqZbExAfIl4ApVrXL4c27HuxL1sMOfY8yIrEVgzCAi8iAwFXhZRJp9e/2/KSLlvu3Lh17/gIhc57v9oog86rv9WRH5nu/2N33nHLwtIk+JyD0icgNQAjzhOyMjIXh/S2M+zAqBMYP4Vm0fBi4FfgrMBq7Gu031t3x74wy2FrjId7sAmOO7fRGwRkTOBa4HzgauwfvDH1V9HigFblHVc1S1w7G/lDGnYYXAmJH9QVW7VLUO73bDeUOeXwtcJCJzgJ3AUd+BK+cD7wIXAr9V1U7fnvu/C2J2Y/xiYwTGjKxr0O0+hnzPqGq1b/OxZcAaIBP4FNCqqse9+6oZE9qsRWDM2K0DvoK3EKwF7vH9CfAO8HHfGbfJeLcTH3AcSAliTmOGZYXAmLFbC0SrahmwCW+rYC2Aqm7Au531Vryny20Dmn2v+yXwoA0WG7fZ7qPGOExEkn2HnCfibTXcOXBWrzGhwMYIjHHeSt9gcjzwKysCJtRYi8AYYyKcjREYY0yEs0JgjDERzgqBMcZEOCsExhgT4awQGGNMhPv/FiQ+UlrBtdgAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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MrJYlH/Ab2ptoKiztt3na+izgvUxjZjUsz22SfwPcDZwjab+kf5nXWPM5ssQ2BSWndbYCcPi4d9KYWe1qzOvEEfHOvM5drqVexVriJRozS0HSSzR9J8bozmbjS7GhvYnmQgPPeQZvZjUs2YCfmg6e7R9h+4a2Jb9XEt2dLfR5Bm9mNSzZgD98fJSJqWDnpqUHPEB3p/fCm1ltSzbg9x0dAWDHxvZlvf+0zhZ/yWpmNS3ZgN9/bBiAHRuXN4M/fX0rz3mJxsxqWMIBX5zBL2cNHop/MQyMTDAw4ht/mFltSjjghzmts4XWpsKy3r97SwcATx8ZqmRZZmarJtmA33d0ZNnLMwBnlgL+eQe8mdWmZAN+f/8wOzct7wtWgF2b2pHgKc/gzaxGJRnwk1PTHOwfXdEMvrWpwLauNi/RmFnNSjLgDw2OMjkdy94iWXLmlg7P4M2sZiUZ8KUdNDtXGPC7t7Tz1JEhIqISZZmZraokA/6X2Rejy72KtWT35g4GRyc5NuytkmZWe5IM+IcODNDZ0rjiGXxpJ42XacysFiUZ8A/uH+C87V00NGhF53HAm1ktSy7gxyaneOzgIOfv7FrxuXZuaqe5sYHHDw5WoDIzs9WVXMA/fvA4E1PBBTs2rPhcTYUGLty5gZ89fXTlhZmZrbLkAv6B/f0AnL9j5TN4gMvO2szDBwYYHPUXrWZWW9IL+H0DbO5oXnaTsdkuO2sT0wG9nsWbWY1JL+D393P+ji6klX3BWnLxro00Fxr46ZMOeDOrLUkF/KPPDvKLwyf4lbO7K3bO1qYCF+7cwE+ffL5i5zQzWw1JBfzXevfRXGjgn160vaLnvfwlxXX4Z54fruh5zczylEzAj05M8Y37DvCG87aysaO5oud+5yW7aGxo4LM//EVFz2tmlqfGahdQKbf17mNgZIJ3vHJnxc+9tauVt79yJ7fe8wwfuPLsin2Ba2a16yt7npnz+Lsu3bXKlcwv14CXdBVwE1AAbomIP85jnHuePson7nyUV71kM5eftTmPIfi9176EW+95hg/dej+3XNvD+tamXMYxs9oxNDbJgf4R9h8bYWBknNGJae595hjbulo5d9t6zj2jix0b21Z8Vf1y5RbwkgrAnwOvB/YD90j6VkQ8Wslx+ofHed8X97JjYzufuebi3D7I7Rva+NTbLuDDX3uAt37mJ/yLV5/JZWdtZuv6VpobG2gQFdu5Y2aVFxFEQMx8/MLPUHo0s3lsBExHcGx4nL7jYxw+PsbPDx3nkWcH2PPUUfpnNCLsaGmktbGBIyfGeG5wlOnsPJ2tjZy/o4vzd2zgZVs7OX19K1vXt7JpXTMtjQ00Fxpyy448Z/CXAL+IiCcBJN0KvAWoaMBvaG/mI284h0vO3MSG9squvc/2lgu3s7G9mRu+9QgfveOhFz3fVBCFBlFw0JtVRPDi8I0ZT851fHZw5+GsLR3s3NjO5We1sX1DG9s2tL1w/+d3XbqLkfEp/uG54zx6cJCHDgzw4P5+/vJHTzI5/eKCJNjW1cb/vf7KiteZZ8BvB/bNeLwfuHT2iyRdB1yXPTwh6ec51lSOLdfAkSrXsFZtwZ/NfPzZzC+5z+aXCzx3zdJOtQU48jSgjy67nH803xNV/5I1Im4Gbq52HSWSeiOip9p1rEX+bObnz2Z+/mzml/dnk+c2yQPAzC0tO7JjZma2CvIM+HuAsyWdKakZeAfwrRzHMzOzGXJboomISUkfAP4XxW2SfxURj+Q1XgWtmeWiNcifzfz82czPn838cv1s5BtKm5mlKZlWBWZmdioHvJlZohzwGUlXSfq5pF9Iur7a9awVknZKukvSo5IekfTBate01kgqSLpP0p3VrmUtkbRB0u2SHpf0mKTLq13TWiHpQ9mfp4cl/Y2k1jzGccBzSluF3wDOBd4p6dzqVrVmTAIfjohzgcuA9/uzeZEPAo9Vu4g16CbgOxHxMuAC/BkBIGk78K+Bnog4j+ImlHfkMZYDvuiFtgoRMQ6U2irUvYg4GBH3Zj8fp/iHtLIN92uYpB3A1cAt1a5lLZHUBbwG+BxARIxHRH9Vi1pbGoE2SY1AO/BsHoM44IvmaqvgEJtF0m7gImBPlUtZS/4U+AgwXeU61pozgT7g89ny1S2SOqpd1FoQEQeATwHPAAeBgYj4bh5jOeCtLJLWAV8H/iAiBqtdz1og6Y3A4YjYW+1a1qBG4GLgsxFxETAE+LstQNJGiisEZwLbgA5J785jLAd8kdsqLEBSE8Vw/3JE3FHtetaQK4A3S3qa4rLelZK+VN2S1oz9wP6IKP1r73aKgW/wa8BTEdEXERPAHcCr8hjIAV/ktgrzULFR9eeAxyLixmrXs5ZExEcjYkdE7Kb4/8wPIiKXmVitiYhDwD5J52SHXkeFW4XXsGeAyyS1Z3++XkdOX0BXvZvkWlDDbRVWwxXAe4CHJN2fHftYRHy7eiVZjfh94MvZpOlJ4L1VrmdNiIg9km4H7qW4S+0+cmpZ4FYFZmaJ8hKNmVmiHPBmZolywJuZJcoBb2aWKAe8mVmiHPBWtyRty7arIelCSb9ZxnteO1fXSEm7JT2cR51my+WAt7oVEc9GxG9lDy8EFg14s1rigLeaJem3JT0o6QFJX5T0Jkl7suZW35d0eva6G7Ln75b0hKTfzY7vzvpxNwOfAN4u6X5Jb5d0Sfb6+yT9ZMYVmeXU1Srp85Ieyt7/q9nxl0v6WTbGg5LOltQh6e+y38PDkt6ex2dl9clXslpNkvRy4A+BV0XEEUmbgAAui4iQ9DsUuzx+OHvL+RT72XcA90n6u9K5ImJc0r+n2J/7A9n51wO/kl3l/GvAfwLeWmZ57y+eNl4h6WXAdyW9FPg94KaIKF3dWaD4r4ZnI+LqbNyu5X8qZqdywFutuhK4LSKOAETEUUmvAL4q6QygGXhqxuv/NiJGgBFJd1G8B8D9C5y/C/iCpLMp/sXRtITaXg18OqvrcUm/BF4K3A38u6yH/B0R8YSkh4D/Jum/AHdGxI+XMI7ZgrxEYyn5NPBnEfEK4H3AzNugze7JsViPjj8C7sruuPOmWedaloj4CvBmYAT4tqQrI+IfKHZZfAj4ZPYvCbOKcMBbrfoB8DZJmwGyJZouTrZ5/uezXv+WbG18M/Baih1EZzoOdM54PPNc1y6xth8D12R1vRTYBfxc0lnAkxHx34G/Bc6XtA0YjogvAf8Vt9S1CnLAW03Kun3+R+CHkh4AbgRuAG6TtBc4MustDwJ3AT8F/igiZt8i7S7g3NKXrMCfAP9Z0n3Ms5QpqUfSXLfq+wzQkC2/fBW4NiLGgH8GPJx15TwP+GvgFcDPsmMfBz5Z/qdgtjB3k7TkSboBOBERn6p2LWaryTN4M7NEeQZvZpYoz+DNzBLlgDczS5QD3swsUQ54M7NEOeDNzBL1/wG2YR+HfJNV6gAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 432x288 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for i in cont:\n",
+    "    sns.distplot(df[i])\n",
+    "    plt.figure()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A lot of skewness has been resuced but we cannot remove skewness more than this."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:18.368392Z",
+     "iopub.status.busy": "2021-07-05T16:36:18.368013Z",
+     "iopub.status.idle": "2021-07-05T16:36:18.378452Z",
+     "shell.execute_reply": "2021-07-05T16:36:18.377402Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:18.368352Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Separating dependent and independent features.\n",
+    "x=df.copy()\n",
+    "x.drop('income',axis=1,inplace=True)\n",
+    "y=df['income']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>age</th>\n",
+       "      <th>workclass</th>\n",
+       "      <th>fnlwgt</th>\n",
+       "      <th>education</th>\n",
+       "      <th>education.num</th>\n",
+       "      <th>marital.status</th>\n",
+       "      <th>occupation</th>\n",
+       "      <th>relationship</th>\n",
+       "      <th>race</th>\n",
+       "      <th>sex</th>\n",
+       "      <th>capital.gain</th>\n",
+       "      <th>capital.loss</th>\n",
+       "      <th>hours.per.week</th>\n",
+       "      <th>native.country</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>993</th>\n",
+       "      <td>-1.111495</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>-1.814520</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>7.690495</td>\n",
+       "      <td>40</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>994</th>\n",
+       "      <td>-1.576984</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.680310</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>7.690495</td>\n",
+       "      <td>40</td>\n",
+       "      <td>35.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>995</th>\n",
+       "      <td>-0.706882</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0.424877</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>7.690495</td>\n",
+       "      <td>40</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>996</th>\n",
+       "      <td>1.391427</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.500601</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>7.690495</td>\n",
+       "      <td>30</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>997</th>\n",
+       "      <td>-1.111495</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>-1.087030</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>7.690495</td>\n",
+       "      <td>32</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32556</th>\n",
+       "      <td>-1.335418</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.186849</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>-0.130031</td>\n",
+       "      <td>40</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32557</th>\n",
+       "      <td>-0.803248</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.764117</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>-0.130031</td>\n",
+       "      <td>38</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32558</th>\n",
+       "      <td>0.267891</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>-0.214107</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>-0.130031</td>\n",
+       "      <td>40</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32559</th>\n",
+       "      <td>1.340658</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>-0.241150</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>-0.130031</td>\n",
+       "      <td>40</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32560</th>\n",
+       "      <td>-1.335418</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.265661</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>-0.130031</td>\n",
+       "      <td>20</td>\n",
+       "      <td>39.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>30132 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            age  workclass    fnlwgt  education  education.num  \\\n",
+       "993   -1.111495        4.0 -1.814520       11.0              9   \n",
+       "994   -1.576984        0.0 -0.680310        1.0              7   \n",
+       "995   -0.706882        6.0  0.424877       15.0             10   \n",
+       "996    1.391427        4.0  0.500601       11.0              9   \n",
+       "997   -1.111495        4.0 -1.087030       11.0              9   \n",
+       "...         ...        ...       ...        ...            ...   \n",
+       "32556 -1.335418        4.0  1.186849       15.0             10   \n",
+       "32557 -0.803248        4.0  0.764117        7.0             12   \n",
+       "32558  0.267891        4.0 -0.214107       11.0              9   \n",
+       "32559  1.340658        4.0 -0.241150       11.0              9   \n",
+       "32560 -1.335418        4.0  0.265661       11.0              9   \n",
+       "\n",
+       "       marital.status  occupation  relationship  race  sex  capital.gain  \\\n",
+       "993               4.0         8.0           1.0   4.0  0.0     -0.296771   \n",
+       "994               3.0         0.0           3.0   1.0  0.0     -0.296771   \n",
+       "995               4.0        14.0           1.0   4.0  1.0     -0.296771   \n",
+       "996               0.0        12.0           4.0   4.0  0.0     -0.296771   \n",
+       "997               4.0        12.0           3.0   4.0  0.0     -0.296771   \n",
+       "...               ...         ...           ...   ...  ...           ...   \n",
+       "32556             4.0        11.0           1.0   4.0  1.0     -0.296771   \n",
+       "32557             2.0        13.0           5.0   4.0  0.0     -0.296771   \n",
+       "32558             2.0         7.0           0.0   4.0  1.0     -0.296771   \n",
+       "32559             6.0         1.0           4.0   4.0  0.0     -0.296771   \n",
+       "32560             4.0         1.0           3.0   4.0  1.0     -0.296771   \n",
+       "\n",
+       "       capital.loss  hours.per.week  native.country  \n",
+       "993        7.690495              40            39.0  \n",
+       "994        7.690495              40            35.0  \n",
+       "995        7.690495              40            39.0  \n",
+       "996        7.690495              30            39.0  \n",
+       "997        7.690495              32            39.0  \n",
+       "...             ...             ...             ...  \n",
+       "32556     -0.130031              40            39.0  \n",
+       "32557     -0.130031              38            39.0  \n",
+       "32558     -0.130031              40            39.0  \n",
+       "32559     -0.130031              40            39.0  \n",
+       "32560     -0.130031              20            39.0  \n",
+       "\n",
+       "[30132 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Handling Imbalanced Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:19.318224Z",
+     "iopub.status.busy": "2021-07-05T16:36:19.317905Z",
+     "iopub.status.idle": "2021-07-05T16:36:19.774222Z",
+     "shell.execute_reply": "2021-07-05T16:36:19.773009Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:19.318196Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Oversampling using Smote\n",
+    "from imblearn.over_sampling import SMOTE\n",
+    "over=SMOTE()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:19.907976Z",
+     "iopub.status.busy": "2021-07-05T16:36:19.907640Z",
+     "iopub.status.idle": "2021-07-05T16:36:20.216843Z",
+     "shell.execute_reply": "2021-07-05T16:36:20.215965Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:19.907946Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "x,y=over.fit_resample(x,y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:20.479115Z",
+     "iopub.status.busy": "2021-07-05T16:36:20.478775Z",
+     "iopub.status.idle": "2021-07-05T16:36:20.644175Z",
+     "shell.execute_reply": "2021-07-05T16:36:20.643132Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:20.479079Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1    23424\n",
+       "0    23424\n",
+       "Name: income, dtype: int64"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x360 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,5))\n",
+    "plt.subplot(1,2,1)\n",
+    "y.value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.subplot(1,2,2)\n",
+    "sns.countplot(y)\n",
+    "y.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Data is balanced now, both the category of income have 50% data each."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Scaling the data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:22.219100Z",
+     "iopub.status.busy": "2021-07-05T16:36:22.218755Z",
+     "iopub.status.idle": "2021-07-05T16:36:22.222422Z",
+     "shell.execute_reply": "2021-07-05T16:36:22.221719Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:22.219068Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Scaling the data using min max scaler\n",
+    "from sklearn.preprocessing import MinMaxScaler\n",
+    "scaler=MinMaxScaler()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:23.538389Z",
+     "iopub.status.busy": "2021-07-05T16:36:23.538054Z",
+     "iopub.status.idle": "2021-07-05T16:36:23.552380Z",
+     "shell.execute_reply": "2021-07-05T16:36:23.551386Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:23.538359Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "xd=scaler.fit_transform(x)\n",
+    "x=pd.DataFrame(xd,columns=x.columns)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Modelling Phase"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:25.047128Z",
+     "iopub.status.busy": "2021-07-05T16:36:25.046784Z",
+     "iopub.status.idle": "2021-07-05T16:36:25.127027Z",
+     "shell.execute_reply": "2021-07-05T16:36:25.126071Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:25.047099Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#We import Classification Models\n",
+    "from sklearn.naive_bayes import  GaussianNB\n",
+    "from sklearn.neighbors import KNeighborsClassifier\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.tree import DecisionTreeClassifier\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from sklearn.ensemble import AdaBoostClassifier\n",
+    "from sklearn.ensemble import GradientBoostingClassifier\n",
+    "from xgboost import XGBClassifier"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:26.248114Z",
+     "iopub.status.busy": "2021-07-05T16:36:26.247757Z",
+     "iopub.status.idle": "2021-07-05T16:36:26.252576Z",
+     "shell.execute_reply": "2021-07-05T16:36:26.251854Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:26.248074Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split, cross_val_score"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:26.639631Z",
+     "iopub.status.busy": "2021-07-05T16:36:26.639156Z",
+     "iopub.status.idle": "2021-07-05T16:36:26.643649Z",
+     "shell.execute_reply": "2021-07-05T16:36:26.642623Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:26.639600Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.metrics import accuracy_score,confusion_matrix,classification_report,roc_auc_score,roc_curve"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:27.319144Z",
+     "iopub.status.busy": "2021-07-05T16:36:27.318791Z",
+     "iopub.status.idle": "2021-07-05T16:36:27.324076Z",
+     "shell.execute_reply": "2021-07-05T16:36:27.323386Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:27.319114Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Function to find the best random state\n",
+    "def randomstate(x,y):\n",
+    "    maxx=0\n",
+    "    model=LogisticRegression()\n",
+    "    for i in range(1,201):\n",
+    "        xtrain,xtest,ytrain,ytest=train_test_split(x,y,test_size=0.25,random_state=i)\n",
+    "        model.fit(xtrain,ytrain)\n",
+    "        p=model.predict(xtest)\n",
+    "        accu=accuracy_score(p,ytest)\n",
+    "        if accu>maxx:\n",
+    "            maxx=accu\n",
+    "            j=i\n",
+    "    return j"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:27.859665Z",
+     "iopub.status.busy": "2021-07-05T16:36:27.859095Z",
+     "iopub.status.idle": "2021-07-05T16:36:27.865052Z",
+     "shell.execute_reply": "2021-07-05T16:36:27.864185Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:27.859631Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#To evakuate performances of all the models\n",
+    "def performance(p,ytest,m,xtest,s):\n",
+    "    print('------------------------------------',m,'------------------------------------')\n",
+    "    print('Accuracy',np.round(accuracy_score(p,ytest),4))\n",
+    "    print('----------------------------------------------------------')\n",
+    "    print('Mean of Cross Validation Score',np.round(s.mean(),4))\n",
+    "    print('----------------------------------------------------------')\n",
+    "    print('AUC_ROC Score',np.round(roc_auc_score(ytest,m.predict_proba(xtest)[:,1]),4))\n",
+    "    print('----------------------------------------------------------')\n",
+    "    print('Confusion Matrix')\n",
+    "    print(confusion_matrix(p,ytest))\n",
+    "    print('----------------------------------------------------------')\n",
+    "    print('Classification Report')\n",
+    "    print(classification_report(p,ytest))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:30.408181Z",
+     "iopub.status.busy": "2021-07-05T16:36:30.407693Z",
+     "iopub.status.idle": "2021-07-05T16:36:30.412054Z",
+     "shell.execute_reply": "2021-07-05T16:36:30.411332Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:30.408148Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Creating a list of models which will be created one by one\n",
+    "models=[GaussianNB(),KNeighborsClassifier(),LogisticRegression(),DecisionTreeClassifier(),\n",
+    "        RandomForestClassifier(),AdaBoostClassifier(),GradientBoostingClassifier(),XGBClassifier(verbosity=0)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:30.858989Z",
+     "iopub.status.busy": "2021-07-05T16:36:30.858664Z",
+     "iopub.status.idle": "2021-07-05T16:36:30.864602Z",
+     "shell.execute_reply": "2021-07-05T16:36:30.863414Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:30.858961Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Creates and trains model from the models list\n",
+    "def createmodel(x,y):\n",
+    "    xtrain,xtest,ytrain,ytest=train_test_split(x,y,test_size=0.25,random_state=randomstate(x,y))\n",
+    "    for i in models:\n",
+    "        model=i\n",
+    "        model.fit(xtrain,ytrain)\n",
+    "        p=model.predict(xtest)\n",
+    "        score=cross_val_score(model,x,y,cv=10)\n",
+    "        performance(p,ytest,model,xtest,score) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:32.968371Z",
+     "iopub.status.busy": "2021-07-05T16:36:32.968055Z",
+     "iopub.status.idle": "2021-07-05T16:40:42.188105Z",
+     "shell.execute_reply": "2021-07-05T16:40:42.187002Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:32.968344Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "------------------------------------ GaussianNB() ------------------------------------\n",
+      "Accuracy 0.7871\n",
+      "----------------------------------------------------------\n",
+      "Mean of Cross Validation Score 0.7567\n",
+      "----------------------------------------------------------\n",
+      "AUC_ROC Score 0.8657\n",
+      "----------------------------------------------------------\n",
+      "Confusion Matrix\n",
+      "[[4479 1065]\n",
+      " [1429 4739]]\n",
+      "----------------------------------------------------------\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.76      0.81      0.78      5544\n",
+      "           1       0.82      0.77      0.79      6168\n",
+      "\n",
+      "    accuracy                           0.79     11712\n",
+      "   macro avg       0.79      0.79      0.79     11712\n",
+      "weighted avg       0.79      0.79      0.79     11712\n",
+      "\n",
+      "------------------------------------ KNeighborsClassifier() ------------------------------------\n",
+      "Accuracy 0.854\n",
+      "----------------------------------------------------------\n",
+      "Mean of Cross Validation Score 0.8437\n",
+      "----------------------------------------------------------\n",
+      "AUC_ROC Score 0.9188\n",
+      "----------------------------------------------------------\n",
+      "Confusion Matrix\n",
+      "[[4717  519]\n",
+      " [1191 5285]]\n",
+      "----------------------------------------------------------\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.80      0.90      0.85      5236\n",
+      "           1       0.91      0.82      0.86      6476\n",
+      "\n",
+      "    accuracy                           0.85     11712\n",
+      "   macro avg       0.85      0.86      0.85     11712\n",
+      "weighted avg       0.86      0.85      0.85     11712\n",
+      "\n",
+      "------------------------------------ LogisticRegression() ------------------------------------\n",
+      "Accuracy 0.7785\n",
+      "----------------------------------------------------------\n",
+      "Mean of Cross Validation Score 0.7542\n",
+      "----------------------------------------------------------\n",
+      "AUC_ROC Score 0.8529\n",
+      "----------------------------------------------------------\n",
+      "Confusion Matrix\n",
+      "[[4475 1161]\n",
+      " [1433 4643]]\n",
+      "----------------------------------------------------------\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.76      0.79      0.78      5636\n",
+      "           1       0.80      0.76      0.78      6076\n",
+      "\n",
+      "    accuracy                           0.78     11712\n",
+      "   macro avg       0.78      0.78      0.78     11712\n",
+      "weighted avg       0.78      0.78      0.78     11712\n",
+      "\n",
+      "------------------------------------ DecisionTreeClassifier() ------------------------------------\n",
+      "Accuracy 0.8557\n",
+      "----------------------------------------------------------\n",
+      "Mean of Cross Validation Score 0.8356\n",
+      "----------------------------------------------------------\n",
+      "AUC_ROC Score 0.8557\n",
+      "----------------------------------------------------------\n",
+      "Confusion Matrix\n",
+      "[[5038  820]\n",
+      " [ 870 4984]]\n",
+      "----------------------------------------------------------\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.85      0.86      0.86      5858\n",
+      "           1       0.86      0.85      0.86      5854\n",
+      "\n",
+      "    accuracy                           0.86     11712\n",
+      "   macro avg       0.86      0.86      0.86     11712\n",
+      "weighted avg       0.86      0.86      0.86     11712\n",
+      "\n",
+      "------------------------------------ RandomForestClassifier() ------------------------------------\n",
+      "Accuracy 0.903\n",
+      "----------------------------------------------------------\n",
+      "Mean of Cross Validation Score 0.8847\n",
+      "----------------------------------------------------------\n",
+      "AUC_ROC Score 0.9634\n",
+      "----------------------------------------------------------\n",
+      "Confusion Matrix\n",
+      "[[5252  480]\n",
+      " [ 656 5324]]\n",
+      "----------------------------------------------------------\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.89      0.92      0.90      5732\n",
+      "           1       0.92      0.89      0.90      5980\n",
+      "\n",
+      "    accuracy                           0.90     11712\n",
+      "   macro avg       0.90      0.90      0.90     11712\n",
+      "weighted avg       0.90      0.90      0.90     11712\n",
+      "\n",
+      "------------------------------------ AdaBoostClassifier() ------------------------------------\n",
+      "Accuracy 0.8566\n",
+      "----------------------------------------------------------\n",
+      "Mean of Cross Validation Score 0.8331\n",
+      "----------------------------------------------------------\n",
+      "AUC_ROC Score 0.9335\n",
+      "----------------------------------------------------------\n",
+      "Confusion Matrix\n",
+      "[[4908  679]\n",
+      " [1000 5125]]\n",
+      "----------------------------------------------------------\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.83      0.88      0.85      5587\n",
+      "           1       0.88      0.84      0.86      6125\n",
+      "\n",
+      "    accuracy                           0.86     11712\n",
+      "   macro avg       0.86      0.86      0.86     11712\n",
+      "weighted avg       0.86      0.86      0.86     11712\n",
+      "\n",
+      "------------------------------------ GradientBoostingClassifier() ------------------------------------\n",
+      "Accuracy 0.8754\n",
+      "----------------------------------------------------------\n",
+      "Mean of Cross Validation Score 0.8502\n",
+      "----------------------------------------------------------\n",
+      "AUC_ROC Score 0.9505\n",
+      "----------------------------------------------------------\n",
+      "Confusion Matrix\n",
+      "[[4982  533]\n",
+      " [ 926 5271]]\n",
+      "----------------------------------------------------------\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.84      0.90      0.87      5515\n",
+      "           1       0.91      0.85      0.88      6197\n",
+      "\n",
+      "    accuracy                           0.88     11712\n",
+      "   macro avg       0.88      0.88      0.88     11712\n",
+      "weighted avg       0.88      0.88      0.88     11712\n",
+      "\n",
+      "------------------------------------ XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
+      "              colsample_bynode=1, colsample_bytree=1, gamma=0, gpu_id=-1,\n",
+      "              importance_type='gain', interaction_constraints='',\n",
+      "              learning_rate=0.300000012, max_delta_step=0, max_depth=6,\n",
+      "              min_child_weight=1, missing=nan, monotone_constraints='()',\n",
+      "              n_estimators=100, n_jobs=4, num_parallel_tree=1, random_state=0,\n",
+      "              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, subsample=1,\n",
+      "              tree_method='exact', validate_parameters=1, verbosity=0) ------------------------------------\n",
+      "Accuracy 0.9129\n",
+      "----------------------------------------------------------\n",
+      "Mean of Cross Validation Score 0.8769\n",
+      "----------------------------------------------------------\n",
+      "AUC_ROC Score 0.9754\n",
+      "----------------------------------------------------------\n",
+      "Confusion Matrix\n",
+      "[[5421  533]\n",
+      " [ 487 5271]]\n",
+      "----------------------------------------------------------\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.92      0.91      0.91      5954\n",
+      "           1       0.91      0.92      0.91      5758\n",
+      "\n",
+      "    accuracy                           0.91     11712\n",
+      "   macro avg       0.91      0.91      0.91     11712\n",
+      "weighted avg       0.91      0.91      0.91     11712\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "createmodel(x,y)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Random Forest, Gradient Boost, Xtreme Gradient Boost give us the best performance, so we further try hyperparameter tuning on them"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Hyperparameter Tuning"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:40:59.299177Z",
+     "iopub.status.busy": "2021-07-05T16:40:59.298762Z",
+     "iopub.status.idle": "2021-07-05T16:40:59.303254Z",
+     "shell.execute_reply": "2021-07-05T16:40:59.301801Z",
+     "shell.execute_reply.started": "2021-07-05T16:40:59.299142Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import GridSearchCV"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:41:00.699099Z",
+     "iopub.status.busy": "2021-07-05T16:41:00.698750Z",
+     "iopub.status.idle": "2021-07-05T16:41:54.416094Z",
+     "shell.execute_reply": "2021-07-05T16:41:54.415022Z",
+     "shell.execute_reply.started": "2021-07-05T16:41:00.699069Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "xtrain,xtest,ytrain,ytest=train_test_split(x,y,test_size=0.25,random_state=randomstate(x,y))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Random Forest"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:41:54.418493Z",
+     "iopub.status.busy": "2021-07-05T16:41:54.417750Z",
+     "iopub.status.idle": "2021-07-05T16:41:54.424355Z",
+     "shell.execute_reply": "2021-07-05T16:41:54.423418Z",
+     "shell.execute_reply.started": "2021-07-05T16:41:54.418443Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "params={'n_estimators':[100,300,500],\n",
+    "            'criterion':['gini','entropty'],\n",
+    "            'max_depth':[None,1,2,3,4,5,6,7,8,9,10],\n",
+    "           'max_features':['int','float','auto','log2']}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:41:54.427242Z",
+     "iopub.status.busy": "2021-07-05T16:41:54.426517Z",
+     "iopub.status.idle": "2021-07-05T16:41:54.437322Z",
+     "shell.execute_reply": "2021-07-05T16:41:54.435883Z",
+     "shell.execute_reply.started": "2021-07-05T16:41:54.427190Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "g=GridSearchCV(RandomForestClassifier(),params,cv=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:41:54.439968Z",
+     "iopub.status.busy": "2021-07-05T16:41:54.439512Z",
+     "iopub.status.idle": "2021-07-05T17:42:07.320823Z",
+     "shell.execute_reply": "2021-07-05T17:42:07.320160Z",
+     "shell.execute_reply.started": "2021-07-05T16:41:54.439918Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "GridSearchCV(cv=10, estimator=RandomForestClassifier(),\n",
+       "             param_grid={'criterion': ['gini', 'entropty'],\n",
+       "                         'max_depth': [None, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10],\n",
+       "                         'max_features': ['int', 'float', 'auto', 'log2'],\n",
+       "                         'n_estimators': [100, 300, 500]})"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "g.fit(xtrain,ytrain)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T17:42:07.322587Z",
+     "iopub.status.busy": "2021-07-05T17:42:07.322161Z",
+     "iopub.status.idle": "2021-07-05T17:42:07.328675Z",
+     "shell.execute_reply": "2021-07-05T17:42:07.327673Z",
+     "shell.execute_reply.started": "2021-07-05T17:42:07.322557Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'n_estimators': 500}\n",
+      "RandomForestClassifier(max_features='log2', n_estimators=500)\n",
+      "0.895093676775149\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(g.best_params_)\n",
+    "print(g.best_estimator_)\n",
+    "print(g.best_score_)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T17:52:25.117160Z",
+     "iopub.status.busy": "2021-07-05T17:52:25.116788Z",
+     "iopub.status.idle": "2021-07-05T17:57:17.067821Z",
+     "shell.execute_reply": "2021-07-05T17:57:17.066617Z",
+     "shell.execute_reply.started": "2021-07-05T17:52:25.117125Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "------------------------------------ RandomForestClassifier(max_features='log2', n_estimators=500) ------------------------------------\n",
+      "Accuracy 0.9044\n",
+      "----------------------------------------------------------\n",
+      "Mean of Cross Validation Score 0.885\n",
+      "----------------------------------------------------------\n",
+      "AUC_ROC Score 0.9651\n",
+      "----------------------------------------------------------\n",
+      "Confusion Matrix\n",
+      "[[5262  474]\n",
+      " [ 646 5330]]\n",
+      "----------------------------------------------------------\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.89      0.92      0.90      5736\n",
+      "           1       0.92      0.89      0.90      5976\n",
+      "\n",
+      "    accuracy                           0.90     11712\n",
+      "   macro avg       0.90      0.90      0.90     11712\n",
+      "weighted avg       0.90      0.90      0.90     11712\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "m=RandomForestClassifier(max_features='log2', n_estimators=500)\n",
+    "m.fit(xtrain,ytrain)\n",
+    "p=m.predict(xtest)\n",
+    "score=cross_val_score(m,x,y,cv=10)\n",
+    "performance(p,ytest,m,xtest,score)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Gradient Boost"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T17:58:51.117177Z",
+     "iopub.status.busy": "2021-07-05T17:58:51.116818Z",
+     "iopub.status.idle": "2021-07-05T17:58:51.120447Z",
+     "shell.execute_reply": "2021-07-05T17:58:51.119819Z",
+     "shell.execute_reply.started": "2021-07-05T17:58:51.117142Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import RandomizedSearchCV"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T17:58:52.395874Z",
+     "iopub.status.busy": "2021-07-05T17:58:52.395308Z",
+     "iopub.status.idle": "2021-07-05T17:58:52.400480Z",
+     "shell.execute_reply": "2021-07-05T17:58:52.399930Z",
+     "shell.execute_reply.started": "2021-07-05T17:58:52.395815Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "params={'n_estimators':[100,300,500],\n",
+    "      'learning_rate':[0.001,0.01,0.10,],\n",
+    "      'subsample':[0.5,1],\n",
+    "      'max_depth':[1,2,3,4,5,6,7,8,9,10,None]}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T17:58:53.916639Z",
+     "iopub.status.busy": "2021-07-05T17:58:53.916103Z",
+     "iopub.status.idle": "2021-07-05T17:58:53.921326Z",
+     "shell.execute_reply": "2021-07-05T17:58:53.920478Z",
+     "shell.execute_reply.started": "2021-07-05T17:58:53.916594Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "g=RandomizedSearchCV(GradientBoostingClassifier(),params,cv=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T17:58:54.635604Z",
+     "iopub.status.busy": "2021-07-05T17:58:54.635275Z",
+     "iopub.status.idle": "2021-07-05T18:53:06.235616Z",
+     "shell.execute_reply": "2021-07-05T18:53:06.234679Z",
+     "shell.execute_reply.started": "2021-07-05T17:58:54.635573Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "RandomizedSearchCV(cv=10, estimator=GradientBoostingClassifier(),\n",
+       "                   param_distributions={'learning_rate': [0.001, 0.01, 0.1],\n",
+       "                                        'max_depth': [1, 2, 3, 4, 5, 6, 7, 8, 9,\n",
+       "                                                      10, None],\n",
+       "                                        'n_estimators': [100, 300, 500],\n",
+       "                                        'subsample': [0.5, 1]})"
+      ]
+     },
+     "execution_count": 85,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "g.fit(xtrain,ytrain)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T18:53:06.237909Z",
+     "iopub.status.busy": "2021-07-05T18:53:06.237460Z",
+     "iopub.status.idle": "2021-07-05T18:53:06.245608Z",
+     "shell.execute_reply": "2021-07-05T18:53:06.244355Z",
+     "shell.execute_reply.started": "2021-07-05T18:53:06.237847Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'subsample': 0.5, 'n_estimators': 100, 'max_depth': 8, 'learning_rate': 0.1}\n",
+      "GradientBoostingClassifier(max_depth=8, subsample=0.5)\n",
+      "0.8977403711168908\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(g.best_params_)\n",
+    "print(g.best_estimator_)\n",
+    "print(g.best_score_)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T18:55:39.112709Z",
+     "iopub.status.busy": "2021-07-05T18:55:39.112375Z",
+     "iopub.status.idle": "2021-07-05T18:57:15.885788Z",
+     "shell.execute_reply": "2021-07-05T18:57:15.884695Z",
+     "shell.execute_reply.started": "2021-07-05T18:55:39.112672Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "------------------------------------ GradientBoostingClassifier(max_depth=8, subsample=0.5) ------------------------------------\n",
+      "Accuracy 0.9062\n",
+      "----------------------------------------------------------\n",
+      "Mean of Cross Validation Score 0.8768\n",
+      "----------------------------------------------------------\n",
+      "AUC_ROC Score 0.9702\n",
+      "----------------------------------------------------------\n",
+      "Confusion Matrix\n",
+      "[[5295  485]\n",
+      " [ 613 5319]]\n",
+      "----------------------------------------------------------\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.90      0.92      0.91      5780\n",
+      "           1       0.92      0.90      0.91      5932\n",
+      "\n",
+      "    accuracy                           0.91     11712\n",
+      "   macro avg       0.91      0.91      0.91     11712\n",
+      "weighted avg       0.91      0.91      0.91     11712\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "m=GradientBoostingClassifier(max_depth=8, subsample=0.5)\n",
+    "m.fit(xtrain,ytrain)\n",
+    "p=m.predict(xtest)\n",
+    "score=cross_val_score(m,x,y,cv=10)\n",
+    "performance(p,ytest,m,xtest,score)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Xtreme Gradient Boost"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:02:31.373415Z",
+     "iopub.status.busy": "2021-07-05T19:02:31.373068Z",
+     "iopub.status.idle": "2021-07-05T19:02:31.378382Z",
+     "shell.execute_reply": "2021-07-05T19:02:31.377400Z",
+     "shell.execute_reply.started": "2021-07-05T19:02:31.373382Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "params={\n",
+    " \"learning_rate\"    : [0.01,0.05, 0.10, 0.15, ] ,\n",
+    " \"max_depth\"        : [ 3, 4, 5, 6, 8, 10, 12, 15],\n",
+    " \"min_child_weight\" : [ 1, 3, 5, 7 ],\n",
+    " \"gamma\"            : [ 0.0, 0.1, 0.2 , 0.3, 0.4 ],\n",
+    " \"colsample_bytree\" : [ 0.3, 0.4, 0.5 , 0.7 ]\n",
+    "    }"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:02:31.892530Z",
+     "iopub.status.busy": "2021-07-05T19:02:31.892195Z",
+     "iopub.status.idle": "2021-07-05T19:02:31.897111Z",
+     "shell.execute_reply": "2021-07-05T19:02:31.895923Z",
+     "shell.execute_reply.started": "2021-07-05T19:02:31.892497Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "g=RandomizedSearchCV(XGBClassifier(),params,cv=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:02:34.952368Z",
+     "iopub.status.busy": "2021-07-05T19:02:34.952049Z",
+     "iopub.status.idle": "2021-07-05T19:05:27.525806Z",
+     "shell.execute_reply": "2021-07-05T19:05:27.524878Z",
+     "shell.execute_reply.started": "2021-07-05T19:02:34.952334Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "RandomizedSearchCV(cv=10,\n",
+       "                   estimator=XGBClassifier(base_score=None, booster=None,\n",
+       "                                           colsample_bylevel=None,\n",
+       "                                           colsample_bynode=None,\n",
+       "                                           colsample_bytree=None, gamma=None,\n",
+       "                                           gpu_id=None, importance_type='gain',\n",
+       "                                           interaction_constraints=None,\n",
+       "                                           learning_rate=None,\n",
+       "                                           max_delta_step=None, max_depth=None,\n",
+       "                                           min_child_weight=None, missing=nan,\n",
+       "                                           monotone_constraints=None,\n",
+       "                                           n_estimators=100...\n",
+       "                                           num_parallel_tree=None,\n",
+       "                                           random_state=None, reg_alpha=None,\n",
+       "                                           reg_lambda=None,\n",
+       "                                           scale_pos_weight=None,\n",
+       "                                           subsample=None, tree_method=None,\n",
+       "                                           validate_parameters=None,\n",
+       "                                           verbosity=None),\n",
+       "                   param_distributions={'colsample_bytree': [0.3, 0.4, 0.5,\n",
+       "                                                             0.7],\n",
+       "                                        'gamma': [0.0, 0.1, 0.2, 0.3, 0.4],\n",
+       "                                        'learning_rate': [0.01, 0.05, 0.1,\n",
+       "                                                          0.15],\n",
+       "                                        'max_depth': [3, 4, 5, 6, 8, 10, 12,\n",
+       "                                                      15],\n",
+       "                                        'min_child_weight': [1, 3, 5, 7]})"
+      ]
+     },
+     "execution_count": 90,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "g.fit(xtrain,ytrain)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:05:27.528110Z",
+     "iopub.status.busy": "2021-07-05T19:05:27.527419Z",
+     "iopub.status.idle": "2021-07-05T19:05:27.537509Z",
+     "shell.execute_reply": "2021-07-05T19:05:27.536404Z",
+     "shell.execute_reply.started": "2021-07-05T19:05:27.528065Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'min_child_weight': 5, 'max_depth': 10, 'learning_rate': 0.15, 'gamma': 0.1, 'colsample_bytree': 0.3}\n",
+      "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
+      "              colsample_bynode=1, colsample_bytree=0.3, gamma=0.1, gpu_id=-1,\n",
+      "              importance_type='gain', interaction_constraints='',\n",
+      "              learning_rate=0.15, max_delta_step=0, max_depth=10,\n",
+      "              min_child_weight=5, missing=nan, monotone_constraints='()',\n",
+      "              n_estimators=100, n_jobs=4, num_parallel_tree=1, random_state=0,\n",
+      "              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, subsample=1,\n",
+      "              tree_method='exact', validate_parameters=1, verbosity=None)\n",
+      "0.9059371395715174\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(g.best_params_)\n",
+    "print(g.best_estimator_)\n",
+    "print(g.best_score_)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:08:13.572829Z",
+     "iopub.status.busy": "2021-07-05T19:08:13.572484Z",
+     "iopub.status.idle": "2021-07-05T19:08:36.785989Z",
+     "shell.execute_reply": "2021-07-05T19:08:36.784870Z",
+     "shell.execute_reply.started": "2021-07-05T19:08:13.572798Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "------------------------------------ XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
+      "              colsample_bynode=1, colsample_bytree=0.3, gamma=0.1, gpu_id=-1,\n",
+      "              importance_type='gain', interaction_constraints='',\n",
+      "              learning_rate=0.15, max_delta_step=0, max_depth=10,\n",
+      "              min_child_weight=5, missing=nan, monotone_constraints='()',\n",
+      "              n_estimators=100, n_jobs=4, num_parallel_tree=1, random_state=0,\n",
+      "              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, subsample=1,\n",
+      "              tree_method='exact', validate_parameters=1, verbosity=None) ------------------------------------\n",
+      "Accuracy 0.9142\n",
+      "----------------------------------------------------------\n",
+      "Mean of Cross Validation Score 0.8822\n",
+      "----------------------------------------------------------\n",
+      "AUC_ROC Score 0.9761\n",
+      "----------------------------------------------------------\n",
+      "Confusion Matrix\n",
+      "[[5425  522]\n",
+      " [ 483 5282]]\n",
+      "----------------------------------------------------------\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.92      0.91      0.92      5947\n",
+      "           1       0.91      0.92      0.91      5765\n",
+      "\n",
+      "    accuracy                           0.91     11712\n",
+      "   macro avg       0.91      0.91      0.91     11712\n",
+      "weighted avg       0.91      0.91      0.91     11712\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "m=XGBClassifier(colsample_bytree=0.3, gamma= 0.1, learning_rate= 0.15, max_depth= 10, min_child_weight= 5)\n",
+    "m.fit(xtrain,ytrain)\n",
+    "p=m.predict(xtest)\n",
+    "score=cross_val_score(m,x,y,cv=10)\n",
+    "performance(p,ytest,m,xtest,score)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We choose random forest as our final model because it gives the highest cross validation score as well as difference between its accuracy score and cross validation score is minimum."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Finalizing the model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:08:48.388688Z",
+     "iopub.status.busy": "2021-07-05T19:08:48.388368Z",
+     "iopub.status.idle": "2021-07-05T19:13:36.449561Z",
+     "shell.execute_reply": "2021-07-05T19:13:36.448834Z",
+     "shell.execute_reply.started": "2021-07-05T19:08:48.388661Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "model=RandomForestClassifier(max_features='log2', n_estimators=500)\n",
+    "model.fit(xtrain,ytrain)\n",
+    "p=model.predict(xtest)\n",
+    "score=cross_val_score(model,x,y,cv=10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Evaluation Metrics"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:13:36.451684Z",
+     "iopub.status.busy": "2021-07-05T19:13:36.451289Z",
+     "iopub.status.idle": "2021-07-05T19:13:37.897673Z",
+     "shell.execute_reply": "2021-07-05T19:13:37.896873Z",
+     "shell.execute_reply.started": "2021-07-05T19:13:36.451642Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "------------------------------------ RandomForestClassifier(max_features='log2', n_estimators=500) ------------------------------------\n",
+      "Accuracy 0.9052\n",
+      "----------------------------------------------------------\n",
+      "Mean of Cross Validation Score 0.8851\n",
+      "----------------------------------------------------------\n",
+      "AUC_ROC Score 0.9653\n",
+      "----------------------------------------------------------\n",
+      "Confusion Matrix\n",
+      "[[5263  465]\n",
+      " [ 645 5339]]\n",
+      "----------------------------------------------------------\n",
+      "Classification Report\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.89      0.92      0.90      5728\n",
+      "           1       0.92      0.89      0.91      5984\n",
+      "\n",
+      "    accuracy                           0.91     11712\n",
+      "   macro avg       0.91      0.91      0.91     11712\n",
+      "weighted avg       0.91      0.91      0.91     11712\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "performance(p,ytest,model,xtest,score)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:13:37.899851Z",
+     "iopub.status.busy": "2021-07-05T19:13:37.899473Z",
+     "iopub.status.idle": "2021-07-05T19:13:39.319284Z",
+     "shell.execute_reply": "2021-07-05T19:13:39.318358Z",
+     "shell.execute_reply.started": "2021-07-05T19:13:37.899802Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "fpred=pd.Series(model.predict_proba(xtest)[:,1])\n",
+    "fpr,tpr,threshold=roc_curve(ytest,fpred)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:13:39.321032Z",
+     "iopub.status.busy": "2021-07-05T19:13:39.320720Z",
+     "iopub.status.idle": "2021-07-05T19:13:39.469322Z",
+     "shell.execute_reply": "2021-07-05T19:13:39.468314Z",
+     "shell.execute_reply.started": "2021-07-05T19:13:39.320978Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7fb4c0705390>"
+      ]
+     },
+     "execution_count": 96,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(fpr,tpr,color='k',label='ROC')\n",
+    "plt.plot([0,1],[0,1],color='b',linestyle='--')\n",
+    "plt.xlabel('False Positive Rate')\n",
+    "plt.ylabel('True Positive Rate')\n",
+    "plt.title('ROC-AUC curve')\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Saving the model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:15:36.273422Z",
+     "iopub.status.busy": "2021-07-05T19:15:36.273091Z",
+     "iopub.status.idle": "2021-07-05T19:15:36.790047Z",
+     "shell.execute_reply": "2021-07-05T19:15:36.789222Z",
+     "shell.execute_reply.started": "2021-07-05T19:15:36.273393Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['census_income.obj']"
+      ]
+     },
+     "execution_count": 97,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import joblib\n",
+    "joblib.dump(model,'census_income.obj')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Fairness"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# This DataFrame is created to stock differents models and fair metrics that we produce in this notebook\n",
+    "algo_metrics = pd.DataFrame(columns=['model', 'fair_metrics', 'prediction', 'probs'])\n",
+    "\n",
+    "def add_to_df_algo_metrics(algo_metrics, model, fair_metrics, preds, probs, name):\n",
+    "    return algo_metrics.append(pd.DataFrame(data=[[model, fair_metrics, preds, probs]], columns=['model', 'fair_metrics', 'prediction', 'probs'], index=[name]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def fair_metrics(dataset, pred, pred_is_dataset=False):\n",
+    "    if pred_is_dataset:\n",
+    "        dataset_pred = pred\n",
+    "    else:\n",
+    "        dataset_pred = dataset.copy()\n",
+    "        dataset_pred.labels = pred\n",
+    "    \n",
+    "    cols = ['statistical_parity_difference', 'equal_opportunity_difference', 'average_abs_odds_difference',  'disparate_impact', 'theil_index']\n",
+    "    obj_fairness = [[0,0,0,1,0]]\n",
+    "    \n",
+    "    fair_metrics = pd.DataFrame(data=obj_fairness, index=['objective'], columns=cols)\n",
+    "    \n",
+    "    for attr in dataset_pred.protected_attribute_names:\n",
+    "        idx = dataset_pred.protected_attribute_names.index(attr)\n",
+    "        privileged_groups =  [{attr:dataset_pred.privileged_protected_attributes[idx][0]}] \n",
+    "        unprivileged_groups = [{attr:dataset_pred.unprivileged_protected_attributes[idx][0]}] \n",
+    "        \n",
+    "        classified_metric = ClassificationMetric(dataset, \n",
+    "                                                     dataset_pred,\n",
+    "                                                     unprivileged_groups=unprivileged_groups,\n",
+    "                                                     privileged_groups=privileged_groups)\n",
+    "\n",
+    "        metric_pred = BinaryLabelDatasetMetric(dataset_pred,\n",
+    "                                                     unprivileged_groups=unprivileged_groups,\n",
+    "                                                     privileged_groups=privileged_groups)\n",
+    "\n",
+    "        acc = classified_metric.accuracy()\n",
+    "\n",
+    "        row = pd.DataFrame([[metric_pred.mean_difference(),\n",
+    "                                classified_metric.equal_opportunity_difference(),\n",
+    "                                classified_metric.average_abs_odds_difference(),\n",
+    "                                metric_pred.disparate_impact(),\n",
+    "                                classified_metric.theil_index()]],\n",
+    "                           columns  = cols,\n",
+    "                           index = [attr]\n",
+    "                          )\n",
+    "        fair_metrics = fair_metrics.append(row)    \n",
+    "    \n",
+    "    fair_metrics = fair_metrics.replace([-np.inf, np.inf], 2)\n",
+    "        \n",
+    "    return fair_metrics\n",
+    "\n",
+    "def plot_fair_metrics(fair_metrics):\n",
+    "    fig, ax = plt.subplots(figsize=(20,4), ncols=5, nrows=1)\n",
+    "\n",
+    "    plt.subplots_adjust(\n",
+    "        left    =  0.125, \n",
+    "        bottom  =  0.1, \n",
+    "        right   =  0.9, \n",
+    "        top     =  0.9, \n",
+    "        wspace  =  .5, \n",
+    "        hspace  =  1.1\n",
+    "    )\n",
+    "\n",
+    "    y_title_margin = 1.2\n",
+    "\n",
+    "    plt.suptitle(\"Fairness metrics\", y = 1.09, fontsize=20)\n",
+    "    sns.set(style=\"dark\")\n",
+    "\n",
+    "    cols = fair_metrics.columns.values\n",
+    "    obj = fair_metrics.loc['objective']\n",
+    "    size_rect = [0.2,0.2,0.2,0.4,0.25]\n",
+    "    rect = [-0.1,-0.1,-0.1,0.8,0]\n",
+    "    bottom = [-1,-1,-1,0,0]\n",
+    "    top = [1,1,1,2,1]\n",
+    "    bound = [[-0.1,0.1],[-0.1,0.1],[-0.1,0.1],[0.8,1.2],[0,0.25]]\n",
+    "\n",
+    "    display(Markdown(\"### Check bias metrics :\"))\n",
+    "    display(Markdown(\"A model can be considered bias if just one of these five metrics show that this model is biased.\"))\n",
+    "    for attr in fair_metrics.index[1:len(fair_metrics)].values:\n",
+    "        display(Markdown(\"#### For the %s attribute :\"%attr))\n",
+    "        check = [bound[i][0] < fair_metrics.loc[attr][i] < bound[i][1] for i in range(0,5)]\n",
+    "        display(Markdown(\"With default thresholds, bias against unprivileged group detected in **%d** out of 5 metrics\"%(5 - sum(check))))\n",
+    "\n",
+    "    for i in range(0,5):\n",
+    "        plt.subplot(1, 5, i+1)\n",
+    "        ax = sns.barplot(x=fair_metrics.index[1:len(fair_metrics)], y=fair_metrics.iloc[1:len(fair_metrics)][cols[i]])\n",
+    "        \n",
+    "        for j in range(0,len(fair_metrics)-1):\n",
+    "            a, val = ax.patches[j], fair_metrics.iloc[j+1][cols[i]]\n",
+    "            marg = -0.2 if val < 0 else 0.1\n",
+    "            ax.text(a.get_x()+a.get_width()/5, a.get_y()+a.get_height()+marg, round(val, 3), fontsize=15,color='black')\n",
+    "\n",
+    "        plt.ylim(bottom[i], top[i])\n",
+    "        plt.setp(ax.patches, linewidth=0)\n",
+    "        ax.add_patch(patches.Rectangle((-5,rect[i]), 10, size_rect[i], alpha=0.3, facecolor=\"green\", linewidth=1, linestyle='solid'))\n",
+    "        plt.axhline(obj[i], color='black', alpha=0.3)\n",
+    "        plt.title(cols[i])\n",
+    "        ax.set_ylabel('')    \n",
+    "        ax.set_xlabel('')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_fair_metrics_and_plot(data, model, plot=False, model_aif=False):\n",
+    "    pred = model.predict(data).labels if model_aif else model.predict(data.features)\n",
+    "    # fair_metrics function available in the metrics.py file\n",
+    "    fair = fair_metrics(data, pred)\n",
+    "\n",
+    "    if plot:\n",
+    "        # plot_fair_metrics function available in the visualisations.py file\n",
+    "        # The visualisation of this function is inspired by the dashboard on the demo of IBM aif360 \n",
+    "        plot_fair_metrics(fair)\n",
+    "        display(fair)\n",
+    "    \n",
+    "    return fair"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>age</th>\n",
+       "      <th>workclass</th>\n",
+       "      <th>fnlwgt</th>\n",
+       "      <th>education</th>\n",
+       "      <th>education.num</th>\n",
+       "      <th>marital.status</th>\n",
+       "      <th>occupation</th>\n",
+       "      <th>relationship</th>\n",
+       "      <th>race</th>\n",
+       "      <th>sex</th>\n",
+       "      <th>capital.gain</th>\n",
+       "      <th>capital.loss</th>\n",
+       "      <th>hours.per.week</th>\n",
+       "      <th>native.country</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.186132</td>\n",
+       "      <td>0.50</td>\n",
+       "      <td>0.131482</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>0.533333</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.428571</td>\n",
+       "      <td>0.945946</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.086358</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.327785</td>\n",
+       "      <td>0.066667</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.6</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.428571</td>\n",
+       "      <td>0.837838</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.272858</td>\n",
+       "      <td>0.75</td>\n",
+       "      <td>0.519066</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.600000</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.428571</td>\n",
+       "      <td>0.945946</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.722618</td>\n",
+       "      <td>0.50</td>\n",
+       "      <td>0.532172</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>0.533333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.8</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.318681</td>\n",
+       "      <td>0.945946</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.186132</td>\n",
+       "      <td>0.50</td>\n",
+       "      <td>0.257392</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>0.533333</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.6</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.340659</td>\n",
+       "      <td>0.945946</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        age  workclass    fnlwgt  education  education.num  marital.status  \\\n",
+       "0  0.186132       0.50  0.131482   0.733333       0.533333        0.666667   \n",
+       "1  0.086358       0.00  0.327785   0.066667       0.400000        0.500000   \n",
+       "2  0.272858       0.75  0.519066   1.000000       0.600000        0.666667   \n",
+       "3  0.722618       0.50  0.532172   0.733333       0.533333        0.000000   \n",
+       "4  0.186132       0.50  0.257392   0.733333       0.533333        0.666667   \n",
+       "\n",
+       "   occupation  relationship  race  sex  capital.gain  capital.loss  \\\n",
+       "0    0.571429           0.2   1.0  0.0           0.0           1.0   \n",
+       "1    0.000000           0.6   0.0  0.0           0.0           1.0   \n",
+       "2    1.000000           0.2   1.0  1.0           0.0           1.0   \n",
+       "3    0.857143           0.8   1.0  0.0           0.0           1.0   \n",
+       "4    0.857143           0.6   1.0  0.0           0.0           1.0   \n",
+       "\n",
+       "   hours.per.week  native.country  \n",
+       "0        0.428571        0.945946  \n",
+       "1        0.428571        0.837838  \n",
+       "2        0.428571        0.945946  \n",
+       "3        0.318681        0.945946  \n",
+       "4        0.340659        0.945946  "
+      ]
+     },
+     "execution_count": 72,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "##train['Sex'] = train['Sex'].map( {'female': 1, 'male': 0} ).astype(int)\n",
+    "x.head()\n",
+    "\n",
+    "#features = [\"Pclass\", \"Sex\", \"SibSp\", \"Parch\", \"Survived\"]\n",
+    "#X = pd.get_dummies(train_data[features])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_data = pd.DataFrame(x)\n",
+    "train_data['income'] = pd.DataFrame(y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#print(X)\n",
+    "\n",
+    "\n",
+    "#combine_final = [train_df, test_df]\n",
+    "#result = pd.concat(combine_final)\n",
+    "#print(result.ifany())\n",
+    "#print(result)\n",
+    "privileged_groups = [{'sex': 1}]\n",
+    "unprivileged_groups = [{'sex': 0}]\n",
+    "dataset_orig = StandardDataset(train_data,\n",
+    "                                  label_name='income',\n",
+    "                                  protected_attribute_names=['sex'],\n",
+    "                                  favorable_classes=[1],\n",
+    "                                  privileged_classes=[[1]])\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "#### Original training dataset"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Difference in mean outcomes between unprivileged and privileged groups = -0.342722\n"
+     ]
+    }
+   ],
+   "source": [
+    "metric_orig_train = BinaryLabelDatasetMetric(dataset_orig, \n",
+    "                                             unprivileged_groups=unprivileged_groups,\n",
+    "                                             privileged_groups=privileged_groups)\n",
+    "display(Markdown(\"#### Original training dataset\"))\n",
+    "print(\"Difference in mean outcomes between unprivileged and privileged groups = %f\" % metric_orig_train.mean_difference())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ipynbname\n",
+    "nb_fname = ipynbname.name()\n",
+    "nb_path = ipynbname.path()\n",
+    "\n",
+    "from sklearn.ensemble import AdaBoostClassifier\n",
+    "import pickle\n",
+    "\n",
+    "data_orig_train, data_orig_test = dataset_orig.split([0.7], shuffle=True)\n",
+    "X_train = data_orig_train.features\n",
+    "y_train = data_orig_train.labels.ravel()\n",
+    "\n",
+    "X_test = data_orig_test.features\n",
+    "y_test = data_orig_test.labels.ravel()\n",
+    "num_estimators = 100\n",
+    "\n",
+    "model = AdaBoostClassifier(n_estimators= 1)\n",
+    "\n",
+    "mdl = model.fit(X_train, y_train)\n",
+    "with open('../../Results/AdaBoost/' + nb_fname + '.pkl', 'wb') as f:\n",
+    "        pickle.dump(mdl, f)\n",
+    "\n",
+    "with open('../../Results/AdaBoost/' + nb_fname + '_Train' + '.pkl', 'wb') as f:\n",
+    "    pickle.dump(data_orig_train, f) \n",
+    "    \n",
+    "with open('../../Results/AdaBoost/' + nb_fname + '_Test' + '.pkl', 'wb') as f:\n",
+    "    pickle.dump(data_orig_test, f) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from csv import writer\n",
+    "from sklearn.metrics import accuracy_score, f1_score\n",
+    "\n",
+    "final_metrics = []\n",
+    "accuracy = []\n",
+    "f1= []\n",
+    "\n",
+    "for i in range(1,num_estimators+1):\n",
+    "    \n",
+    "    model = AdaBoostClassifier(n_estimators= i)\n",
+    "    \n",
+    "    mdl = model.fit(X_train, y_train)\n",
+    "    yy = mdl.predict(X_test)\n",
+    "    accuracy.append(accuracy_score(y_test, yy))\n",
+    "    f1.append(f1_score(y_test, yy))\n",
+    "    fair = get_fair_metrics_and_plot(data_orig_test, mdl)                           \n",
+    "    fair_list = fair.iloc[1].tolist()\n",
+    "    #fair_list.insert(0, i)\n",
+    "    final_metrics.append(fair_list)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "           0         1         2         3         4\n",
+      "0  -0.741932 -0.940403  0.706274  0.000000  0.145814\n",
+      "1  -0.741932 -0.940403  0.706274  0.000000  0.145814\n",
+      "2  -0.537461 -0.484364  0.409891  0.292022  0.099742\n",
+      "3  -0.482904 -0.204766  0.270314  0.313533  0.105164\n",
+      "4  -0.470556 -0.138382  0.236466  0.340949  0.090376\n",
+      "..       ...       ...       ...       ...       ...\n",
+      "95 -0.413469 -0.153160  0.172784  0.332407  0.086249\n",
+      "96 -0.415167 -0.155892  0.174596  0.332106  0.085110\n",
+      "97 -0.413066 -0.151672  0.171656  0.334748  0.084918\n",
+      "98 -0.415433 -0.156145  0.174678  0.328916  0.085864\n",
+      "99 -0.403590 -0.141393  0.160990  0.343876  0.085865\n",
+      "\n",
+      "[100 rows x 5 columns]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>classifier</th>\n",
+       "      <th>T0</th>\n",
+       "      <th>T1</th>\n",
+       "      <th>T2</th>\n",
+       "      <th>T3</th>\n",
+       "      <th>T4</th>\n",
+       "      <th>T5</th>\n",
+       "      <th>T6</th>\n",
+       "      <th>T7</th>\n",
+       "      <th>T8</th>\n",
+       "      <th>...</th>\n",
+       "      <th>T90</th>\n",
+       "      <th>T91</th>\n",
+       "      <th>T92</th>\n",
+       "      <th>T93</th>\n",
+       "      <th>T94</th>\n",
+       "      <th>T95</th>\n",
+       "      <th>T96</th>\n",
+       "      <th>T97</th>\n",
+       "      <th>T98</th>\n",
+       "      <th>T99</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>accuracy</th>\n",
+       "      <td>0.862469</td>\n",
+       "      <td>0.757453</td>\n",
+       "      <td>0.757453</td>\n",
+       "      <td>0.772750</td>\n",
+       "      <td>0.797652</td>\n",
+       "      <td>0.809321</td>\n",
+       "      <td>0.822056</td>\n",
+       "      <td>0.821060</td>\n",
+       "      <td>0.817289</td>\n",
+       "      <td>0.818997</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.860050</td>\n",
+       "      <td>0.859979</td>\n",
+       "      <td>0.860548</td>\n",
+       "      <td>0.860548</td>\n",
+       "      <td>0.860832</td>\n",
+       "      <td>0.861046</td>\n",
+       "      <td>0.861615</td>\n",
+       "      <td>0.861900</td>\n",
+       "      <td>0.862042</td>\n",
+       "      <td>0.862469</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f1</th>\n",
+       "      <td>0.865381</td>\n",
+       "      <td>0.767922</td>\n",
+       "      <td>0.767922</td>\n",
+       "      <td>0.797489</td>\n",
+       "      <td>0.811979</td>\n",
+       "      <td>0.825475</td>\n",
+       "      <td>0.831662</td>\n",
+       "      <td>0.830331</td>\n",
+       "      <td>0.825425</td>\n",
+       "      <td>0.824309</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.862975</td>\n",
+       "      <td>0.863010</td>\n",
+       "      <td>0.863510</td>\n",
+       "      <td>0.863567</td>\n",
+       "      <td>0.864299</td>\n",
+       "      <td>0.864177</td>\n",
+       "      <td>0.864977</td>\n",
+       "      <td>0.865255</td>\n",
+       "      <td>0.865057</td>\n",
+       "      <td>0.865381</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>statistical_parity_difference</th>\n",
+       "      <td>-0.403590</td>\n",
+       "      <td>-0.741932</td>\n",
+       "      <td>-0.741932</td>\n",
+       "      <td>-0.537461</td>\n",
+       "      <td>-0.482904</td>\n",
+       "      <td>-0.470556</td>\n",
+       "      <td>-0.438328</td>\n",
+       "      <td>-0.447929</td>\n",
+       "      <td>-0.570035</td>\n",
+       "      <td>-0.544274</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.413392</td>\n",
+       "      <td>-0.413713</td>\n",
+       "      <td>-0.413503</td>\n",
+       "      <td>-0.414094</td>\n",
+       "      <td>-0.418055</td>\n",
+       "      <td>-0.413469</td>\n",
+       "      <td>-0.415167</td>\n",
+       "      <td>-0.413066</td>\n",
+       "      <td>-0.415433</td>\n",
+       "      <td>-0.403590</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>equal_opportunity_difference</th>\n",
+       "      <td>-0.141393</td>\n",
+       "      <td>-0.940403</td>\n",
+       "      <td>-0.940403</td>\n",
+       "      <td>-0.484364</td>\n",
+       "      <td>-0.204766</td>\n",
+       "      <td>-0.138382</td>\n",
+       "      <td>-0.123168</td>\n",
+       "      <td>-0.152834</td>\n",
+       "      <td>-0.479536</td>\n",
+       "      <td>-0.454018</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.155543</td>\n",
+       "      <td>-0.154990</td>\n",
+       "      <td>-0.153754</td>\n",
+       "      <td>-0.157080</td>\n",
+       "      <td>-0.158706</td>\n",
+       "      <td>-0.153160</td>\n",
+       "      <td>-0.155892</td>\n",
+       "      <td>-0.151672</td>\n",
+       "      <td>-0.156145</td>\n",
+       "      <td>-0.141393</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>average_abs_odds_difference</th>\n",
+       "      <td>0.160990</td>\n",
+       "      <td>0.706274</td>\n",
+       "      <td>0.706274</td>\n",
+       "      <td>0.409891</td>\n",
+       "      <td>0.270314</td>\n",
+       "      <td>0.236466</td>\n",
+       "      <td>0.199982</td>\n",
+       "      <td>0.216645</td>\n",
+       "      <td>0.410609</td>\n",
+       "      <td>0.382213</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.173993</td>\n",
+       "      <td>0.174114</td>\n",
+       "      <td>0.173282</td>\n",
+       "      <td>0.174695</td>\n",
+       "      <td>0.178061</td>\n",
+       "      <td>0.172784</td>\n",
+       "      <td>0.174596</td>\n",
+       "      <td>0.171656</td>\n",
+       "      <td>0.174678</td>\n",
+       "      <td>0.160990</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>disparate_impact</th>\n",
+       "      <td>-1.067475</td>\n",
+       "      <td>-inf</td>\n",
+       "      <td>-inf</td>\n",
+       "      <td>-1.230925</td>\n",
+       "      <td>-1.159850</td>\n",
+       "      <td>-1.076024</td>\n",
+       "      <td>-1.063033</td>\n",
+       "      <td>-1.105433</td>\n",
+       "      <td>-1.752993</td>\n",
+       "      <td>-1.697683</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-1.106795</td>\n",
+       "      <td>-1.105466</td>\n",
+       "      <td>-1.106050</td>\n",
+       "      <td>-1.107005</td>\n",
+       "      <td>-1.111536</td>\n",
+       "      <td>-1.101394</td>\n",
+       "      <td>-1.102302</td>\n",
+       "      <td>-1.094376</td>\n",
+       "      <td>-1.111952</td>\n",
+       "      <td>-1.067475</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>theil_index</th>\n",
+       "      <td>0.085865</td>\n",
+       "      <td>0.145814</td>\n",
+       "      <td>0.145814</td>\n",
+       "      <td>0.099742</td>\n",
+       "      <td>0.105164</td>\n",
+       "      <td>0.090376</td>\n",
+       "      <td>0.097831</td>\n",
+       "      <td>0.099540</td>\n",
+       "      <td>0.105541</td>\n",
+       "      <td>0.111558</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.087619</td>\n",
+       "      <td>0.087348</td>\n",
+       "      <td>0.087137</td>\n",
+       "      <td>0.086963</td>\n",
+       "      <td>0.085378</td>\n",
+       "      <td>0.086249</td>\n",
+       "      <td>0.085110</td>\n",
+       "      <td>0.084918</td>\n",
+       "      <td>0.085864</td>\n",
+       "      <td>0.085865</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7 rows × 101 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               classifier        T0        T1        T2  \\\n",
+       "accuracy                         0.862469  0.757453  0.757453  0.772750   \n",
+       "f1                               0.865381  0.767922  0.767922  0.797489   \n",
+       "statistical_parity_difference   -0.403590 -0.741932 -0.741932 -0.537461   \n",
+       "equal_opportunity_difference    -0.141393 -0.940403 -0.940403 -0.484364   \n",
+       "average_abs_odds_difference      0.160990  0.706274  0.706274  0.409891   \n",
+       "disparate_impact                -1.067475      -inf      -inf -1.230925   \n",
+       "theil_index                      0.085865  0.145814  0.145814  0.099742   \n",
+       "\n",
+       "                                     T3        T4        T5        T6  \\\n",
+       "accuracy                       0.797652  0.809321  0.822056  0.821060   \n",
+       "f1                             0.811979  0.825475  0.831662  0.830331   \n",
+       "statistical_parity_difference -0.482904 -0.470556 -0.438328 -0.447929   \n",
+       "equal_opportunity_difference  -0.204766 -0.138382 -0.123168 -0.152834   \n",
+       "average_abs_odds_difference    0.270314  0.236466  0.199982  0.216645   \n",
+       "disparate_impact              -1.159850 -1.076024 -1.063033 -1.105433   \n",
+       "theil_index                    0.105164  0.090376  0.097831  0.099540   \n",
+       "\n",
+       "                                     T7        T8  ...       T90       T91  \\\n",
+       "accuracy                       0.817289  0.818997  ...  0.860050  0.859979   \n",
+       "f1                             0.825425  0.824309  ...  0.862975  0.863010   \n",
+       "statistical_parity_difference -0.570035 -0.544274  ... -0.413392 -0.413713   \n",
+       "equal_opportunity_difference  -0.479536 -0.454018  ... -0.155543 -0.154990   \n",
+       "average_abs_odds_difference    0.410609  0.382213  ...  0.173993  0.174114   \n",
+       "disparate_impact              -1.752993 -1.697683  ... -1.106795 -1.105466   \n",
+       "theil_index                    0.105541  0.111558  ...  0.087619  0.087348   \n",
+       "\n",
+       "                                    T92       T93       T94       T95  \\\n",
+       "accuracy                       0.860548  0.860548  0.860832  0.861046   \n",
+       "f1                             0.863510  0.863567  0.864299  0.864177   \n",
+       "statistical_parity_difference -0.413503 -0.414094 -0.418055 -0.413469   \n",
+       "equal_opportunity_difference  -0.153754 -0.157080 -0.158706 -0.153160   \n",
+       "average_abs_odds_difference    0.173282  0.174695  0.178061  0.172784   \n",
+       "disparate_impact              -1.106050 -1.107005 -1.111536 -1.101394   \n",
+       "theil_index                    0.087137  0.086963  0.085378  0.086249   \n",
+       "\n",
+       "                                    T96       T97       T98       T99  \n",
+       "accuracy                       0.861615  0.861900  0.862042  0.862469  \n",
+       "f1                             0.864977  0.865255  0.865057  0.865381  \n",
+       "statistical_parity_difference -0.415167 -0.413066 -0.415433 -0.403590  \n",
+       "equal_opportunity_difference  -0.155892 -0.151672 -0.156145 -0.141393  \n",
+       "average_abs_odds_difference    0.174596  0.171656  0.174678  0.160990  \n",
+       "disparate_impact              -1.102302 -1.094376 -1.111952 -1.067475  \n",
+       "theil_index                    0.085110  0.084918  0.085864  0.085865  \n",
+       "\n",
+       "[7 rows x 101 columns]"
+      ]
+     },
+     "execution_count": 78,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "final_result = pd.DataFrame(final_metrics)\n",
+    "final_result[3] = np.log(final_result[3])\n",
+    "final_result = final_result.transpose()\n",
+    "acc_f1 = pd.DataFrame(accuracy)\n",
+    "acc_f1['f1'] = f1\n",
+    "acc_f1 = pd.DataFrame(acc_f1).transpose()\n",
+    "acc = acc_f1.rename(index={0: 'accuracy', 1: 'f1'})\n",
+    "final_result = final_result.rename(index={0: 'statistical_parity_difference', 1: 'equal_opportunity_difference', 2: 'average_abs_odds_difference', 3: 'disparate_impact', 4: 'theil_index'})\n",
+    "final_result = pd.concat([acc,final_result])\n",
+    "final_result.columns = ['T' + str(col) for col in final_result.columns]\n",
+    "final_result.insert(0, \"classifier\", final_result['T' + str(num_estimators - 1)])   ##Add final metrics add the beginning of the df\n",
+    "final_result.to_csv('../../Results/AdaBoost/' + nb_fname + '.csv')\n",
+    "final_result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}